Mark Gregory

PhD studentmarkrogergregory@hotmail.com

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A Personal Working Modelwww.markrogergregory.net

The principal themes of this presentation An introduction to my research into the personal work system and

personal working model of knowledge workers The research question: What is the contribution of personal

information management systems PIMS to the Working Model and personal work system PWS of knowledge workers?

The thinking and philosophy behind this research Justifying the need for PWS and PIMS: Ashby’s law of requisite

variety and the good regulator theorem of Conant and Ashby A new approach to modelling personal knowledge: concept-

process reciprocity modelling, Conceprocity The research design: objectives, motivation, planned

dissemination, methodology and techniques Research findings: identifying a personal working model and

personal information management system Existing and forthcoming research contributions, shortcomings,

future plan and papers

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The PhD for which I am registered Registration title:

Towards a Better Understanding of How Individuals and Small Groups useComputer-Based Information and Knowledge Representation Tools

Thesis title: What is the contribution of personal information

management systems PIMS to the Working Model and personal work system of knowledge workers?

Thesis compete August 2015

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What is my research demonstrating? In the paper: (Gregory and Macgilchrist, 2014)

We present a model of a Personal Working Model We show why such a Working Model must exist We discuss ways in which to model the Working

Model and its components As I complete my doctoral research, I am

modelling the working model and building a proof of concept personal information management system

All this has been exploratory research Subsequent to the PhD: more exploration and

the beginnings of explanatory research

An introduction to my research My research question: What is the contribution

of personal information management systems PIMS to the Working Model and personal work system of knowledge workers?

An introductory question: what do I mean by a Working Model?

This presentation concerns the motivation, justification and methodology for my research, including some contributions I am making as I answer my research question

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A Personal Working ModelThe modelling language used here, called Conceprocity, is itself a contribution of this research

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personal information management system

personal work system

working model

A Personal Working Model

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Shopping item

Supplier Quantity

bread hard discount

2 loaves

pasta hard discount

1 kg

basic veg hard discount

enough for 3 days

exotic veg supermarket enough for one meal

chicken farm shop 2.5 kg

Harry Potter DVD

online 2

Table structure

Rows

Columns: header gives

meaning

Personal data: a shopping list

A personal information management system is constituted when someone uses ICT – here a spreadsheet – to store data which subsequently informs decisions or action. The “systemic” element – the knowledge-wielding, learning element of the system – is the person who uses the information. The information is filtered data associated with meaning, here “simple” column headings. But in fact there is nothing simple about this process of attributing meaning. How “meaningful” would this data be if the content and headings were in a natural language you didn’t understand?

Is personal information management PIM important? In terms purely of academic research: there are perhaps

30 or 40 researchers in the world active in this area – slight significance They are largely drawn from cognitive science and

human computer interface backgrounds; almost no contribution from the Information Systems community

In terms of significance as a business and to businesses and to consumers: huge The business of Google, of Microsoft and of Apple are

all greatly dependent on the use made by consumers of devices and services by means of which they store, manipulate and share their personal data

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The phenomenon: people keep and use data as they get their work done The phenomenon I am investigating is the personal knowledge

management of individual knowledge workers as they carry out their work

This constitutes a personal work system (Alter 1999, 2010); (Baskerville 2011) in which the primary systemic element is the knowledge worker, who works – that is, she acts knowledgeably

Inter alia, she interacts with her personal data as it is stored on and made available by means of information and communications technology: cf. (Paul, 2010)’s definition of an information system as “IT in use”

(Baskerville 2011) calls the computer-oriented element of this an individual information system

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A distinctive approach Taking up the challenge made by (Baskerville 2011,

p.253): “Individual IS may well be an extremely large, undiscovered, arena for future IS research.”

We have established the need for an information systems perspective on personal information management - cf. (Gregory and Descubes, 2011b) and (Gregory, Kehal and Descubes, 2012)

This perspective is based critically on necessarily unusual lenses and research approaches because we are here exploring a new area of academic research: I am using individual IS to study individual IS

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Abduction, auto-ethnography, textual analysis and conceptual modelling An abductive leap: for me even to be able to complete a PhD in

personal information management systems it would be necessary to build a PIMS – a piece of design research – and possible to carry out auto-ethnographic research on that design process and associated learning Admissible in this initial exploratory research - cf. (Schultze, 2000) An instance of design science research (Hevner, March, Park and

Ram, 2004); (Gregor and Hevner, 2013); (Iivari, 2015); or of action design research (Sein et al., 2011); cf. (Baskerville and Wood-Harper, 1998)

