Transaction-based Definitions and Implementations of...

Presentation Title 2/4/09

Speaker Name 1

Transaction-based Definitions and Implementations of Community-of-Interest Languages

Dr. Andreas Tolk, Old Dominion University Mr. Saikou Diallo, VMASC

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Thanks for Sponsored Research

  US Joint Forces Command –  XC2I Interface –  X-BML –  JEDIS / JTDS / JRSG

  US Army Test and Evaluation Command – Data Management –  Architecture Studies in support of

Net-centric Testing   US Army PEO Soldier

– Model-based selection, composition, and orchestration

  NATO – MSG-027 Pathfinder – MSG-048 C-BML

  Industry Partners –  IBM – Raytheon –  Accenture –  TEI

  Academic Partners – MOVES/NPS –  ARL/UT

  and many more …


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Outline

  Concepts and Background – Community of Interest (COI) Languages – Model Based Data Engineering

  Composites and Transactionals – Data Model Theory – Composites and Transactionals

  Application Domains – Standardization – Migration and Implementation

  Example: C-BML and JC3IEDM –  Implementing BML as JC3IEDM Composites – BML Standard and Composites

Concepts and Background

COI Languages Model Based Data Engineering


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Community of Interest (COI)

  COI is defined as the collection of people that are concerned with the exchange of information in some subject area

Scott A. Renner: A Community of Interest Approach to Data Interoperability. Proceedings Federal Database Colloquium ’01

  The community is made up of the – users/operators that actually participate in the information exchange –  the system builders that develop computer systems for these users –  the functional proponents that define requirements and acquire

systems on behalf of the users   Renner stresses the importance of COI data panels and their task to

support Common Data Representations (CDR) to be used within the COI for data exchange

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Drives

Enables

Data Needed

Service Implementations

Enables

Community Information Exchange

Vocabulary

Capability Delivery

Drives

Info Sharing

Need

Drives

Service Needed

Net Enabled C2 Capability


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Result of the COI work

  Agreement on – Common information sharing need – Data needed for implementing services

  Common Data Representation – COI specific – Common Core

  Challenge – Unambiguously define the information (logically) – Unambiguously identify the representation in the system

(physically)

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Data Challenges for System to System Interoperability

  Describe data information exchange – Capture what systems can provide (information exchange capability) – Capture what systems can understand (information exchange need) – Capture what is necessary (information exchange requirement)

  Support the unambiguous definition of meaning of data – Syntax, semantics, and pragmatics – Gradually enhance and extend the common core

  Enable mediation based on these results – Configurable software layers – Minimize programmers interpretation – Maximize documentation for reuse


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Model-based Data Engineering

  Data Administration – Managing the information exchange needs incl. source, format, context

of validity, fidelity, and credibility   Data Management

– Planning, organizing and managing of data, define and standardize the meaning of data as of their relations

  Data Alignment – Ensuring that data to be exchanged exist in all participating systems

  Data Transformation – Technical process of mapping data elements

  Model-based Data Engineering –  Introducing a Common Reference Model for Data Management to

capture Standardized Data Elements and Relations

Composites and Transactionals Data Model Theory

Strong and Weak Composites Transactionals


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Data Model Theory

  Logical Data Model – Capture the business requirements based on conceptual

modeling   Physical Data Model Instance

– Generated from the Logical Model – Includes additional physical constraints (keys, etc…)

  Physical Data Model – The database

  Interoperation happens at the physical level, composition at the logical level.

