Decision support and knowledge exploitation technologies...

Decision support and knowledge

exploitation technologies for C4ISR

A. AugerD. GouinJ. RoyDRDC Valcartier

Defence R&D Canada – ValcartierTechnical Memorandum

DRDC Valcartier TM 2004-451September 2006

Decision support and knowledge exploitation technologies for C4ISR

A. Auger D. Gouin J. Roy DRDC Valcartier

Defence Research and Development Canada -Valcartier Technical Memorandum DRDC Valcartier TM 2004-451 September 2006

Author

Alain Auger

Approved by

Yves Van Chestein

Section Head/IKM, DRDC Valcartier

Approved for release by

Gilles Bérubé

Chief Scientist, DRDC Valcartier

© Her Majesty the Queen as represented by the Minister of National Defence, 2006

© Sa majesté la reine, représentée par le ministre de la Défense nationale, 2006

DRDC Valcartier TM 2004-451 i

Abstract

In military operations, commanders and decision-makers at all levels work in an information-saturated environment. Turning pieces of information into situation awareness requires the expertise and experience of many. Two main aspects will impact on the next generation of C4ISR systems: advances in command and control (C2), and information technologies, in particular in situation analysis, knowledge exploitation technologies and decision support systems.

In order to facilitate interoperability, growth and maintainability, C4ISR systems must be developed by adhering to a number of open standards. Information technologies will be used to develop net-centric enterprise services (NCES) in order to provide modularity, sharing of decision support tools and services, and interoperability of C4ISR systems.

Knowledge exploitation technologies will provide new C4ISR systems with tools and processes to build actionable knowledge. Like situation awareness, knowledge management is about getting the right information to the right people at the right place and time. Therefore, in the military context, any knowledge management model and any decision-making model, including people, processes and technologies, must contribute directly to the achievement of this goal.

Future C4ISR systems will also require the development and application of new decision science principles adapted to new and evolving decision-making contexts. They will need to incorporate both the decision science principles and new tools into a science-based decision support framework leveraging information and knowledge exploitation technologies.

This document presents a generic, high-level view of current research activities in each of the areas mentioned previously.

Keywords: C4ISR, information technologies, environments, capability, knowledge management, knowledge exploitation, command and control, decision support systems, integration, fusion, ontology, semantics, interoperability.

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Résumé

Dans le cadre des opérations militaires, les commandants et les preneurs de décisions de tous les niveaux travaillent dans un environnement saturé d’information. Transformer ces éléments d’information en éveil situationnel exige diverses expertises et expériences. Deux facteurs majeurs auront un impact significatif sur la capacité de la prochaine génération de systèmes C4ISR de générer et de maintenir des connaissances pouvant être utilisées sur-le-champ : les progrès en commandement et contrôle et ceux en technologies de l’information, tout particulièrement en analyse de la situation, exploitation de la connaissance et systèmes d’aide à la décision.

Afin de faciliter leur interopérabilité, leur croissance et leur maintenance, les systèmes de C4ISR doivent être développés en conformité avec un certain nombre de normes publiques. Les technologies de l’information seront mises à profit sous forme de services d’entreprise réseautés, dans le but de supporter la modularité, le partage d’outils et services d’aide à la décision et l’interopérabilité des systèmes C4ISR.

Les technologies d’exploitation de la connaissance devraient fournir aux futurs systèmes C4ISR un ensemble d’outils et processus facilitant la transformation de cette connaissance en actions. Tout comme l’éveil situationnel, le but de la gestion des connaissances consiste à procurer la bonne information à la bonne personne au bon moment et au bon endroit. Ainsi, dans le contexte militaire, tout modèle de gestion de la connaissance et tout modèle d’aide à la décision, incluant les personnes, les processus et les technologies, doivent contribuer directement à l’atteinte de cet objectif.

Les futurs systèmes de C4ISR vont exiger également le développement et l’application de nouveaux principes de la science de la décision adaptés aux contextes nouveaux et changeants de prise de décision. Ces systèmes devront incorporer à la fois les nouveaux principes et outils de la science de la décision dans un cadriciel d’aide à la décision s’appuyant sur des technologies de l’information et de l’exploitation des connaissances.

Ce document présente une vue générique de haut niveau des activités de recherche actuelles dans chacun des domaines mentionnés précédemment.

Mots-clés: C4ISR, technologies de l’information, environnements, capabilité, gestion de la connaissance, exploitation des connaissances, commandement et contrôle, systèmes d’aide à la décision, intégration, fusion, ontologies, sémantique, interopérabilité.

DRDC Valcartier TM 2004-451 iii

Executive summary

The Revolution in Military Affairs (RMA) has moved to centre-stage the requirement for information dominance in the joint battlespace. It is predicted that the greatest change in the conduct of future military operations will be the result of the application of information technology to military command and control (C2). Commanders and decision-makers at all levels need enough information to make decisions but need to be supported by technology so that they are not overwhelmed with information.

Two main aspects will impact the next generation of C4ISR systems: advances in command and control, and information technologies, in particular in situation analysis, knowledge exploitation technologies and decision support systems.

The development of a computer-based support system (CBSS) requires the incremental integration of existing and new support capabilities. These support capabilities should be regarded as some kind of “agents” having some degree of autonomy, each one interacting with its own changing environment, which could be the external physical world or other agents. Hence, there is a requirement that the capabilities must, at a minimum, communicate with one another or, ideally, cooperate with one another. In order to facilitate interoperability, growth and maintainability, C4ISR software must be developed by adhering to a number of open standards. In providing support to C4ISR systems, information technologies will be guided by the new trend towards net-centric enterprise services (NCES), which will provide modularity, sharing of decision support tools and services, and interoperability between C4ISR systems.

Knowledge exploitation technologies will provide new C4ISR systems with tools and processes to build actionable knowledge. Like situation awareness, knowledge management is about getting the right information to the right people at the right place and time. Therefore, in the military context, any knowledge management model and any decision-making model, including people, processes and technologies, must contribute directly to the achievement of this goal. As organizations begin to work and collaborate virtually, collaborative tools enable people to share data, information and knowledge in real time. On the one hand, collaborative environments encourage people to build trust and enhance communication skills. On the other hand, collaborative environments create great expectations for interoperability of legacy and new information systems and for knowledge representation models.

An important challenge for the next generation of C4ISR systems is to develop a CBSS that takes advantage of all the technological opportunities while keeping it totally compatible with the way humans execute the tasks to be supported. The development of support systems includes the participation of experts from the application domain, i.e., the subject matter experts, system designers and human factor specialists to ensure the cognitive fit between the CBSS and the decision-makers, in order to maximize decision-making effectiveness. Knowledge exploitation technologies will be essential in order to capture and facilitate the use of actionable knowledge in such decision support systems. Future C4ISR systems will require the development and application of new decision science principles adapted to new and

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evolving decision-making contexts. They will need to incorporate both the decision science principles and new tools into a science-based decision support framework enabled by information and knowledge exploitation technologies.

This document is of interest to any person concerned with future C4ISR systems, from an acquisition, a design and development or an end-user perspective.

Auger, A., Gouin, D., Roy, J. 2006. Decision Support and Knowledge Exploitation Technologies for C4ISR. DRDC Valcartier TM-2004-451. DRDC Valcartier.

DRDC Valcartier TM 2004-451 v

Sommaire

La révolution dans les affaires militaires a mis au premier plan le besoin de la dominance informationnelle comme stratégie des nouvelles opérations militaires. Il est prédit que le plus grand changement dans la conduite des opérations militaires futures sera lié à l’application des technologies de l’information au commandement et contrôle. Les commandants et preneurs de décision à tout niveau de commandement requièrent un niveau suffisant d’information pour prendre des décisions mais doivent être adéquatement supportés par la technologie afin de ne pas faire face à une surabondance d’information.

Deux facteurs auront un impact significatif dans le développement des systèmes de C4ISR : les progrès en commandement et contrôle (C2) et ceux en technologies de l’information, tout particulièrement en analyse de la situation, exploitation de la connaissance et systèmes d’aide à la décision.

Le développement d’un système d’aide à la décision nécessite l’intégration graduelle de capacités existantes et nouvelles. Ces capacités de support devraient être considérées comme des agents ayant un niveau d’autonomie, chacun interagissant avec son propre environnement dynamique, celui-ci pouvant être le monde physique réel ou encore l’ensemble des autres agents. Par conséquent, ces capacités doivent au minimum être en mesure de communiquer ou encore mieux collaborer avec les autres agents. Afin de faciliter l’interopérabilité, la croissance et la maintenance des systèmes, le logiciel des systèmes C4ISR doit être développé en conformité à un certain nombre de standards ouverts. Les technologies de l’information seront mises à profit sous forme de services d’entreprise réseautés, dans le but de supporter la modularité, le partage d’outils et services d’aide à la décision et l’interopérabilité des systèmes C4ISR.

Les technologies d’exploitation de la connaissance devraient fournir aux futurs systèmes C4ISR un ensemble d’outils et processus facilitant la transformation de cette connaissance en actions. Comme pour l’éveil situationnel, la gestion de la connaissance se préoccupe d’obtenir la bonne information à la bonne personne, à la bonne place et au bon moment. Par conséquent, dans le contexte militaire, tout modèle de gestion de la connaissance et de prise de décision, incluant personnes, processus et technologies, doit contribuer directement à la réalisation de cet objectif. Au fur et à mesure que les organisations commencent à travailler et collaborer de façon virtuelle, les outils de travail collaboratif permettent aux usagers de partager des données, de l’information et de la connaissance en temps réel. D’un coté les environnements de travail collaboratif encouragent les gens à développer la confiance réciproque et améliorer leurs talents de communication. D’un autre côté, les environnements de travail collaboratif créent des attentes en termes d’interopérabilité avec les systèmes patrimoniaux et nouveaux et au niveau des modèles de représentation de la connaissance.

Un défi important pour la prochaine génération de systèmes C4ISR est de développer des systèmes d’aide à la décision qui exploitent toutes les opportunités technologiques tout en demeurant complètement adaptés à la façon avec laquelle les humains exécutent leurs tâches. Le développement de systèmes d’aide à la décision doit inclure la participation des experts du

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domaine de l’application, i.e., les experts des sujets matières (Subject Matter Experts), les concepteurs de systèmes et les spécialistes des facteurs humains afin de garantir une adéquation cognitive entre le système et les preneurs de décision et de maximiser l’efficacité de la prise de décision. Dans ces nouveaux systèmes d’aide à la décision, les technologies d’exploitation des connaissances seront essentielles afin de capturer et de faciliter l’utilisation de connaissances pouvant être transformées en actions. Les futurs systèmes de C4ISR vont exiger également le développement et l’application de nouveaux principes de la science de la décision adaptés aux contextes nouveaux et changeants de prise de décision. Ces systèmes devront incorporer à la fois les nouveaux principes et outils de la science de la décision dans un cadriciel d’aide à la décision s’appuyant sur des technologies de l’information et de l’exploitation des connaissances.

Ce document présente une vue générique et de haut niveau les activités de recherché courante dans chacun des créneaux mentionnés précédemment.

Auger, A., Gouin, D., Roy, J. 2006. Decision Support and Knowledge Exploitation Technologies for C4ISR. DRDC Valcartier TM-2004-451. DRDC Valcartier.