In order to increase the reflexivity and objectivity of such auto-ethnography, I have also employed diarising, semi-formal research journal textual analysis and conceptual modelling of aspects of the developing exploration

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Philosophical thinking In principle, every piece of research needs to

demonstrate its epistemology: how we claim to know what we know

In this research, it has additionally been necessary to think about and develop (an) ontology: what we know Ontology: “That branch of philosophy which deals

with the order and structure of reality in the broadest sense possible” – quoted by (Wand, Storey and Weber, 1999, p.496)

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Ontologies in information science An ontology is a formal naming and

definition of the types, properties, and interrelationships of the entities that really or fundamentally exist for a particular domain of discourse

It is thus a practical application of philosophical ontology

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Ontologies, formal and personal A formal ontology (or upper-level

ontology) is defined by axioms in a formal language and aims to provide a domain- and application-independent view of reality, which can help the modeller of domain- or application-specific ontologies to avoid perhaps erroneous ontological assumptions

The notion of a personal ontology is not well-developed but we shall see that it is fundamental to more exact personal information management

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Philosophical background - 1 Abduction or retroduction; existential graphs;

semiotics as signs which lead to further signs; data as tables – Charles Sanders Peirce, e.g. (Peirce, 1902)

Scientific realism and modelling-as-theory – (Bunge, 1977, 1979) - (physics, chemistry, life sciences, social systems)

Conceptual modelling – (Wand, Storey and Weber , 1999), (Wand and Weber, 2002) Bunge’s realist ontology is the explicit basis for Wand

and Weber’s conceptual modelling– the so-called Bunge-Wand-Weber “BWW” approach

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Philosophical background - 2 The systems approach: systems of the real,

conceptual systems and conceptualising real systems (Mingers and Willcocks, 2014; Mingers, 2014)

I have adopted a critical realist stance – Roy Bhaskar (Bhaskar, 1978; Collier, 1994), Margaret Archer (Archer, 1995), Philip Dobson (Dobson, 2002); cf. Barry Smith (Smith and Ceusters, 2010; Smith, 2014) Philosophy as the “underlabourer and occasional

midwife” (Bhaskar) which helps us towards applied and applicable knowledge

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Critical Realism: significant tenets Distinguishes between the real, the actual and

the empirical (Bhaskar, 1978; Collier, 1994) Argues for ontological realism (cf. Smith, 2014) Accepts epistemological relativism:

the social world is transitive, can be explained but not predicted

Cf. "Critical attitude, self reflection, awareness of hidden presuppositions, and disclosure of assumptions of various perspectives" (Tsoukas, 1992) quoted by (Dobson, 2002)

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Margaret Archer, sociologist (Archer, 1995)Emphases as noted by (Dobson, 2002): Contra Anthony Giddens (Giddens, 1986), Archer

argues, from a critical realist perspective, that we must not conflate structure and agency

Structures are real entities with their own powers, tendencies and potentials

Social systems depend on relationships and have causal and emergent properties

Human agents reproduce structures by means of morphostasis and transform them by morphogenesis as structure and agency interact over time

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Critical Realism: implications Ontological realism

Holds that universals or types exist in reality Demands that we seek always to represent the

real and the actual in our empirical ontology Technology has a real existence and impacts

on both the agent and the structures within which she functions

Morphogenesis is significant as a mechanism for emergence over time

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How my research thinking has developed - 0 – An emphasis on tools Initially, my interest was in PIM tools and in their

support for conceptual data structures Personal cloud-based relational database, functional

spreadsheets and the like I chose specific tools, notably InfoQube and Zotero I built situational applications

But this was always unlikely to be an adequate approach in isolation – it is wrong to adopt “solutions” to problems which have not been properly analysed

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How my research thinking has developed - 1 – From tools to systems thinking & philosophy Building out from my initial interest in PIM tools Gradually I realised that what was important was the

notion of a cybernetic PIM system in which the emergent behaviour is primarily derived from the user herself

This led to questions about the nature of a system: compare the scientific realism of (Bunge 1979) and the phenomenology of (Checkland 2000); by means of: Ontology – what we know and Epistemology – how we know what we know

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How my research thinking has developed – 2 - From data to knowledge and back again The initial research object: me as an information worker and my use

of computer-based tools to manage – what? personal knowledge… Q: But how can such knowledge be represented as computer-

manipulable data? A: « semantic web » technologies for data structures and

specifically-written computer programs – But these are not accessible by « end users » Q: How can you possibly manage knowledge on a computer? A: You can't. But you can store the data and the conceptual data

structures that surround that data Data, information, knowledge: revisited; see (Gregory and

Descubes, 2011b) Sense must be made of the data; this can inform action

(abbreviation: inform-ation)

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How my research thinking has developed – 3 - Conceptual modelling Identification of concepts by means of textual

analysis - Leximancer Model-based reasoning and analysis (Nersessian,

1999) Conceprocity: concept-process reciprocity – a

visual knowledge modelling language Q: The ontological basis for conceptual modelling?