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Composites and Transactionals

Logical Model

Physical Model

CRM Logical Model Sys A

Logical Model Sys A

Physical Model Sys A

Physical Model Sys A


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Composites and Transactionals

Logical Model

Physical Model

Composites

Transactionals Transactionals

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Composited and Transactionals

  Standardization happens on the logical level – CRM captured information to be shared between systems – Common language

  Understood by the systems   Spoken by the systems

  Implementation happens on the physical level – Transactionals capture the system constraints

  Accuracy (int16 versus int32 problems)   Mandatory and optional fields (incl. identifiers)   Business objects


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Application Domains

Definition Migration

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Definition

  Unambiguous definition of terms – Composite in the CRM – All properties that are needed to describe the concept

represented by the term – Only those properties needed to describe the concept

represented by the term   Key questions

– What is logically needed to unambiguously identify the type and the item of a represented term (such as a unit)

– What is logically sufficient to unambiguously identify the type and the item of a represented term


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Migration

  Migration means: “Make the system speak the COI language” (such as C-BML) – Logical mapping to the CRM – Identify “transactionals” implementing this mapping – Evaluate differences in scope, resolution, and structure

(logically) – Evaluate differences in accuracy and obtainability

(physically) Model-based Data Engineering was developed to support this application

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Special Case

  If we use an existing CRM – JC3IEDM – C2 Common Core / Universal Core this becomes our logical reference

  If we implement the infrastructure based on this CRM – JC3IEDM based web services – C2 Common Core SOA – GIG services using DISA Core Models we also have a physical reference

  Mapping still is needed on the logical level, the physical reference (transactionals) just serve as the mapping hub


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Example: C-BML and JC3IEDM Implementing BML as JC3IEDM Composites

BML Standard and Composites

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Overview

Slide courtesy of Kevin Gupton from ARL/UT


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WHO


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WHAT-WHEN



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WHERE


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Example: WHO

  Logical Composite – CL= {Object_Type, Organisation_Type,

Government_Organisation_Type, MilitaryOrganisationType, Unit_Type, Object_Item, Organisation, Unit, Object_Item_Status, Organisation_Status}

  Physical Composite – Cp = {Object Item, Organization, Unit}

  Reference to Existing Who – ID – Name + Index – Owner


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Where Example

  Where – Logical Composite – Location, Point, Absolute Point, Geographic Point – Specified in the logical schema – Other ways of representing location exist – All composites are explicit in the logical specification

  Physical Composite – Latitude, Longitude – Specified in the physical data model – The composite is embedded in the implementation

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Who is Where: Static Vs. Dynamic Information

  Logical Composite – Static Who Composite, Dynamic Where Composite – CL= {Object_Type, Organisation_Type,

Government_Organisation_Type, MilitaryOrganisationType, Unit_Type, Object_Item, Organisation, Unit, Object_Item_Status, Organisation_Status, Object_Item_Location, Location, Point, Absolute_Point, Geographic_Point }

  Solution – Reference Who + Initialize {Location, Point, Absolute_Point} +

update {Geographic_Point, Object_Item_Location} – Physical Composite {Id + (lat,lon) }


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References

  Andreas Tolk, Saikou Y. Diallo, Robert D. King, Charles D. Turnitsa: “A Layered Approach to Composition and Interoperation in Complex Systems,” in Tolk and Jain (Eds.): Complex Systems in Knowledge based Environments: Theory, Models and Applications, SCI 168, pp. 41-74, Springer, 2009

  Andreas Tolk, Saikou Y. Diallo: “Model-based Data Engineering for Web Services,” in Nayak et al. (Eds.): Evolution of the Web in Artificial Intelligence Environment, SCI 130, pp. 137–161, Springer, 2008

  Andreas Tolk, Robert D. Aaron: “Data Engineering for Data-Rich Integration Projects: Case Studies Addressing the Challenges of Knowledge Transfer,” Engineering Management Journal, in press, 2009

  Andreas Tolk, Saikou Y. Diallo, Charles D. Turnitsa, Leslie S. Winters: “Composable M&S Web Services for Net-centric Applications,” Journal for Defense Modeling & Simulation (JDMS), Volume 3 Number 1, pp. 27-44, January 2006

  Andreas Tolk, Saikou Diallo: “Model-Based Data Engineering for Web Services,” IEEE Internet Computing Volume 9 Number 4, pp. 65-70, July/August 2005

http://www.vmasc.odu.edu

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