DRDC Valcartier TM 2004-451 vii

Table of Contents

Abstract........................................................................................................................................ i

Résumé ....................................................................................................................................... ii

Executive summary ................................................................................................................... iii

Sommaire.................................................................................................................................... v

Table of Contents ..................................................................................................................... vii

List of Figures............................................................................................................................ ix

List of Tables.............................................................................................................................. x

Acknowledgements ................................................................................................................... xi

1. Introduction ................................................................................................................... 1

2. C4ISR Requirements ..................................................................................................... 2

3. The Command and Control Domain ............................................................................. 3

4. Information Management Requirements for Future C4ISR .......................................... 6 4.1. Situation awareness and situation analysis....................................................... 6 4.2. The COP concept.............................................................................................. 6

5. C4ISR Support Systems ................................................................................................ 8 5.1. The ISR challenge ............................................................................................ 8 5.2. Stress and pressure ........................................................................................... 8 5.3. Need for technological support ........................................................................ 9 5.4. Ideal support system......................................................................................... 9 5.5. Generic support system .................................................................................. 10 5.6. The right information ..................................................................................... 10

viii DRDC Valcartier TM 2004-451

6. Information Technologies ........................................................................................... 13 6.1. Key architectural trends.................................................................................. 13 6.2. Communications and system interfaces ......................................................... 25 6.3. Data and information fusion........................................................................... 25 6.4. Knowledge management and exploitation ..................................................... 27 6.5. Information visualization................................................................................ 42 6.6. Human-computer interactions ........................................................................ 43 6.7. Decision support systems ............................................................................... 44

7. Support System Development Process ........................................................................ 46

8. Some Information Technologies (IT) Forecasts for DND/CF..................................... 48 8.1. Smart Enterprise Study findings..................................................................... 48

9. Conclusion................................................................................................................... 50

10. References ................................................................................................................... 51

11. Distribution list ............................................................................................................ 57

DRDC Valcartier TM 2004-451 ix

List of Figures

Figure 1 - C2 Enduring Principles [Alberts, 2002]..................................................................... 3

Figure 2 - Command and Control (Adapted from [Knight, 2002]) ............................................ 4

Figure 3 - Command and Control (Adapted from: [Knight, 2002]) ........................................... 4

Figure 4 - A Generic Support System ...................................................................................... 10

Figure 5 - The Right Information? ........................................................................................... 11

Figure 6 - Exploiting Information Sources and Tools/Services ............................................... 11

Figure 7: DND/CF BOSTIS framework................................................................................... 15

Figure 8: Future Interdepartmental Marine Information Exchange Concept ........................... 17

Figure 9: The general process of engaging a Web Service....................................................... 20

Figure 10 - Overview of Decision Support Systems and Knowledge Exploitation Elements.. 28

Figure 11 - Knowledge Management and Exploitation Dimensions........................................ 29

Figure 12 - Ontology Samples.................................................................................................. 34

Figure 13: Example of Ontology Engineering Architecture [Kietz et al, 2000]....................... 35

Figure 14: Knowledge Process [Staab et al, 2002]................................................................... 36

Figure 15 - Sample Computer Flaws Taxonomy [Landwehr, 1994]........................................ 37

Figure 16 - Canadian Forces Lessons Learned Process [Boury-Brisset et al., 2002]............... 40

Figure 17: Performance of Data Mining Desktop Tools [King et al., 1998]............................ 41

Figure 18 - Information hierarchy [Waltz, 1998] ..................................................................... 44

Figure 19 - Hierarchy of systems ............................................................................................. 44

Figure 20 - CBSS development process ................................................................................... 46

Figure 21: Maturity Level of Some KM Technologies [Smart Enterprise Study, 2004] ......... 49

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List of Tables

Table 1 - Common Portal Functionalities [ADGA, 2003]........................................................ 31

Table 2 - Common Text Handling Tasks ................................................................................. 39

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Acknowledgements

Special thanks to Mario Couture from DRDC Valcartier for his in-depth review and contribution to enhance this memorandum.

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DRDC Valcartier TM 2004-451 1

1. Introduction

Released in July 1999, [Strategy 2020] stresses that the ongoing information-based Revolution in Military Affairs (RMA) will transform the nature of warfare and the conduct of military operations. One of the principal transformations will be that, in future, commanders and decision-makers at all levels will work in an information-saturated environment in which there is too much information available – rather than too little. Military operations will be increasingly conducted in a “real-time” world in which decisions, actions and their results at all levels will be known nearly instantaneously. In such an environment, commanders and decision-makers at all levels will need enough information to make decisions but not so much information that they are overwhelmed. Adding to the challenge is the expectation that military sensor data is expected to increase a billion-fold in the coming decade. In order to make sense out of the coming flood of information, a whole new approach to the collection, processing and dissemination of this information will be required if useful understanding is to be obtained from this enormous volume of data [DCDS, 2002]. How will future C4ISR systems make sense of a situation?

As stated by [Alberts and Hayes, 2003], “Making sense of a situation begins with putting the available information about the situation into context and identifying the relevant patterns that exist. […] Being able to bring available information to bear involves more than collecting needed information. It also means being able to make information available to everyone who needs it, in a form that they can use it, in a secure and timely manner. Turning pieces of information into situation awareness requires the expertise and experience of many”.

Two main aspects will impact the next generation of C4ISR systems: advances in command and control (C2), and information technologies, in particular in situation analysis, decision support systems and knowledge exploitation technologies.

This document presents a generic, high-level view of current research activities and trends in each of these areas.

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2. C4ISR Requirements

For [Perricelli and Corea, 2000], the battlespace of 2010 and beyond will be characterized by widely separated forces and non-contiguous areas of operations. Distributed operations will be decentralized in execution and carried out in accordance with a centralized, fully integrated joint plan. This plan will be orchestrated and supported by a pervasive and resilient C4ISR1 infrastructure. Achieving dominance across the air/land/sea/space and cyber-domains are essential prerequisites to achieving success in the battlespace of the future. Three broad capabilities form the foundation for this dominance: knowledge, speed and power.

Knowledge encompasses battlespace information and situational awareness. Knowledge about one’s own forces, friendly forces and the enemy’s forces is essential to battle effectiveness. As the primary and universal enabler for virtually all battlespace functions, knowledge is paramount; it affects everything at all levels (operational, tactical and strategic). Conversely, the absence of sufficient knowledge puts everything at risk in battlespaces. Assembly and delivery of sufficient knowledge will be ensured by selection of the most relevant information so that commanders will not be overwhelmed with inappropriate information. This will better shape the battlespace and create conditions that will permit and support distributed, decentralized, non-contiguous operations.

“C4ISR is the embodiment of information technology and allows the U.S. Army and its allies to achieve information dominance in the battlespace. The combined effectiveness and integration of C4ISR systems will permit the successful conduct of rapid and sustained operations in any environment under any environmental conditions. Information technology has and will continue to revolutionize the way we operate and fight in the battlespace. How we exploit and adapt this technology will be the measure of our success in the battlespace of the 21st century and beyond 2010 towards the 2025 timeframe.” [Perricelli and Corea, 2000]

In Canada, according to [DND Capability Outlook, 2002] “the Department’s information and intelligence capability will face major challenges in the next decade, particularly in the areas of human resources and the CF’s organizational capacity to exploit and disseminate information.” It is expected that “the evolution of information technology will increasingly assist the CF in integrating the traditional forms of information operations with sophisticated all-source intelligence, surveillance, and reconnaissance (ISR) in a fully synchronized information campaign. This requires the development of an integrated information environment/enterprise architecture – globally interconnected, secure and seamless.”

1 Command, Control, Communications, Computers, Intelligence, Surveillance, and Reconnaissance (C4ISR)


3. The Command and Control Domain

Several models of the command and control (C2) process have been proposed over the years. Many documents have been published on the subject under the Command and Control Research Program (CCRP2). Generally, C2 is considered as "the exercise of authority and direction by a designated commander over assigned forces in the accomplishment of the force's mission". [McCann and Pigeau, 2000] argue that C2 should be defined as "the establishment of common intent to achieve coordinated action". Another definition states that C2 is "the process by which commanders can plan, direct, control and monitor any operation for which they are responsible".

Whatever the definition, it is generally accepted that C2 is composed of a number of dynamic and cyclic perceptual, procedural and cognitive activities, achieved either by humans, computer systems or both. At a very high level, these activities can be summarized as the perception of the environment, the appraisal of the situation, decision-making about a course of action, and the implementation of the chosen plan. Figure 1 from [Alberts, 2002] illustrates the enduring principles of C2.

Awareness

Operating Environment

Understanding Command Intent

Cognitive Domain

Physical Domain

Information Domain

SituationMonitoring

ResponseManagement

Synchronization

Information Systems

Sensemaking

Figure 1 - C2 Enduring Principles [Alberts, 2002]

Figure 2 and Figure 3, slightly adapted from [Knight, 2002], each provide an interesting perspective of the nature of the command and control domain. As we can see, support from

2 http://www.dodccrp.org/index.htm


information technologies and more specifically from knowledge exploitation technologies will be mandatory in the implementation of such a vision.

Commander

Physical domain

Information domain

Cognitive domain

Objects/EventsObjects/Events

Commander’s Intent

Commander’s Intent

PriorKnowledge

AndMental models

PriorKnowledge

AndMental models

BackgroundInfo

Current Info

GlobalISR &

Operational Data

Analysis, fusion &Integrated Info Products,

Analysis, fusion &Integrated Info Products,

Tasking Tasking

Actions/EffectsActions/Effects

SynchronizationSynchronization

OperationalOrders

OperationalOrders Information

OrdersInformation

Orders

PlanningPlanning

Decision-Making

COP

Operations

Pre-planned Responses to Time

Critical Combat Information

Figure 2 - Command and Control (Adapted from [Knight, 2002])

Access Control – Dissemination LayerSecurity Layer

Information Grid – Collaborative Information Environment

Virtu

alK

now

ledg

eB

ase

Glo

bal I

SR &

Ope

ratio

nal

Dat

a

BackgroundInformation

CurrentInformation

Fusion Capability

Sources

Sensors

TDLs

U . S . AI R F O R CEU . S . AI R F O R CE

Reports / BFT

Observations

Operational data

Sources

Geomatics

Meteorology

Etc...

Orders, Plans

Intelligence

Own ForceInfo

Contextual data

COP

Commanders

Decision Makers

DeployedForces

HigherAuthorities

Feedback &Requirements

Commander'sIntent

Decision Support& Tasking

Figure 3 - Command and Control (Adapted from: [Knight, 2002])


In 2004, the Technical Committee Program (TTCP) C3I3 Working Group published three reports describing the state of the art on information fusion, situation analysis, situation awareness and decision-making.

The first report [Roy, 2004] reviews the concepts and models for information fusion in support of coalition situation awareness. As such it provides the common foundation for the demonstration of information fusion capabilities later in the AG-2 and National Programs by reviewing the command and control process, decision-making models, situational awareness and analysis concepts, and information fusion to support decision-making.

The second report [Bossé, 2004] reviews the mathematical foundations of information fusion and the specific fusion methods derived from them.

The third report [Wark, 2004] reviews the computational foundations and implementations of information fusion. It focuses on higher levels of information fusion and issues relating to an integrated information fusion environment, and does not otherwise address the specialized issues particular to multi-sensor fusion and control.

3 Command, Control, Communications and Information Systems


4. Information Management Requirements for Future C4ISR

4.1. Situation awareness and situation analysis

The term situation awareness (SAW) has emerged as an important concept in dynamic human decision-making. [Endsley, 1995] proposed a general definition of SAW that has been found to be applicable across a wide variety of domains. She describes SAW as "the perception of the elements in the environment within a volume of time and space, the comprehension of their meaning and the projection of their status in the near future".

Situation analysis (SA) is defined as a process, the examination of a situation, its elements, and their relations, to provide and maintain a product, i.e., a state of SAW for the decision-maker [Roy, 2001]. The SA process encapsulates that part of the overall decision-making cycle that is concerned with understanding the world of interest. There is a real situation in the environment, and the SA process will create and maintain a mental representation of it, the situation model, in the mind of the decision-maker(s).

An important component of situation analysis is threat analysis, defined in [Roy et al., 2002] as the analysis of the past, present and expected actions of external entities, and their consequences. The aim of the analysis is to identify menacing situations and quantitatively establish the degree of their impact on the mission, the intents, the plans, the actions and the human and material assets of some valuable units to be protected, taking into account the defensive actions that could be performed to reduce, avoid or eliminate the identified menace.

4.2. The COP concept

The CF identifies its SAW capability as the common operating picture (COP) or recognized picture, specifically the recognized maritime picture (RMP) in the case of the Navy. Many concerns have been raised with this terminology. First, it is not clear what is meant by common. Depending on their role, staff officers need to see different pieces of the current situation. The word ‘consistent’ has been suggested as a replacement for ‘common’, reflecting the common set of information sources rather than a common representation, where each commander or staff officer is able to filter and customize his view based on his own needs or task.