A1: Scientific realism: Bunge-Wand-Weber (Wand and Weber, 1990; Rosemann and Green, 2002)

A2: Critical realism: Bunge-Searle (March and Allen, 2014)

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How my research thinking has developed – 4 - Getting real about philosophy Inspired by Learning for a User by a Methodology-

informed Approach to a problem Situation LUMAS: the product of the phenomenology of Peter Checkland (Checkland, 2000)

Phenomenology has been presented as the basis of the systems approach (Georgiou, 2007 )

I have however reacted against phenomenology per se in favour of critical realism With great respect to Checkland: systems can be

real and should normally be treated as actual

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How my research thinking has developed – 5 – Individual learning and action as morphogenesis Macgilchrist presents learning and the creation of knowledge

as semantic morphogenesis (Macgilchrist and Gregory, 2015 - forthcoming)

I have observed stages of learning and individual transformation in my own doctoral research which do indeed suggest morphogenesis at the level of the individual agent

This developing knowledge is enacted in research speech acts (Searle, 2006 after Habermas)

My speech acts include: The elaboration of my PIMS: design research and adaptation Conference papers and forthcoming journal articles The writing of a reflective and, in significant part, conceptual and

philosophically-informed thesis

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How my research thinking has developed – 6 – Action Design Research Set within the broad spectrum of action research approaches

identified by (Baskerville and Wood-Harper, 1998) My work and developing understanding is situated at the

intersection of action science and action learning A major element of my work can be positioned as design

science research (Hevner, March, Park and Ram, 2004); (Gregor and Hevner, 2013); (Iivari, 2015)

We can view my auto ethnographic approach, coupled with my construction and use of a proof of concept personal information management system, as an application of Action Design Research (Sein et al., 2011)

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How my research thinking has developed – 7 –boundary considerations and systems principles I have concerned myself with at least two interdependent

but distinct systems One is the (soft) work system or human activity system

which I constitute as I work (alone and in collaboration with others)

The other is the (hard) information system that supports and serves that work system

Emerging from working with both are certain principles which I suggest may have wider application than my own personal accounts – sharing my action learning

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An example principle: problem setting before problem solution (Schön, 1983, p.40): “Professionals… are coming to

recognise that although problem setting is a necessary condition for technical problem solving, it is not itself a technical problem. When we set the problem, we select what we will treat as the “things” of the problem, we set the boundaries of our attention to it, and we impose upon it a coherence which allows us to say what is wrong and in what directions the situation needs to be changed.

“Problem setting is a process in which, interactively, we name the things to which we will attend

and frame the context in which we will attend to them.”

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Conceprocity dictionary in InfoQube

Conceprocity map

(Checkland, 2012): four conditions for serious systems thinking and actionConditions 1 and 2:

1. Any entity called a system may also contain within itself functional subsystems and may itself as a whole be a functional part of a wider system. So a system will in principle be part of a layered structure making a hierarchy of systems.

2. To achieve adaptation to change, there will have to be processes of communication. These will have to involve both the system and its environment. These processes will enable performance to be monitored so that a decision to adapt or not can be taken, whether by automatic processes or by human beings.

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(Checkland, 2012): four conditions for serious systems thinking and actionConditions 3 & 4:

3. If action to adapt is to be taken, the system will have to have available to it a number of possible control processes (responses to the shocks from the environment and to internal failure), which can be appropriately activated to bring about [adaptive] change.

4. There will be definable emergent properties that characterise the particular system or systems of interest, this being the pre-eminent systems idea.

Principle: It is essential to recognise and make explicit the emergent properties of any system that adapts and learns.

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The law of requisite variety put forward by Ross Ashby (Ashby 1956) can be stated thus:

“Variety absorbs variety, defines the minimum number of states necessary for a controller to control a system of a given number of states”

A good PIMS amplifies good variety while attenuating bad variety

The principal adaptive element in a PIMS is the individual knowledge worker herself

She adopts and adapts PIM tools over time Their use contributes to improved variety management

The Law of Requisite Variety and PIMS

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(Conant & Ashby 1970), Good Regulator theorem: “Every good regulator of a system must be a model of that system...