The term ‘picture’ is also misleading. For many people, the COP is a picture, and mostly this picture is a map. For most allied countries, this picture is provided by the Global Command and Control System (GCCS), with the capability to show tracks superimposed onto a map. The COP is actually more than a map or picture. Consider the following examples of information a joint commander and his staff need in order to understand the current situation:

• higher commander’s intent • friendly and opposing forces deployment


• opposing forces Tables of Organization and Equipment (TO&Es) • allied forces Tables of Organization and Equipment (TO&Es) • allied forces doctrine and staff operating procedures • opposing forces doctrine • planned course of action • social, cultural and political context of a country • weather • terrain • lessons learned from previous similar operations • open source information.

Although a lot of this information is or can be geo-referenced and superimposed onto a map background, some of it cannot be depicted on a map or is best represented using non-geospatial representations. This is particularly true in the wide variety of military force planning scenarios, including peace support operations and asymmetric/terrorist threats.

So, rather than simply being a picture/map, situation awareness is provided by the assembly of several information pieces. A better definition of COP provided by the US DoD [CJCSI 31051.01, 200x] is: “the integrated capability to receive, correlate, and display a Common Tactical Picture (CTP), including planning applications and theater-generated overlays/projections (i.e., Meteorological and Oceanographic (METOC), battleplans, force position projections)….”. To remove the recursive aspect of this definition, we could say: “The common operational picture is the integrated capability to receive, correlate and display heterogeneous sources of information in order to provide a consistent view of the battlespace”. The key word here is ‘capability’. This capability is provided through the use of information technology, including data/information fusion, knowledge management and information visualization, but it also needs to be aligned with the user’s requirements and constraints.


5. C4ISR Support Systems

5.1. The ISR challenge

Nowadays, operating in the ‘Information Age’ is seriously challenging 21st century decision-makers. With the availability of increasingly numerous information sources, decision-making is facing the problem of having to make decisions when faced with too much information, rather than too little. As stated by [Barber, 2001], “it is anticipated that the coming decade will bring a billion-fold increase in C4ISR data (computing power X bandwidth X sensor acuity). To make sense out of this flood of information, the CF will have to create a new way of processing sensor and intelligence information, and of providing the results to commanders who must make timely operational decisions”.

In a paper published in 2001, Cmdr Josh Barber introduced working definitions for ISR, developed after extensive consultation with DND and CF personnel involved in the ISR community:

“Intelligence. The product of processed information concerning hostile or potentially hostile forces;

Surveillance. Systematic observation by technical sensors or human beings. This implies continuous 24 hours a day/7 days a week surveillance of areas or forces of interest;

Reconnaissance. Directed mission(s) to obtain specific information; and

ISR. The capability that integrates command direction, sensors, and processed formation and intelligence with timely dissemination in order to provide decision makers with effective ‘Situational Awareness’. [Barber, 2001]

According to [Barber, 2001] the key concepts to note in the definition for ISR is “integrated”, “timely” and “ituational awareness”. What ISR is really about is the provision of the right information to the right people and places at the right time.

5.2. Stress and pressure

Operational trends in warfare put the C2 process under pressure. For example, in complex military environments known to be non-collaborative, the C2 process is stressed mainly by real-time and uncertainty issues. The technological evolution constantly increases the lethality and the reach of weapons, the scope of the battlefield, and the tempo of the engagement. Moreover, a huge load of uncertain data and information is generated about the environment. Clearly, all these data and information may exceed human information processing capabilities. Yet, the military community typically maintains that the dominant requirement to


counter the threat and ensure the survivability of a military platform is the ability to perform C2 activities quicker and better than the adversary.

5.3. Need for technological support

Information technology support is thus typically required to cope with human limitations in such complex environments. This emphasizes the need for real-time, computer-based support systems (CBSSs) to bridge the gap between the cognitive demands inherent in the accomplishment of the C2 process and human limitations. Successful exploitation of resources (e.g., sensors, weapons) during the conduct of C2 activities is linked with the modelling and design of systems to support cognitive demands in a timely manner, using uncertain information.

5.4. Ideal support system

A CBSS is a computerized system that is intended to interact with and complement a human [Elm et al., 2002]. Such support systems range from formulae embedded within a spreadsheet to sophisticated autonomous reasoning ‘agents’. Whatever the nature of the CBSS, the objective is to develop CBSS features that intuitively fit the perceptual and cognitive processes of the human user. The ideal CBSS is one that:

Provides the information needed by the human decision-maker, as opposed to raw data that must be transformed by the human into the information needed. If the data can be perfectly transformed into information by the CBSS, no human cognitive effort is required for the transformation / no cognitive work is expended on the data, allowing total focus on the domain’s problem-solving.

Can be controlled effortlessly by a human. It presents the information to the human as effortlessly as a window allows a view of a physical world outside. In this sense, the CBSS is ‘transparent’ to the user. If the interaction with the CBSS is completely effortless, no human cognitive effort is required to manage and interact with the CBSS, allowing total focus on the domain’s problem-solving.

Complements the cognitive power of the human mind. In this way, the CBSS not only avoids creating a world that is ripe for human decision-making errors but can include features that complement the trends and power of human cognitive processes. Decision-making errors categorized by such terms as fixation, garden path, etc. are avoided by the form of the decision-making world embodied by the CBSS.

Supports a wide variety of problem-solving strategies, from nearly instinctive reactions to events to knowledge-based reasoning on fundamental principles in a situationally independent manner.

Effective CBSSs are those that “make the problem transparent to the user”.


5.5. Generic support system

Figure 4 shows a generic support system. On the right-hand side are the capabilities supporting the C2 activities per se. On the left-hand side are the necessary ancillary capabilities. All these heterogeneous capabilities are glued together through the core system architecture.

Situation Analysisand Awareness

Support Capabilities

Decision MakingSupport Capabilities

Response PlanningSupport Capabilities

Response Controland Monitoring

Support Capabilities

CoreSystem

ArchitectureA Priori Knowledge

Management andExploitation Server

Visualization andHuman Computer

Interactions

PeripheralSystemsInterface

Internal andExternal

Communications

Figure 4 - A Generic Support System

5.6. The right information

In her model, [Endsley, 1995] presents SAW as a stage separate from decision-making (DM) and action. SAW is described as the decision-maker's internal model of the state of the environment. Based on that representation, the decision-maker can decide what to do about the situation and carry out any necessary actions. There is thus a strong link between SAW and the DM processes. SAW is represented as the main precursor to decision-making, and is the key factor determining decision quality. Enhancing SAW improves the probability of selecting the appropriate course of action in most situations. Consequently, SAW is considered essential for commanders to conduct DM activities, and the improvement of the human DM process can be seen as highly related to the enhancement of SAW.

In the same vein, SAW quality can be related to the amount of information available to an individual. Clearly, circumstances where no information is available should result in poor SAW, leading with high probability to very low decision quality. In such a case, a natural reaction would be to provide mechanisms to increase the amount of information available to the decision-makers in order to improve SAW quality. One could even claim that a good approach to reach optimal SAW would be to provide as much information as possible. However, this does not necessarily represent the best solution, as more information does not automatically mean better SAW to ensure better human performance. First, all this information may exceed the human information processing capabilities, leading to cognitive overload. Second, not all the data and information available in the environment is relevant and useful for reaching an optimal decision. In fact, in some situations, most of the data can be seen as distracters and noise for the decision-maker, and may thus reduce his/her level of


SAW. The decision-maker must detect and use only a specific fraction of this information to enhance his/her SAW and DM processes. Such considerations lead to the concept of “the right information, at the right place, at the right time”, as opposed to “all information, everywhere, all the time”. This is illustrated in Figure 5.

Information

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isio

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nfor

mat

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lity

NoInformation

All InformationEverywhereAt All Times

CognitiveOverload

Information FusionKnowledge ManagementAdvanced Visualization

Single WorkstationContextual Portfolios

Task Oriented ServicesEtc.

System Integration andInteroperability Issues

The Right InformationAt the Right PlaceAt the Right Time

Figure 5 - The Right Information?

Clearly, research and technological advancements toward providing “all information, everywhere, all the time” are necessary, as such progresses ensure that “the right information, at the right place, at the right time” will actually be available to the decision-makers. Figure 6 presents a different perspective of a generic CBSS that takes into account these issues.

Tool /Service

#1

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#2

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#N

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forSituation AnalysisDecision Making

KnowledgeExploitation

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All InformationEverywhereAt All Times

System Integration &Interoperability, Middleware,

Net-Centric Enterprise Services

The Right InformationTo The Right PersonAt The Right Time

People. . . . . . . . . . . .

Info. Fusion, Knowledge Management,Advanced Visual., Contextual Portfolios

Task Oriented ServicesInfo. Centric Workspace

Figure 6 - Exploiting Information Sources and Tools/Services


In Figure 6, the support capabilities of Figure 5 are represented as a set of independent system tools and services supporting situation analysis, decision-making, knowledge exploitation, etc. Part of the necessary interactions between these tools/services is enabled by the system integration and interoperability layer. However, the system also requires the appropriate mechanisms, based on technological enablers such as information fusion and knowledge management, to provide “the right information, to the right person, at the right time”.


6. Information Technologies

6.1. Key architectural trends

Typically, the development of a CBSS requires the incremental integration of existing and new support capabilities (i.e., a set of largely autonomous capabilities that must be integrated and interleaved into an overall process flow). These support capabilities should be implemented as agents having some degree of autonomy, each one interacting with its own changing environment, which could be the external physical world or other agents. Hence, there is a requirement that the capabilities must, at a minimum, communicate with one another or, ideally, cooperate with one another.

In order to facilitate interoperability, growth and maintainability, C4ISR software must be developed by adhering to a number of open standards. Military, commercial and not-for-profit organizations have set up significant programs and projects to address and improve interoperability. The following sections present a number of these programs, important standards, and technological trends.

6.1.1. Network centric warfare and net-centric enterprise services

Over the last several years, the US Department of Defense and its allies have been going through a major transformation which exploits the power of the Information Age. This transformation focuses on information superiority to implement network centric warfare (NCW). NCW networks the three domains of warfare [Alberts et al., 2001]:

Physical Domain

• All elements of the force are robustly networked, achieving secure and seamless connectivity and interoperability.

Information Domain

• The force has the capability to share, access and protect information to a degree that it can establish and maintain an information advantage over an adversary.

• The force has the capability to collaborate in the information domain, which enables it to improve its position through processes of correlation, fusion and analysis.


Cognitive Domain

• The force has the capability to develop high quality awareness and share this awareness.

• The force has the capability to develop a shared understanding including commander’s intent.

• The force has the capability to self-synchronize its operations.

The US Defense Information Systems Agency (DISA) is responsible for building, operating and protecting joint command, control, communications and computer (C4) capabilities to help catalyze and sustain the Department of Defense’s (DoD) transformation from platform-centric to net-centric operations [Quagliotti, 2004]. One of the initiatives to implement NCW is net-centric enterprise services (NCES). NCES will provide a common set of information capabilities across the Global Information Grid (GIG), allowing DoD, the intelligence community, and coalition partners to pull information they want, whenever they need it, from wherever they are – within appropriate constraints. The overarching objective of the GIG vision is to provide users with information superiority, decision superiority, and full-spectrum dominance [NSA, 2004].

6.1.2. Global Command and Control System (GCCS) and Joint Command and Control (JC2)

As part of their transformation initiative, beginning in 2006 the US DoD will be replacing the Global Command and Control System by the Joint Command and Control (JC2) system. JC2 will use Web services and fit with DoD's plan for NCW and NCES [Temin, 2004]. The interesting aspect is that in order to achieve interoperability, allied nations will no longer need to share the same application (e.g., GCCS). Rather, each nation will have its own application while sharing some Web services.

6.1.3. BOSTIS framework

The BOSTIS framework is a component-based architecture developed by DND/CF. It is currently being enhanced and documented in the Defence Enterprise Architecture Manual (DEAM).


Figure 7: DND/CF BOSTIS framework

The DND BOSTIS framework is being currently developed under ADM (IM). It is presented as a central method to the integration of all perspectives of the enterprise, which emphasizes the multitude of interdependencies between strategic thrusts and practices, and the capabilities to deliver on objectives and goals. This framework highlights the high level of importance that information and security have for National Defence. Specific tools and methods will be used to develop each architecture view; a powerful hyper-relational electronic model and electronic classification system will assist in analyzing and sharing the departmental interdependencies.

Business View

The Business View represents the highest view of the enterprise. This view makes the connections to the external influences of DND/CF and translates their impact through policy and procedures that ultimately govern programs.

Operational View

This view primarily describes the relationships and interdependencies between all DND/CF functions and services, highlighting information flows, responsibilities and resources required to deliver capabilities.


System View

The System View is the central piece to responding to ADM (IM)'s need to define system architectures and applications that enable and support the business.

Technical View

The DND/CF Technical View is comprised of technology principles and best practices, domains, and standards, policies and guidelines, to support the systems and applications specific to DND/CF.

Information View

The Information View provides the definitions and structure of the information that an organization requires to make decisions and manage its resources.

Security View

The Security View provides the framework for translating the business risk assessments into security policies and procedures that identify direct security constraints on system and application design and development. To properly provide advice on the security constraints, the technical requirements must be enabled through the capability and certification of existing technologies.

6.1.4. Military exchange data model/repositories

6.1.4.1. C2IEDM

In order to improve interoperability, NATO nations have developed an information exchange data model. This was initially known as the Army Tactical Command and Control (ATCCIS) data model, and later became the Land C2 Information Exchange Data Model (LC2IEDM), and more recently the Command and Control Information Exchange Data Model (C2IEDM). The new standard is under the control of the Multilateral Interoperability Program (MIP), which involves over 24 nations [MIP, 2004a].

The C2IEDM [MIP, 2004b]:

• models the information that allied nation commanders need to exchange (both vertically and horizontally);

• provides message exchange mechanisms (MEM), consisting of a suite of formatted messages that conform to Adat-P3;

• provides data exchange mechanisms (DEM) to automatically push data, using database replication. The DEM also allows the establishment of rules for the exchange of information, such as what information should be sent to whom, when and over what communication medium.


In short, C2IEDM provides interoperability at the data level. Each nation’s system can use its own internal data model, but mapping is required into the common exchange data model. The MIP has organized several interoperability trials and the C2IEDM has shown its strengths in terms of interoperability and efficiency.

6.1.4.2. MIMDEX

The Maritime Information Management and Data Exchange Study (MIMDEX) is a common repository of data that is strictly controlled through authentication and access control. MIMDEX is superior to CANMARNET (Canadian Maritime Network) because it is a stand-alone web-based network with dedicated operators who can pass information, communicate in real time, and maintain awareness of other departments' concerns. In its first iteration, the MIMDEX system will operate at the "PROTECTED" level of security and it will have the capability to migrate into a "SECRET" level government network in the future. This system will have many advantages, including displaying geo-spatial information in close to real time, allowing updates by members on-line, email, and chat. Reference material in a shared on-line database will be available for participating government departments, and a system will be put in place to allow each member to "flag" or alert others about particular concerns. This is a novel system that allows interdepartmental collaboration while remaining within Canadian privacy and Charter constraints. In short, MIMDEX is superior to CANMARNET because it is a two-way (or multi-way) system that allows the marine community to interact in real time to better share information and alert each other to possible challenges or threats to marine security” [MIMDEX, 2004].

Figure 8: Future Interdepartmental Marine Information Exchange Concept


6.1.5. Web standards and protocols

The advent and rapid evolution of World Wide Web (www, Web or W3) technologies have had a considerable impact on the connectivity of people, organizations and information, creating a universe of network-accessible information, and embodiment of human knowledge [W3C, 2004a]. The Web has a body of software and a set of protocols and conventions defined through the World Wide Web Consortium [W3C, 2004b]).

6.1.5.1. Hypertext markup language (HTML)

“HTML is the lingua franca for publishing hypertext on the World Wide Web. It is a non-proprietary format based upon SGML (Standard Generalized Markup Language (ISO 8879:1986)), and can be created and processed by a wide range of tools, from simple plain text editors – you type it in from scratch – to sophisticated WYSIWYG authoring tools. HTML uses tags such as <h1> and </h1> to structure text into headings, paragraphs, lists, hypertext links” [W3C, 2004c].

6.1.5.2. Extensible markup language (XML)

XML (eXtensible Markup Language) is a markup language much like HTML, but designed to describe and carry data. HTML is about displaying information (to display data and to focus on how data looks), while XML is about describing information. The tags used to mark up HTML documents and the structure of HTML documents are predefined. The author of HTML documents can only use tags that are already defined in the HTML standard (like <p>, <h1>, etc.). XML allows the author to define his own tags and document structure using a Document Type Definition (DTD) or an XML Schema. XML is a cross-platform, software- and hardware-independent tool for transmitting information [W3C, 2004c].

The following is an example of an XML structure and tags:

<note> <to>John</to> <from>Jim</from> <heading>Reminder</heading> <body>Don't forget the meeting this afternoon</body> </note>

“It has been amazing to see how quickly the XML standard has been developed and how quickly a large number of software vendors have adopted the standard. We strongly believe that XML will be as important to the future of the Web as HTML has been to the foundation of the Web and that XML will be the most common tool for all data manipulation and data transmission” [W3C, 2004c].

6.1.5.3. Extensible hypertext markup language (XHTML)

Extensible hypertext markup language (XHTML™) is a family of current and future document types and modules that reproduce, subset and extend HTML, reformulated in XML.


XHTML family document types are all XML-based, and ultimately are designed to work in conjunction with XML-based user agents. XHTML is the successor of HTML [W3C, 2004c].

6.1.5.4. Web services

The World Wide Web is increasingly used for application-to-application communication. The programmatic interfaces made available are referred to as Web services [W3C, 2002]. “A Web service is a software system designed to support interoperable machine-to-machine interaction over a network. It has an interface described in a machine-processable format (specifically WSDL – Web Service Definition Language). Other systems interact with the Web service in a manner prescribed by its description using SOAP4 messages, typically conveyed using HTTP with an XML serialization in conjunction with other Web-related standards” [W3C, 2004d]. SOAP is an XML-based messaging system, which specifies all the necessary rules for locating Web services, integrating them into applications, and communicating between them.

The purpose of a Web service is to provide some functionality on behalf of its owner – a person or organization, such as a business or an individual. The provider entity is the person or organization that provides an appropriate agent to implement a particular service. A requester entity is a person or organization that wishes to make use of a provider entity's Web service. It will use a requester agent to exchange messages with the provider entity's provider agent. (See Figure 1-1: Basic Architectural Roles).

The general process of engaging a Web service is the following [W3C, 2004d]:

1. the requester and provider entities become connected and known to each other (or at least one becomes known to the other);

2. the requester and provider entities somehow agree on the service description and semantics that will govern the interaction between the requester and provider agents;

3. the service description and semantics are realized by the requester and provider agents; and

4. the requester and provider agents exchange messages, thus performing some task on behalf of the requester and provider entities.

4 Simple Object Access Protocol SOAP is a lightweight protocol for exchange of information in a decentralized, distributed environment. It is an XML based protocol that consists of three parts: an envelope that defines a framework for describing what is in a message and how to process it, a set of encoding rules for expressing instances of application-defined datatypes, and a convention for representing remote procedure calls and responses (www.factory3x5.com/more_info/glossary.xml)


Figure 9: The general process of engaging a Web Service

6.1.5.5. Semantic Web standards

As described in [W3C, 2004e], the semantic Web is a vision for the future of the Web in which information is given explicit meaning, making it easier for machines to automatically process and integrate information available on the Web. The semantic Web is currently building on XML's ability to define customized tagging schemes, Resource Description Framework (RDF)’s flexible approach to representing data, and the Web Ontology Language (OWL)’s ability to formally describe the meaning of terminology used in Web documents. Semantic Web supports advanced Web search, software agents and knowledge management. A further description of semantic Web technologies is provided in section 6.4.3.4.

XML provides a surface syntax for structured documents, but imposes no semantic constraints on the meaning of those documents.

XML Schema is a language for restricting the structure of XML documents and also extends XML with datatypes.

RDF is a datamodel for objects (“resources”) and relations between them and provides simple semantics for this datamodel, and these datamodels can be represented in an XML syntax. RDF Schema is a vocabulary for describing properties and classes of RDF resources, such as the title, author and modification date of a Web page, copyright and licensing information about a Web document, or the availability schedule for some shared resources. RDF is based on the idea of identifying things using Web identifiers (called Uniform Resource Identifiers, or URIs), and describing resources in terms of simple properties and property values.


OWL adds more vocabulary for describing properties and classes: among others, relations between classes (e.g., disjointness), cardinality (e.g., "exactly one"), equality, richer typing of properties, characteristics of properties (e.g., symmetry), and enumerated classes.

6.1.6. Multitier application environments

Multitier applications enable enterprises to share information with, and permit collaboration among, employees, customers and business partners. A typical multitier application has three tiers: a front end that performs authentication and serves as an interface to the user, a middle tier that handles authorization and business logic, and a back end that acts as a store for information.

Today's enterprises gain a competitive advantage by quickly developing and deploying custom applications that provide unique business services. Whether they are internal applications for employee productivity or Internet applications for specialized customer or vendor services, quick development and deployment are the key to success.

Portability and scalability are also important for long-term viability. Enterprise applications must scale from small working prototypes and test cases to complete 24/7, enterprise-wide services, accessible by tens, hundreds, or even thousands of clients simultaneously.

However, multitier applications are hard to architect. They require bringing together a variety of skill sets and resources, legacy data and legacy code. In today's heterogeneous environment, enterprise applications have to integrate services from a variety of vendors with a diverse set of application models and other standards. Industry experience shows that integrating these resources can take up to 50% of application development time.

Conversely, multitier application environments have been designed to facilitate the development of multitier applications. These are broken down into two camps: the Java 2 Platform, Enterprise Edition (J2EE) for all non-Microsoft platforms, and .NET (Dot NET) for Microsoft platforms.

6.1.6.1. Java 2 Platform Enterprise Edition (J2EE)

Java 2 Platform, Enterprise Edition (J2EE) defines the standard for developing component-based multitier enterprise applications. The J2EE platform simplifies enterprise applications by basing them on standardized, modular components, by providing a complete set of services to those components, and by handling many details of application behaviour automatically, alleviating complex programming. J2EE defines the standard for developing multitier enterprise applications. Pioneered by Sun Microsystems, the J2EE standard represents a collaboration between leaders from throughout the enterprise software arena. Partners include OS and database management system providers, middleware and tool vendors, and vertical market applications and component developers. Working with these partners, Sun has defined a robust, flexible platform that can be implemented on the wide variety of existing enterprise systems currently available, and which supports the range of applications that IT organizations need to keep their enterprises competitive [Java, 2004].


The J2EE platform takes advantage of many features of the Java 2 Platform, Standard Edition (J2SE), such as "Write Once, Run Anywhere" portability, JDBC API for database access, CORBA technology for interaction with existing enterprise resources, and a security model that protects data even in Internet applications. Building on this base, J2EE adds full support for Enterprise JavaBeans components, Java Servlets API, JavaServer Pages and XML technology. The J2EE standard includes complete specifications and compliance tests to ensure portability of applications across the wide range of existing enterprise systems capable of supporting the J2EE platform. In addition, the J2EE specification now ensures Web services interoperability.

According to [Java, 2004]: “The success of the J2EE platform in the enterprise continues to rise as more than two-thirds of enterprise software development managers use the J2EE platform to develop and deploy their applications. With addition of interoperable Web services and other new features in version 1.4, the J2EE platform will continue to be the industry standard for enterprise solutions for many years to come”.

6.1.6.2. .NET (Dot NET)

“Microsoft .Net uses a set of software technologies for connecting information, people, systems and devices. This new generation of technology is based on Web services, small building-block applications that can connect to each other as well as to other, larger applications over the Internet” [Microsoft, 2004]. Web services are invoked over the Internet by means of industry-standard protocols including SOAP, XML and Universal Description, Discovery and Integration (UDDI). UDDI is a public registry, offered at no cost, where one can publish and inquire about Web services.

Although .NET leverages on the W3C standards and protocols, it does not provide full cross-platforms interoperability as J2EE provides. For instance, Web services developed on a J2EE platform may not interoperate on a .NET platform. Although this may not be an issue if an organization is only based on Microsoft platforms, it does not ensure interoperability with other organizations and coalition partners.