“The design of a complex regulator includes the making or maintenance of a model of the system to be regulated.

“The theorem shows that any regulator that is maximally both successful and simple must be isomorphic with the system being regulated.”

The Good Regulator theorem

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Good Regulator Theory: Significance Recap: The regulator or control system must be

capable of creating requisite variety; it must also be a model of the system it is to control Conant and Ashby claimed great generality for their theory,

initially applied to stochastic phenomena See (Scholten, 2010a), (Scholten, 2010b) for a primer and an

exegesis: “Every Good Key Must Be A Model Of The Lock It Opens”

Q: Why is this significant for personal work management?

A: The need for self organisation and control mandate systematic and adaptive personal information management

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Fundamental questions and putative answers Q: What is the system under investigation? A: It is the work system constituted by the

knowledge worker as she gets things done, as she informs her work, and as she reflects and learns

Q: What is the form and function of the model which regulates that system?

A: A « Working Model » which is a dynamic representation of the life she seeks to live The true isomorphic model is likely to be difficult to

perceive, changeable, very individual and fragmented But the effort has to be made to discern it at least

homomorphically and to make it more concrete

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Work systems and information systems - 1 (Alter, 1999, p.8): a work system is ‘a system in which

human participants and/or machines perform a business process using information, technology, and other resources to produce products and/or services for internal or external customers. Organizations typically contain multiple work systems and operate through them.’ Example work systems: building an aircraft; co-authoring a textbook.

(Alter, 2008, p.451) defines an information system IS as a type of ‘work system’, ‘in which human participants and/or machines perform work (processes and activities) using information, technology, and other resources to produce informational products and/or services for internal or external customers’ Example information systems: enterprise resource planning system;

accounting information system.

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Work systems and information systems - 2 (Alter, 2008) summarises and discusses 20 overlapping

but distinct definitions of the phrase ‘information system’ Amongst which, (Checkland and Holwell, 1998) posit:

‘'Any and every information system can always be thought of as entailing a pair of systems, one a system which is served (the people taking the action), the other a system that does the serving [i.e., the processing of selected data (capta) relevant to people undertaking purposeful action].'’ Elsewhere, Checkland calls these a human activity

system and an information system We prefer the language of Steven Alter: work system

and information system

Work Systems and Information Systems

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Information system is a small, dedicated component of a single work system

Information system is roughly equivalent to work system

Information system designed to support one work system is also used in another work system

Large information system supports a number of different work systems

Information system

Work system

Source: (Alter, 2002)

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Personal work systems and personal information management systems (Baskerville, 2011) suggests that his

individual information system – we call it a personal information management system PIMS – has an interface with both the personal work system of an individual and one or more work systems corresponding to her employer – this is identified on the next slide

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(Baskerville, 2011): individual information system architecture

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(Baskerville, 2011): individual information system interfaces

Regulation: an « age of steam » analogy

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Watt’s steam engine governor

Feedback control theory Single-loop feedback

system: source - (Doyle, Francis and Tannenbaum, 1992, p.8)

The system under consideration isshown in their Figure 1.3, where P and C are the plant and controller transfer functions

The signals are as follows:r reference or command input

e tracking error

u control signal, controller output

d plant disturbance

y plant output

n sensor noise

Not a theory which is directly applicable to PIMS

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Comparator Effectuator

A general control system

Source - (Doyle, Francis and Tannenbaum, 1992, p.6)

The "plant" (factory) is the set of production facilities, actuators that generate inputs, signal sensors, etc.

Controller has to be designed so that the plant creates the desired outputs z from the input w

This simplified control system is a better analogy for the way in which an individual controls her work

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A posited model of how a knowledge worker uses information to regulate her work

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3

5

6

2

1

4

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Principal research question and design What is the contribution of personal information

management systems PIMS to the Working Model and personal work system of knowledge workers?