6.1.7. Open Database Connectivity (ODBC)

In order to ensure interoperability and portability, an open standard has been developed in terms of database access. “Open DataBase Connectivity (ODBC), a standard database access method developed by the SQL Access group in 1992. The goal of ODBC is to make it possible to access any data from any application, regardless of which database management system (DBMS) is handling the data. ODBC manages this by inserting a middle layer, called a database driver, between an application and the DBMS. The purpose of this layer is to translate the application's data queries into commands that the DBMS understands. For this to work, both the application and the DBMS must be ODBC-compliant – that is, the application must be capable of issuing ODBC commands and the DBMS must be capable of responding to them” [ODBC, 2004].


6.1.8. Metadata standards

The use of metadata standards improves interoperability. Some of the metadata standards that should be looked at for C4ISR systems are:

• Dublin Core. The Dublin Core Metadata set is a standard for cross-domain information resource description. There are no fundamental restrictions to the types of resources to which Dublin Core Metadata can be assigned [Dublin, 2004].

• The Federal Geographic Data Committee (FGDC) approved the Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998) in June 1998. Through this standard, governmental, non-profit, and commercial participants worldwide can make their collections of spatial information searchable and accessible on the Internet [FGDC, 2004].

• ADM (IM). In Canada, ADM (IM) has a working group dedicated to information management domain standards. This domain includes:

o Standards Management Framework

To ensure that DND systems evolve and utilise the upcoming technologies, it is imperative that standards are continuously managed. If the management framework is not in place, the current standards tables within the Technical View will quickly become stale and inaccurate over time. Standards Management describes a generic framework, through which Information Management and Information Technology (IM/IT) standards are adopted/developed, approved, deployed, monitored and retired within Department of National Defence.

o Metadata Sub-Domain

The Metadata sub-domain is part of the Information Management Domain. It defines the standards, tools and techniques, for the definition, interchange, and dissemination of metadata. It includes the rules, principles and best practices related to metadata directories/repositories.

At ADM (IM), the Information Management Environment Domain defines the principles, best practices, technologies and standards that enable all information life-cycle stages of the Management of Recorded Information (MoRI), including planning, collection, creation or generation of information; its organization, retrieval, use, accessibility and transmission; its storage and protection; and finally, its disposition through transfer to archives or destruction. This domain contains several sub-domains:


• electronic document management • records management • data management • data interchange • document interchange • email management • forms and e-forms management • imaging • data warehousing • metadata • knowledge management • information management tools • terminology.

6.1.9. Open Geospatial Consortium (OGC) standards

The Open Geospatial Consortium, Inc. (OGC) is a non-profit, international, voluntary consensus standards organization that is leading the development of standards for geospatial and location-based services. Through member-driven consensus programs, OGC works with government, private industry and academia to create open and extensible software application programming interfaces for geographic information systems (GIS) and other mainstream technologies. Adopted specifications are available for the public's use at no cost [OGC, 2004a].

Three of the main specifications that are provided for open access to geospatial data are the following [OGC, 2004b]:

• Web Map Service (WMS) provides three operations protocols (GetCapabilities, GetMap, and GetFeatureInfo) in support of the creation and display of registered and superimposed map-like views of information that come simultaneously from multiple sources that are both remote and heterogeneous. This service applies to raster products.

• The purpose of the Web Feature Server Interface Specification (WFS) is to describe data manipulation operations on OpenGIS Simple Features (feature instances) such that servers and clients can “communicate” at the feature level. This service applies to vector products.

• The Geographic Markup Language (GML) is an XML encoding for the transport and storage of geographic information, including both the geometry and properties of geographic features.

6.1.10. Sensor Web

“Sensor Web is an independent network of wireless, intra-communicating sensor pods, deployed to monitor and explore a limitless range of environments” [JPL, 2004]. This


initiative originates from the NASA/Jet Propulsion Laboratory in 1997. “The purpose of a Sensor Web system is to extract knowledge from the data it collects and use this information to intelligently react and adapt to its surroundings. It links a remote end user’s cognizance with the observed environment” [Sensors OnLine, 2004]. For instance, the ability to view traffic camera information in a Web browser is a simple Sensor Web service. In the future, more intelligence will be provided in Sensor Webs, where the information collected will be used to launch some actions such as setting alarms or refining the collection management plan.

6.2. Communications and system interfaces

The CBSS must have the necessary interfacing mechanisms to enable its interaction with the other systems (e.g., sensors, weapon systems, etc.) required and used to fulfill the mission. Connectivity and communications are a critical cornerstone for the CBSS. There is a requirement for assured (sufficient, redundant), secure and accessible communication paths to guarantee the exchange of relevant information.

6.3. Data and information fusion

Data fusion (DF) is a key enabler to meeting the demanding requirements of military command decision support systems (DSSs). In this regard, the data fusion model maintained by the Joint Directors of Laboratories’ Data Fusion Group (JDL DFG) is the most widely-used method for categorizing data fusion-related functions [Steinberg et al., 1998]. The following concise definition of data fusion has been proposed by the JDL DFG: Data fusion is the process of combining data to refine state estimates and predictions. Then, the JDL distinction among fusion “levels” provides a way of differentiating between data fusion processes that relate to the refinement of “objects”, “situations,” “threats” and “processes.” Note that the JDL differentiate the levels first on the basis of types of estimation process that typically relates to the type of entity for which the state is estimated. If the process involves explicit association in performing state estimates (usually, but not necessarily the case), there is a corresponding distinction among the types of association process. The definitions are as follows:

Level 0 − Sub-Object Data Assessment: Estimation and prediction of signal/object observable states on the basis of pixel/signal level data association and characterization; Level 0 assignment involves hypothesizing the presence of a signal (i.e., of a common source of sensed energy) and estimating its state.

Level 1 − Object Assessment: Estimation and prediction of entity states on the basis of observation-to-track association, continuous state estimation (e.g., kinematics) and discrete state estimation (e.g., target type and ID); Level 1 assignments involve associating reports (or tracks from prior fusion nodes) into association hypotheses, for which we use the convenient shorthand ‘tracks’. Each such track represents the hypothesis that the given set of reports is the total set of reports available to the system referencing some individual entity.

Level 2 − Situation Assessment: Estimation and prediction of relations among entities, to include force structure and cross-force relations, communications and perceptual influences,


physical context, etc.; Level 2 assignment involves associating tracks (i.e., hypothesized entities) into aggregations. The state of the aggregate is represented as a network of relations among its elements. Any variety of relations is considered − physical, informational, perceptual, organizational − as appropriate to the given system’s mission. As the class of relationships estimated and the numbers of interrelated entities broaden, they tend to use the term ‘situation’ for an aggregate object of estimation.

Level 3 − Impact Assessment: Estimation and prediction of effects on situations of planned or estimated/predicted actions by the participants, to include interactions between action plans of multiple players (e.g., assessing susceptibilities and vulnerabilities to estimated/predicted threat actions given one’s own planned actions); Level 3 assignment is usually implemented as a prediction function, drawing particular kinds of inferences from Level 2 associations. Level 3 fusion estimates the “impact” of an assessed situation; i.e., the outcome of various plans as they interact with one another and with the environment. The impact estimate can include likelihood and cost/utility measures associated with potential outcomes of a player’s planned actions.

Level 4 − Process Refinement: Adaptive data acquisition and processing to support mission objectives. Level 4 processing involves planning and control, not estimation. Level 4 assignment involves assigning tasks to resources.

6.3.1. Adaptive data and information fusion

The data fusion model proposed by the JDL DFG, with its process refinement capability, implicitly supposes that all levels of fusion are integrated. This means, for instance, that the Level 1 data fusion process (object assessment) should be polished and enhanced leveraging from the results of higher levels of data fusion (Levels 2 and 3). Close integration is claimed to be essential to gain the maximum benefits from the data fusion process.

In this regard, to improve the process of data fusion, and ultimately that of perception, in a multi-sensor system, processing and resources must be constantly managed and coordinated. This defines the problem of process refinement or adaptive data fusion. Development of adaptive data fusion systems is driven by the belief in continuous refinement. This essentially concerns the study/implementation of ways to improve and optimize the ongoing fusion process. Process refinement closes the loop over all the fusion levels and, based on the newly available contextual information, it develops options for collecting further information, allocates/directs resources towards the achievement of the mission goals and/or tunes the processing parameters for the real-time improvement of the effectiveness of the whole fusion process.

Even though it has witnessed a growing interest during the last few years, process refinement, which represents a logical extension of the fusion tree, is still the least mature part of the fusion process. DRDC Valcartier has initiated R&D activities to study the specific problem of integrating all levels of data fusion involved in the compilation and analysis of the tactical picture, and to demonstrate the benefits of integration. The work undertaken seeks a new formalism, based on the control theory, for making the data fusion process adaptive. Therefore, process refinement is currently being addressed from a control theory viewpoint.


The Situation Analysis and Information Fusion (SAIF) group at DRDC Valcartier has also proposed the concept of a framework for integrated data fusion composed of a number of interconnected data fusion sub-processes or agents.

6.4. Knowledge management and exploitation

From Francis Bacon (1605) to Edvinsson and Malone (1997), [Kakabadse et al., 2003] reported more than thirty definitions for knowledge in the literature. Hence, for [McElro, 2000] “knowledge management is the most successful fuzzy idea in the history of management”. Definitions of knowledge management usually range from data warehousing or data mining to more or less vague notions of communities of practice and virtual collaborative environments.

Despite the variety of these definitions, it seems that there is consensus on the idea that knowledge management is about getting the right information to the right people at the right place and time. Therefore, in the military context, any knowledge management model, including people, processes and technologies, must contribute directly to the achievement of this goal. This is also true for any decision support model.

For [Waruszynsky 2003], “as organizations begin to work and collaborate virtually, the need for collaborative tools enables people to share data, information and knowledge in real time. Collaborative environments encourage people to build trust, enhance communications skills, and facilitate interactive communication and social interaction. The building blocks of virtual collaborative environments—people, process and technology—demonstrate the importance of sustaining successful teams across global networks”.

Figure 10 below shows different dimensions that may be involved in advanced decision support systems.


Figure 10 - Overview of Decision Support Systems and Knowledge Exploitation Elements


Figure 11 - Knowledge Management and Exploitation Dimensions

6.4.1. A Priori knowledge management

As discussed in [Boury-Brisset, 2001], the techniques being developed for the support of capabilities in command and control support systems are becoming increasingly more sophisticated, particularly through the incorporation of methods for high-level reasoning processes. A fundamental component of these processes is a database (or databases) containing a priori knowledge, i.e., static (or slowly changing) information/knowledge to support the various processes providing the commander with a gain in the level of situation awareness. This knowledge refers to different aspects such as expected objects, behaviours of objects, and relationships between objects, political and geographical knowledge, platform characteristics, mission guidelines, weapon characteristics, corridors and flight paths, lethality, emitter characteristics, doctrine, etc., that can be used by the support capabilities.

The expression “a priori knowledge” entails several things. The “knowledge” portion of the expression refers to the fact that the database may contain more than just a description of objects. More abstract notions about the behaviour of these objects or the relationships between objects can also be included. It is the existence of this different level of information, so important to sophisticated CBSS processes, that characterizes the database as containing knowledge, not simply data. The “a priori” portion of the expression entails that the contents of the database are mostly collected, analyzed and stored in advance of use in the support processes.


It thus seems useful to go beyond the basic concept of a support database towards the more advanced one of a knowledge server that must incorporate various knowledge sources useful to the information process. Databases are limited both in data representation and in capabilities for supporting the data fusion process. If databases are well suited to describe objects and their attributes, they are less appropriate to represent taxonomies of objects, or specify the behaviour of objects. So, more expressive knowledge representation formalisms are needed to capture the semantics and behaviour of concepts, and mechanisms are required to exploit this formalism (e.g., inference capabilities, automatic classifier, semantic retrieval).

To satisfy these knowledge representation requirements (expressiveness and heterogeneity of knowledge sources), the concept of a knowledge server has been proposed in [Boury-Brisset, 2001], aiming at incorporating different types of knowledge sources that could be exploited by a decision support system. This knowledge server is called KNOWMES (Knowledge Management and Exploitation Server). The system envisioned aims to integrate various information and knowledge sources, theoretical knowledge related to the domain theory (doctrines, procedures, etc.), static domain knowledge encapsulated in ontologies, as well as experiential knowledge.

An overview discussion on the application of knowledge management principles and techniques in the military context can be found in [McIntyre et al., 2003].

For a comprehensive overview of technologies for supporting virtual collaborative environments, see [Waruszynski 2003].

6.4.2. Knowledge management technologies

According to the Technology Investment Strategy (2002), R&D in information and knowledge management (IKM) shall cover and support three strategic objectives:

(A) Advanced techniques and architectures for more effective sharing of information and knowledge: Investigate and advance techniques and architectures for more effective sharing of information and knowledge across the enterprise’s distributed and heterogeneous information systems. This activity will benefit knowledge creation and workflow integration in both the corporate and military operational environments.

(B) Knowledge modelling, discovery and creation for improved situational awareness: Investigate and advance knowledge creation and discovery techniques through which we collect and process information to gain sufficient situational awareness to be able to project possible future courses of action or trends with confidence. Investigation of these techniques will offer improvements in knowledge management applicable to both corporate and military environments.

(C) Visualization and geospatial systems for enhanced understanding of spatial- and time-related knowledge: Investigate and advance techniques for multi-dimensional information management, analysis and visualization to enhance the understanding of spatial- and time-related knowledge. These techniques should also facilitate the discovery of knowledge in complex environments. Particular emphasis


will be given to reducing operator workloads by introducing trusted intelligent assistants. [TIS, 2002]

The next generation of C4ISR systems will require innovation in each of these three research domains.

6.4.2.1. Portal architectures

Information portals have become an effective means of enabling organizations to access, share and manage information and knowledge of pertinence to the organizations.

A “Portal” refers to a collection of technologies and processes required to locate, retrieve, organize and publish structured and unstructured information in a secure manner and to integrate applications and services embodied in an organization. Portals support the formulation and collaboration of on-line communities [ADGA, 2003].

A portal can provide an organization with the following Web capabilities:

personalized access Users can define what they want

role-based filtering of content users retrieve information based on role or possibly rank

user-friendly interaction users can navigate instinctively (they understand what they see)

multi-system integration users directly access the systems they require to complete daily tasks

scalability users experience good on-line response time with lowest possible hardware investment

single sign-on users require only one password for all systems they use (with validation)

content management users need to find documents and knowledge-sharing to be effective

security systems and content are accessed by appropriate personnel

community support employees and suppliers can collaborate on-line

a general development framework

a technology tool kit that can aggregate various internal organizational software

Table 1 - Common Portal Functionalities [ADGA, 2003]

Seen from a technical point of view, portals are frameworks which integrate various tools and applications together in a common framework. Ideally speaking, a single central place to look for everything is the best that you can do provided that the portal software performance is good. All information can be cross-linked and stored once; updates can be performed and the


intellectual capital of the organization protected. A portal like this can offer a complete environment for everyone in the organization to do his or her job, completely and seamlessly integrated with the desktop [RoweBots, 2004].

According to [RoweBots, 2004], the overall benefits are:

• a single point of sharing and communication in the organization;

• elimination of duplicate information;

• reduction in information overload;

• improved communication with all partners and customers;

• access to a consistent set of applications with support and backups;

• international and multi-site collaboration without difficulties of shared drives and similar issues;

• simple, cross-functional, cross-organization communication;

• creating norms of information sharing and knowledge creation for the organization;

• communicating new reward systems which emphasize knowledge sharing.

Knowledge portals are collaborative environments that may also include the following functionalities: scheduling, calendaring, file sharing, emailing, chat groups/discussion fora, bulletin boards, expertise locator, latest news, team co-location, task management, workflow management, brainstorming, on-line meetings, and other collaborative software. Knowledge portal technology links virtual teams and communities into a shared workspace [Waruszynski, 2003]. These features can support communities of practice efficiently. Communities of practice are groups that form to share what they know and to learn from one another regarding some aspect of their work. In their thesis, Kendall and McHale [Kendall and McHale, 2003] demonstrate how the US Naval Intelligence Community, through the implementation of communities of practice, reduced duplication of effort, increased collaboration between personnel, and better supported the resources in its people. [Gauvin et al., 2004] introduced new key concepts for a situational awareness knowledge portal where context, ontology and portfolios are intertwined to support contextualized knowledge management activities.

The value of portal technology in providing coalition situation awareness still has to be demonstrated but the premises are all present to enable it. However, “portals are all about vision and organizational alignment with technology. The technology is only 20% of the problem. The other 80% is making sure that the technology aligns with the business requirements and delivers true value to the enterprise” [ADGA, 2003].

The US Horizontal Fusion Program, a US DoD transformation initiative, is exploring portal technology as a way to support net-centric warfare [Ref., Williams, 2003]. Its objectives are to:


• integrate data from disparate sources for rapid and effective decision-making to make forces less vulnerable and more lethal;

• enable the troops to get the information that is relevant to them so that they can maintain situational awareness around them.

Although in its early stages, the horizontal fusion project expects to provide improved situational awareness, more rapid integration of operational intelligence planning, capability for incorporating video information on-line, collaborative planning and modern mission rehearsal utilizing high-fidelity simulation, and improved data interoperability [OSD, 2003].

In Canada, a knowledge management portal called COP 21 [Gouin et al, 2003] has been developed and was exercized at the Joint Warrior Interoperability Demonstration (JWID) in 2004. COP 21 has a number of capabilities that contribute to improved situation awareness:

• single point of access to multiple information sources;

• multiple collated windows to view several documents together;

• filtering and categorizing information using portfolio views;

• provision of contextual search services;

• provision of search agents and notification services;

• interaction with information via Web-based applications running within the portal.

6.4.3. Knowledge representation enablers: ontologies, taxonomies, metadata and the semantic Web

Knowledge objects can be expressed by different means and represented in different ways. The following sections present a very generic view of some of the most important knowledge representation enablers: ontologies, taxonomies, metadata and the semantic Web.

6.4.3.1. Ontologies

Since [Gruber, 1993], it is usually admitted that “an ontology is a formal, explicit specification of a shared conceptualization. A conceptualization refers to an abstract model of phenomena in the world by having identified the relevant concepts of those phenomena. Explicit means that the type of concepts used and the constraints on their use are explicitly defined. Formal refers to the fact that the ontology should be machine readable. […] Shared reflects that ontology should capture consensual knowledge” accepted by the communities [Fensel, 2001]. Ontologies resemble faceted taxonomies but use richer semantic relationships among terms and attributes, as well as strict rules about how to specify terms and


relationships. Because ontologies do more than just control a vocabulary, they are thought of as knowledge representation. The following figure shows two samples of ontologies.

12 a)

12 b)

Figure 12 - Ontology Samples

Ontologies are a very active research topic in various communities such as ontological engineering [Gómez-Pérez et al., 2004; Staab & Studer, 2004], knowledge engineering [Gómez-Pérez et al., 2004], natural language processing [Bourigault, 2002], cooperative


information systems, intelligent information integration, information retrieval systems [Wu et al, 2003], knowledge management [Staab et al., 2002], decision support systems [Boury-Brisset, 2001], data fusion [Boury-Brisset, 2003], C2I2, C4ISR, etc. Using formal representation languages, ontologies provide a means that allow shared and common understanding of a domain that can be communicated between people and heterogeneous and widely spread application systems [Fensel 2001]. Ontologies provide a shared and common understanding of a domain among software agents by specifying concepts and their relationships, thus providing concept semantics. Nowadays, many softwares and systems for ontology engineering are freely available (e.g. KAON, Protégé, OILed, etc.)5

Figure 13: Example of Ontology Engineering Architecture [Kietz et al, 2000]

Similarly, the SACOT6 research project is a recent ontological engineering initiative from DRDC aimed at generating domain ontologies using electronic texts.

5 Readers will find two comprehensive reviews of ontology engineering tools in [Gómez-Pérez et al., 2004] and [OntoWeb Consortium, 2002]

6 SACOT: Semi-Automatic Construction of Ontologies from Texts. (DRDC Valcartier. PoC, Dr Alain Auger)


In the C4ISR context, knowledge processes aim to build and sustain some contextual “knowledge awareness”. [Staab et al, 2002] suggest a knowledge process divided into four major steps.

Figure 14: Knowledge Process [Staab et al, 2002]

According to the authors, once a KM system is fully implemented in an organization, knowledge processes essentially circle around the following steps.

• Knowledge creation and/or import, i.e., contents need to be created or converted such that they fit the conventions of the company, e.g., the knowledge management infrastructure of the organization.

• Then knowledge items have to be captured in order to elucidate importance or interlinkage, e.g., the linkage to the conventionalized vocabulary of the company.

• Retrieval of and access to knowledge satisfies the “simple” requests for knowledge by the knowledge worker.

• Typically, however, the knowledge worker will not only recall knowledge items, but will process them for further use in his/her context.

6.4.3.2. Taxonomies

Traditionally, taxonomy is the science of naming and classifying organisms. In a broader sense, we can say that it is the science of systematic classification based on similarities and differences between items or concepts.

Compared with ontologies, taxonomies provide a more limited yet extensive way to express concepts within a domain. In taxonomies, concepts are hierarchically organized in the form of a tree. The relationship between concepts that is supported and implemented in taxonomies is


the IS_A relationship. In taxonomies, concepts are classified using homology; that is, shared characteristics that have been inherited from a common ancestor. Figure 15 shows a taxonomy of computer flaws.

Figure 15 - Sample Computer Flaws Taxonomy [Landwehr, 1994]

The MindMap in Figure 11 is also a taxonomic representation of knowledge management and exploitation dimensions to be considered in decision support systems.

6.4.3.3. Metadata

Metadata describes the attributes of an information-bearing object (IBO) – document, data set, database, image, artifact, collection, etc.; metadata acts as a surrogate representation of the IBO. A metadata record can include representations of the content, context, structure, quality, provenance, condition, and other characteristics of an IBO for the purposes of representing the IBO to a potential user or system – for discovery, evaluation for fitness for use, access, transfer, and citation. Examples of metadata formats are the MARC format used by the library community, Content Standards for Digital Geospatial Metadata developed by the Federal Geographic Data Committee, Directory Interchange Format (DIF) used by NASA's Global Change Master Directory, Government Information Locator Service (GILS), and Dublin Core set of attributes for electronic resources developed with the lead of the Online Computer Library Center (OCLC). (See also 6.1.5.5.)

6.4.3.4. Semantic Web

With the recent advances of the Semantic Web technologies [Fensel et al., 2003], ontologies are used to enrich documents with semantic annotations. This allows structural and semantic


definitions of documents and provides new capabilities to traditional information systems such as:

• intelligent concept-based search instead of traditional keyword matching;

• intelligent automatic document classification and filtering;

• intelligent topic identification;

• inference and reasoning over information.

In the military context, [Chance and Hagenston, 2003] assessed the potential value of semantic Web technologies in support of military operations. the general conclusion is that semantic Web technologies are likely to “produce faster sensor-to-shooter times and assist in achieving the speed required to achieve victory on any battlefield”. [Bowman et al., 2001] developed an ontology to implement a course of action critiquing agent as part of the DARPA High Performance Knowledge Bases (HPKB) program. Ontologies can be used in a wide range of many military applications and requirements such as:

• military equipment description ontology and markup;

• thesaurus-assisted search query for equipment descriptions;

• military task list ontology;

• glossary ontology (extends thesauri ontology);

• lessons learned ;

• intelligent data fusion;

• systems interoperability (ontologies provide mapping capabilities between data models);

• operation planning process validation;

• course of action generation.

Semantic Web technologies rely on ontologies. Ontologies are enablers to several knowledge exploitation and decision support systems. They can be used as means for interoperability in software development [Hansi, 2003], for data fusion problem-solving [Elmore et al., 2003], for document classification and filtering [Wu et al., 2003], for geospatial data representation7 [Wiegand and Zhou, 2003], and for inference and reasoning of software agents.

7 A list of geospatial ontologies can be found at http://loki.cae.drexel.edu/~wbs/ontology/list.htm


6.4.4. Information handling tasks

Information is the very essence of C4ISR. Taken as an artifact, it is involved in several information handling tasks. Advanced knowledge management and exploitation systems will provide effective support for the user to be able to perform these tasks properly and in a timely fashion.

Adapting the taxonomy proposed by the US Federal Intelligent Document Understanding Laboratory (FIDUL), we can group the main information handling tasks under the following topics.

Task Description

Publishing Acquire, create, edit, modify, delete, convert, publish and share data/information/documents.

Summarizing Produce a summary of the document.

Extracting For documents of interest, capture specified key information. This activity might be involved in topic identification applications.

Triage For a set of data/information/documents determined to be of interest, rank by importance.

Detection Find data/information/documents of interest. This task is involved in most search and retrieve applications.

Classification Classify data/information/documents according to pre-defined categories.

Filtering Discard irrelevant data/information/documents.

Translating Translate data/information/documents from one language to another.

Table 2 - Common Text Handling Tasks

An important dimension to be taken into account in future knowledge exploitation systems is the diversity of media types. To be truly fieldable, the next generation of integrated knowledge exploitation systems will be required to support several types of media such as text files, voice files, image files and multimedia files in every possible information handling task. This implies, for instance, that systems will be able to provide automatic classification for any piece of information, whether it is text, voice, image, video or even audio information.


6.4.5. Lessons learned

Lessons learned can be defined as “knowledge generated by reflecting on experience that has the potential to improve future actions. A lesson learned summarizes knowledge at a point in time, while learning is an ongoing process”8. It is therefore an important asset in knowledge enrichment and continuous learning. In the future, knowledge exploitation systems will integrate support for lessons learned in order to meet the requirement of continuous learning.

In Canada, the Department of National Defence is hosting the Army Lessons Learned Centre (ALLC). The mission of ALLC is to collect and analyze Canadian and allied operational and training experiences for dissemination as lessons, with a view to improving the overall operational capability of the Canadian Army. DRDC Valcartier made a major contribution to the development and success of the system currently being used by ALLC [Boury-Brisset et al., 2002].

ActionsFollow-up

Impact Analysis

LessonsDetermination

KnowledgeAnalysis

KnowledgeGathering

Mission-Reporting

Requirements

Reporting

PerformingActions

Searching

LL CellUser

ActionsFollow-up

Impact Analysis


KnowledgeAnalysis

KnowledgeGathering

Mission-Reporting

Requirements

ActionsFollow-up

Impact Analysis


KnowledgeAnalysis

KnowledgeGathering

Mission-Reporting

Requirements

Reporting

PerformingActions

Searching

LL CellLL CellUserUser

Figure 16 - Canadian Forces Lessons Learned Process [Boury-Brisset et al., 2002]

6.4.6. Knowledge discovery technologies

6.4.6.1. Data mining

“The omnipresence of uncertainty requires us to be able to cope with it” [Hand et al., 2001]. In most of the definitions we can find, data mining is always about discovering new and unexpected relationships in data sets. For [Hand et al. 2001], “data mining is the analysis of (often large) observational data sets to find unsuspected relationships and to summarize the data in novel ways that are both understandable and useful to the data owner”.

Data mining techniques are used in search and optimization methods, in descriptive modelling, in predictive modelling and in finding patterns and rules. They are at the heart of

8 Source: http://www.ifad.org/evaluation/guide/annexa/a.htm#l


knowledge objects discovery techniques. In 1998, Elder Research conducted a comparative study of most popular data mining desktop applications [King et al, 1998]. The following figure shows a summary of their evaluations.

++ = Excellent; + = Good; 3 = Average; - = Needs Improvement; -- = Poor; None = Does not exist; NE = Not Evaluated. *Averages assume that the symbols represent an equal interval ordinal rating scale.

Figure 17: Performance of Data Mining Desktop Tools [King et al., 1998]

Twenty evaluation criteria and a standardized procedure for assessing tool qualities were developed and applied. The traits were collected in five categories: Capability, Learnability/Usability, Interoperability, Flexibility, and Accuracy. Performance in each of these categories was rated on a six-point ordinal scale, to summarize their relative strengths and weaknesses.

In order to support knowledge workers (such as intelligence analysts) when dealing with the task of knowledge discovery, knowledge management and exploitation systems will integrate sets of data mining tools implementing different data mining techniques (e.g., clustering, Bayesian networks, neural networks, decision trees, etc.). In particular, it has been established in the scientific community that Hyperbolic Self-Organization Maps (HSOM) algorithms are efficient at providing navigation support in the semantic space of large text collections [see Ontrup and Ritter, 2001]. HSOMs are very good at revealing semantic links between concepts in large electronic text collections.

6.4.6.2. Link analysis

Link analysis is a technique that reveals and visually represents complex patterns by linking together values from a data set. Associations between entities such as people, places, vehicles and organizations are mapped as a chart, providing the analyst with an understanding of the


hidden structure of investigated data and helping to quickly isolate patterns of interest for further investigation [Bouchard and Gouin, 2004]. Link analysis is of interest because of the increased terrorist threats that allied countries have experienced in the new century and the CF role in the surveillance of illegal activities such as migrant smuggling and drug trafficking.

With the types of activities, particularly terrorism, the battlespace is no longer circumscribed, threats are asymmetric, hard to discriminate and engage, and many of the tools formerly used to create the common operational picture are no longer appropriate. Fortunately, link analysis techniques have already proven their value in making sense of complex information.

Typical use of link analysis techniques to track terrorists or drug dealers involves nodes representing the organization members and links depicting formal and informal relationships between these people; these graphs are commonly called social networks. Although social network analysis might provide a good understanding of the structure of an organization, the visualization of many other nodes and links might be used to discover patterns, trends, associations, and hidden networks within complex structures. The integration of geospatial and temporal analysis with social network analysis provides the analyst with a more comprehensive and thorough network analysis.

6.5. Information visualization

Visualization has two main dimensions. The first is the cognitive ability of a human to perceive and form a mental representation of a situation or of information. The second is the supporting technology that allows the presentation of this situation or information.

From the latter perspective, military command and control systems use a wealth of visualization techniques that are applied to a variety of application domains, including command and control, intelligence, logistics and information operations. Recognizing this variety, the TTCP C3I Action Group on Information Visualization conducted a survey of visualization techniques and approaches currently used in allied command and control systems or being examined as applied R&D activities [Gouin et al., 2002]. A knowledge base of these techniques – C3I-Vis - has been developed. It contains in excess of 110 C3I visualization approaches and over 240 showcase examples (screen shots, video clips, etc), each characterized in terms of the domain contexts, the descriptive aspects and the visualization approaches. A majority of visualization techniques consist in map-based representations. Still, many differences exist in the implementation of map-based representations that result in various degrees of situation awareness and battlefield visualization:

• Use of 2D or 3D map representations depending on the task and possibility of transition from one mode to another.

• Information content and map scale that is tailored to the user role/task.

• Use of a meaningful symbology (shapes, colours). Improvements to the STANAG symbology (e.g., use of different colours to represent each coalition faction).


• Capability to dim the map background to highlight overlayed information.

• Display of temporal information using traces, playback, blobology.

In terms of non-map-based representations, there is widespread use of organization charts and Gantt charts, and increasing use of dashboards, particularly for logistics and planning applications. R&D activities are conducted on abstract representations, particularly for exploiting the human recognition of visual patterns; military users need to be exposed to these representations before they are adopted for command and control systems.

6.6. Human-computer interactions

In a C2 environment, the human interface defined by its sensory modalities (such as the visual and auditory sensors) is not sufficient to process all of the information required by the DM task. A technological interface must therefore be designed to help humans work around their limitations. Indeed, in many circumstances, most of the information required is made available to the user through such an interface, which becomes the main link between the human and their environment. The decision-maker’s SAW is thus closely related to the quality of this interface. In an ideal situation, the interface could be seen as an extension of the human visual, auditory and memory capabilities. By properly organizing the information according to human capabilities, an efficient interface may give the decision-maker the opportunity to process more of the critical information. Indeed, the ultimate goal of any display design is to positively impact the performance of the human-machine system of which it is a part. To enhance the SAW and DM processes, the critical information required for optimal DM must be presented through the interface in an appropriate, compatible format for human information processing. This information must also be presented at the proper time, as the situation unfolds.

Regarding these issues, [Roy et al., 2001] provides a description of CODSI (Command Decision Support Interface), an "operational-like" human-machine interface prototype that has been developed to study the enhancement of SAW quality in computer-based SA and DM support systems.

From the hardware perspective, a wide variety of display systems are coming forward to solve problems ranging from command and control at the strategic level down to enabling the dismounted warfighter to partake of the common tactical picture for better situational awareness [Gouin et al., 2002]. The future will see integrated command centres containing many types of displays, including knowledge walls and virtual reality displays. Large, frameless, immersive displays will be used for 3D situational awareness, while individual, tailored displays will be readily available to provide specialist information. Perceptual, multimodal interfaces will replace wands (3D joysticks). Integrated speech and gesture will be the primary interface, and we will have moved from speech recognition towards the requisite use of natural language recognition.


6.7. Decision support systems

Figure 18 and Figure 19 attempt to approximately locate decision-making and decision support on the "data-information-knowledge" spectrum and the "system" spectrum, respectively.

Physicalprocess

DATAMeasurements andobservations

INFORMATIONData placed in context,indexed and organized

KNOWLEDGEInformation understoodand explained

WISDOMKnowledgeeffectively applied

ObservationCollecting, tagging and dispatching

quantitative measurements

OrganizationAligning, transforming, filtering, sorting,

indexing and storing data elements

UnderstandingComprehend relationships

between sets of information

ApplicationEffectively

implement plan

Decision makingDecision aiding

InferenceReasoningUncertainty mgt

AlignmentCorrelationExtrapolation

CalibrationFiltering

SensingMsg parsingAcquisition

Figure 18 - Information hierarchy [Waltz, 1998]

Physical Level

Databases, Data Warehouses

Information Systems

Intelligent &Decision Support Systems

Figure 19 - Hierarchy of systems

6.7.1. Decision-making

Advisory capabilities can be provided for decision analysis to balance decisions and manage risk. For example, multiple-criteria decision support tools can be provided to help the decision-makers to compare courses of action (COAs) and rank them according the commander’s intent.

6.7.2. Response planning

A classic definition of planning is the generation of an action sequence or policy to transit from an initial state to a goal state. Planning activities are typically carried out in the context


of force employment [Cochran, 2002]. The operational planning process is a coordinated process to determine the best method of accomplishing assigned operational tasks or planning for future tasks.

The planning process is designed to optimize logical, analytical steps of decision-making in conditions of uncertainty and ambiguity. The output of the planning process is a contingency operations plan or operations order designed to produce a desired end-state and achieve an assigned mission. Elements of the planning process are:

• initiation/mission analysis/objective identification ; • orientation/definition of COAs; • COAs development; • COAs evaluation; • COAs selection; • plan development; • plan review; • scheduling/synchronization tasking.

Deliberate planning includes planning that is not subject to the immediate pressures of time or prevailing threats. Time-sensitive planning occurs when the degree of immediacy of a crisis demands an accelerated operations planning process. However, it should neither disrupt the logical flow of information nor divert staff from considering all planning principles. There are three distinct but related planning levels, which correspond to the three levels of command: strategic, operational, and tactical. Prior to or during an operation, there will be some degree of planning at all three levels. However, the level of command that conducts the planning will vary depending on the scope and complexity of the operation.

6.7.3. Response control and monitoring

Response control and monitoring capabilities can be provided, for example, for resource tracking. A status board could be an appropriate means of achieving such a capability.


7. Support System Development Process

To build the appropriate CBSS, a well-structured development process needs to be adopted and followed. Figure 20 illustrates such a development process. Many aspects of this process are discussed in [Breton et al., 2002]. An important challenge is to develop a CBSS that, on the one hand, takes advantage of all the technological opportunities while, on the other hand, is totally compatible with the way a human executes the tasks to be supported. The development of support systems thus includes the participation of experts from the application domain, i.e., the subject matter experts (SMEs) in Figure 20, system designers and human factor specialists to ensure the cognitive fit between the CBSS and the decision-makers, in order to maximize decision-making effectiveness.

The CBSS development process begins with the identification of SMEs (mostly decision-makers) from the operational community. Then it proceeds with the capture and understanding of the requirements of the particular application domain of interest. This is a fundamental step, as the application domain characteristics will define the fundamental skeleton of the CBSS and ultimately the form of the CBSS knowledge model communicated to the human practitioner controlling the domain. This step can be initiated through reading appropriate documentation of the domain, through an analysis of documented lessons learned, and through active participation in training courses and/or exercises/demonstrations with end users. However, a serious CBSS development process must include formal interviews of SMEs following cognitive engineering methods. This step includes the use of current cognitive theories and models to interpret and understand the impact of the results and findings from a human factor perspective.

Requirements

• User Needs• Problems• Deficiencies• Etc.

OperationalCommunity

SME

SME

SMESME

SME

DomainRequirements Capture• Documentation• Lessons Learned• Training Courses• Exercises/Demonstrations• Formal Methods• Etc.

DomainRqts. Understanding

• Knowledge Elicitation• Integrated C4I Model• Ontologies• Relevant Scenarios• Information Sources• C2 Structure• Roles/Responsibilities• Operational Procedures• Existing Systems/Capabilities• Etc.

SystemDevelopment

Activities

Experimentations/Demonstrations

FEEDBACK

INTERPRETATION

VALIDATION

Research &Technology Watch

Activities

Identification of Support

Capabilities

Figure 20 - CBSS development process


The analyses above lead to the identification of user needs, problems and deficiencies in the form of explicit system/software requirements. Then, technological solutions are identified to address the requirements, taking into account the findings of research and technology watch activities, leading to system development activities. A serious system development process, if the project timeframe and appropriate resources permit, should follow formal software engineering methodologies. Testing procedures and demonstrations/experimentations are required to validate the technological solutions from the human performance and operational perspectives. Transparency must be one characteristic of the development process. With testing/demonstration/experimentation results presented as a feedback, the SMEs can understand the link between their requirements and the solutions provided at the end of the development process to answer these requirements. Moreover, discussions around these results may lead to the identification of other problems experienced by the SMEs, or potential problems created by the new CBSS. On the one hand, being more involved into the development process through the feedback process allows the SMEs to develop a better understanding of how the CBSS is built, which can result in better acceptance and a higher level of confidence in the CBSS. On the other hand, having more contacts with the SMEs helps the team members to be more aware of the SME reality, which can lead to the development of a more appropriate CBSS.


8. Some Information Technologies (IT) Forecasts for DND/CF

Recognizing the value of network-enabled capabilities, the Assistant Deputy Minister Information Management (ADM (IM)) in 2004 launched a study conducted by Gartner to identify the requirements for a smart enterprise by examining the current state, future trends (five-plus years) and impacts of advancing IT on DND and CF. A smart enterprise is a flexible information-networking environment connecting people to information and people to people. A flexible information-networking environment enables the end user to maximize decisions or productivity by employing adaptive technologies through a secure open architecture. Here are some of the key findings of this [Smart Enterprise Study, 2004].

8.1. Smart Enterprise Study findings

A number of initiatives are underway in DND/CF to enable a more strategic capability of CF through the integration of networks, applications and data. The focus of these efforts is on joint force capabilities and convergence in order to bring information to the end user in a seamless and timely manner.

Key requirements for tactical and operational decision-making are the ability to access all information from anywhere at any time and to do this from an integrated environment. Self-synchronization and interoperability with other government departments, countries and partners, such as NATO and NORAD, are critical elements of this strategy, requiring DND/CF to integrate its personnel, equipment and logistics into joint task forces including members from many other countries around the world.

A major DND/CF issue identified during the interviews for the Smart Enterprise Study is the ability to get to meaningful information. Many acknowledge that the issue is not that the information is missing, but that access to the information and analysis tools are lacking. Data mining technologies can provide DND/CF with tools to meet two major needs:

• The ability to analyze and gain ad-hoc insights from information.

• The ability to build information models that can be used to predict future events, behaviours and outcomes.

According to the Smart Enterprise Study, DND/CF requirements and current technical infrastructure indicated that a number of the technologies will have a significant impact on the operational and administrative environment in enabling shared information, common situational awareness, collaboration and mission effectiveness. Figure 21 below shows some of the knowledge management technologies that can support these requirements, together with their respective levels of maturity.


Figure 21: Maturity Level of Some KM Technologies [Smart Enterprise Study, 2004]

Document management and e-learning technologies are considered mature, whereas the new generation of semantic-based information extraction technologies is slowly emerging.

Knowledge management and the ability to easily retrieve and analyze unstructured data for key decision-making activities will be important in the future due to the need to react and mobilize quickly to worldwide events, respond to access-to-information requests, and effectively manage DND/CF. This will be achieved through the development and implementation of and adherence to standards, as well as the integration of corporate administrative applications with tactical and operational systems in the field. The ability to exploit DND/CF’s network while adhering to defined security and privacy requirements will be key to the success of achieving this vision.


9. Conclusion The Revolution in Military Affairs (RMA) has moved to centre-stage the requirement for information dominance in the joint battlespace. It is predicted that the greatest change in the conduct of future military operations will be the result of the application of information technology to military command and control. Commanders and decision-makers at all levels need enough information to make decisions but need to be supported by technology so that they are not overwhelmed with information.

By leveraging advances in information technologies such as data and information fusion, knowledge management and exploitation, information visualization, human-computer interactions and decision support systems, future C4ISR systems will definitely allow the improvement of situation awareness and decision-making.

Future C4ISR systems will need to incorporate both the decision science principles and new tools into a science-based decision support framework sustained by information and knowledge exploitation technologies. By exploiting open standards and net-centric enterprise services, these systems will also provide increased interoperability and support modular software development.


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11. Distribution list

Internal

1 - Director General 3 - Document Library 1 - Head/Decision Support Systems Section 1 - Head/Information and Knowledge Management Section 1 - Head/System of Systems Section 2 - Dr Alain Auger (author) 1 - Mr Denis Gouin (author) 1 - Mr Jean Roy (author) 1 - Dr Michel Gagnon 1 - Mrs Régine Lecocq 1 - Mr Yaïves Ferland 1 - Mr François Létourneau 1 - Mr François Lemieux 1 - Mr Marc-André Morin 1 - Dr A. Guitouni 1 - LCdr E. Woodliffe 1 - LCol Benoît Carrier (CTG) 1 - Maj Michel Gareau 1 - Mrs Micheline Bélanger 1 - Dr Anne-Claire Boury-Brisset 1 - Mr Stéphane Paradis 1 - Dr Richard Breton 1 - Mr Michel Lizotte 1 - Mr Claude Roy (SDA)

External

1 - Director - R&D Knowledge and Information Management (PDF file) 1 - Dr Mark McIntyre, DRDC Halifax 1 - Thrust Leader "11h", DRDC Halifax Attn: Jim S. Kennedy 1 - Directorate Science and Technology (C4ISR) Attn: Dr Chris McMillan Attn: Mrs Donna Wood 1 - Directorate Science and Technology (Air) 1 - Directorate Science and Technology (Land) 1 - Directorate Science and Technology (Maritime)


1 - Directorate Science and Technology (Policy) 1 - Directorate Science and Technology (Human Performance) 1 - CBRN Research and Technology Initiative (CRTI) Attn: Dr Kam Boulet Attn: Mrs Susan McIntyre 1 - Mrs Barbara Waruszinsky, DRDC Ottawa 1 - Col Williams (Associate DG RDP) 1 - Mr Louis Bélanger, (Communications Security Establishment (CSE)) 1 - Mr Rodney Howes, (Communications Security Establishment (CSE)) 1 - Mr Kabeer Sayeed (ADM (IM)) 1 - Mr Robert McAulay (ADM (IM), D/PM JIIFC) 1 - Mr Colin Cantlie (ADM (IM)) 1 - LCol Thomas Sullivan (ADM (IM), PM JIIFC) 1 - LCol Terrence Procyshyn (DJFC) 1 - Maj P.C. Kvas (DIMSP 2-2, NDHQ) 1- Maj Claude Charland (Project Director AFIILE) 1 - Dr Brian Eatock, DRDC Ottawa 1 - Capt(N) Darren Knight (DJFC) 1 - Maj Rob Gundling (DJFC) 1 - Maj Anthony Whitaker (DJFC) 1 - LCdr Craig Dewar (DJFC, D/PD JIIFC) 5 - Cdr Tim Addison (DJFC, JIIFC) 1 - Col Christian Rousseau, CO NDCC 1 - LCdr Jim Day, (DMRS 2) 1 - LCol Jacques Hamel (DLCSPM 7 / PMO ISTAR) 1 - Maj Neal Knapp, (DAR 4) 1 - Maj David Perry (DISB) 1 - DRDKIM: Attn: Mr John Oakes Attn: Mr Bill Page 1 - CFEC: Attn: Capt(N) Kevin Laing Attn: LCol Tom Gibbons Attn: LCol J.D. Graham Attn: LCdr Rob Elford Attn: Dr Kendall Wheaton Attn: Dr Phil Farrell 1 - Mrs Cynthia Fowler, (J2 GICI) 1 - LCol John Girard, (DGSC/DKM) 1 - LCol B.J. Busseau, (CFJOG) 1 - LCol Voss, (ALLC) 1- Maj Boule (ALLC) 1 - LCol Ralph Giffin (DIMSP 2) 1 - Col Lindscott (DJFC 2) 1 - Col Joe Gendron (DLCI) 1 - LCol Jean-Louis Chevalier (DLCI 2) 1 - Maj Costello (DLCI 2 – 2) 1 - LCol Chris Blodgett (VCDS/DGSC)


1 - Mr Paul Morin (D INT IM) 1 - Mrs Sonja Heikkila (Public Security Technical Program (PSTP))


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3. TITLE (Its classification should be indicated by the appropriate abbreviation (S, C, R or U) Decision support and knowledge exploitation technologies for C4ISR

4. AUTHORS (Last name, first name, middle initial. If military, show rank, e.g. Doe, Maj. John E.) Auger, Alain; Gouin, Denis; Roy, Jean

5. DATE OF PUBLICATION (month and year) September 2006

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12. DOCUMENT ANNOUNCEMENT (any limitation to the bibliographic announcement of this document. This will normally correspond to the Document Availability (11). However, where further distribution (beyond the audience specified in 11) is possible, a wider announcement audience may be selected.)

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13. ABSTRACT (a brief and factual summary of the document. It may also appear elsewhere in the body of the document itself. It is highly desirable that the abstract of classified documents be unclassified. Each paragraph of the abstract shall begin with an indication of the security classification of the information in the paragraph (unless the document itself is unclassified) represented as (S), (C), (R), or (U). It is not necessary to include here abstracts in both official languages unless the text is bilingual).

(U) In military operations, commanders and decision-makers at all levels work in an information-saturated environment. Turning pieces of information into situation awareness requires the expertise and experience of many. Two main aspects will impact on next generation of C4ISR systems: Advances in command and control (C2) and information technologies, in particular in situation analysis, knowledge exploitation technologies and decision support systems. In order to facilitate interoperability, growth and maintainability, C4ISR systems must be developed by adhering to a number of open standards. Information technologies will be used to develop Net-Centric Enterprise Services (NCES) in order to provide modularity, sharing of decision-support tools and services and interoperability of C4ISR systems. Knowledge exploitation technologies shall provide new C4ISR systems with tools and processes to build actionable knowledge. Like situation awareness, knowledge management is about getting the right information to the right people at the right place and time. Therefore, in the military context, any knowledge management model and any decision-making model, including people, processes and technologies, must contribute directly to the achievement of this goal. Future C4ISR systems will also require the development and application of new decision science principles adapted to new and evolving decision-making contexts. They will need to incorporate both the decision science principles and new tools into a science-based decision support framework leveraging information and knowledge exploitation technologies. This document presents a generic, high-level view of current research activities in each of the areas mentioned previously.

14. KEYWORDS, DESCRIPTORS or IDENTIFIERS (technically meaningful terms or short phrases that characterize a document and could be helpful in cataloguing the document. They should be selected so that no security classification is required. Identifiers, such as equipment model designation, trade name, military project code name, geographic location may also be included. If possible keywords should be selected from a published thesaurus, e.g. Thesaurus of Engineering and Scientific Terms (TEST) and that thesaurus-identified. If it is not possible to select indexing terms which are Unclassified, the classification of each should be indicated as with the title.)

C4ISR, information technologies, environments, capability, knowledge management, knowledge exploitation, command and control, decision support systems, integration, fusion, ontology, semantics, interoperability

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