Necessary precursor: appropriate modelling (analysis) and design (synthesis) approaches Initial exploration (1): homomorphic conceptual models –

whence Conceprocity Going on to “design” and “test” a regulator which is nearer

to an isomorphic model of the system under control – the working life of the individual Initial exploration (2): A proof-of-concept PIMS Which includes a personal taxonomy and a tagged

classification scheme

Conjectured Learning Informed Action For each knowledge worker (Drucker 1999): We posit the existence of (i) a Personal Work System

PWS This PWS is individual to each person’s (ii) Working Model That PWS is supported by (iii) a Personal Information

Management System PIMS: (Gregory & Descubes 2011a, b) Broadly the same as Individual Information Systems

IIS supporting personal and work-related Work Systems: (Baskerville 2011) following (Alter 1999, 2010)

Together permit Learning Informed Action

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Knowledge representation: KR We need to model the model…

Existing KR techniques vary in their: Expressiveness Precision Ease of comprehension

The more abstract, the more precise we can be in expression and manipulation (potentially even by machine); but less generally applicable, and more difficult to learn

Knowledge workers cannot really survive only with one KR approach Especially if that is « just » natural language

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Conceprocity: Concept Process Reciprocity (2013) I initially chose G-MOT as originated by LICEF

UQAM - (Paquette, 2010), but evolved this as I created my own KR approach:

Conceprocity – concept ↔ process reciprocity CPR – is a visual and textual language and toolset intended for capturing, expressing, communicating and co-creating models of topic areas of domain knowledge by domain experts or learners

Semi-formal semantics – human emphasis, used when investigating problem situations; but grammar rules exist and are (currently partially) enforced

A potentially important contribution of my PhD

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Conceprocity design influences - 1 Existential graph meta-model (and pragmatic

construction) - (Peirce, 1933); (Atkin, 2013) Immediate parent: G-MOT (Paquette, 2010)

=> typed concept mapping IS traditional Requirements Analysis: dataflow diagrams,

entity / relationship models, supplemented by rich pictures and concept maps

Particularly influenced by event process chains (Scheer, Thomas and Adam, 2005)

We position Conceprocity as a knowledge organisation system - (Friedman and Thellefsen, 2011), (Friedman and Smiraglia, 2013)

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Conceprocity design influences - 2 We have sought to make the modelling language even

more theory-based than its immediate predecessor G-MOT(whose roots lie in cognitive psychology)

In particular, we respect realist ontologically-based “BWW” conceptual modelling: (Wand, Storey and Weber, 1999), (Wand and Weber, 2002) But whereas their primary focus is on information

systems requirements analysis Ours is additionally on identifying the (conceptual)

work system which any personal information management system must support

Consequently our ontology is broader, benefitting from critical realist insights

Modelling nuggets in the Conceprocity approachA Conceprocity model of a "nugget" (a piece of knowledge, often actionable) consists of: A set of Conceprocity maps – these are visual

representations of aspects of the model A Conceprocity dictionary – this helps to clarify

the semantics of the model by naming properties A set of supporting “resources” , that is, files

which, together with the maps and the dictionary, constitute this nugget For example, for a taught class, these might include a

PowerPoint presentation and supporting articles

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Conceprocity semiotic notions: main symbol types

More semiotics: representing relationshipsDifferent kinds of arrow are used:Symbol Meaning

Association. This needs a text label, such as is-a, is-composed-of, etc.

Flow of control or of data; precedence and consequence

Is instantiated as

Influences. An actor or principle regulates, controls or governs a concept or procedure

Commentary concerning notions

Composition, Aggregation, Generalisation

Influences: (Paquette, 2010); (Booch, Rumbaugh and Jacobson, 2005); (Wand, Storey and Weber, 1999)

More semiotics: example logical connectors

Example KR: a Conceprocity map of the nugget “Planning and doing the shopping”

Dictionary for “Do the shopping”

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No one model is in and of itself sufficient Tables are also models

How philosophy is making a difference The application to conceptual modelling of the

philosopher John Searle’s social ontology, as suggested by (March and Allen, 2014), builds a complete new layer of institutional facts above what (March and Allen, 2014) term the “brute facts” in Mario Bunge’s ontology

Bunge might counter on the grounds that his philosophy is one of scientific realism and he specifically excludes concepts as facts

By contrast, Conceprocity accepts the reality or validity of concepts on the basis of critical (rather than scientific) realism

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Conceprocity changes made as a result of insights from critical realism - 2015We incorporate from (Searle, 2006) via (March and Allen, 2014): collective intentionality as a subtype of

principle institution as a subtype of actor constitutive rule as a subtype of principle deontic power as a subtype of principle action as sometimes a subtype and sometimes

an instance of process

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Conceprocity recent developments - 2015Conceprocity is enhanced in the following areas: Clear separation of attributes and properties

Attributes characterise conceptual objects, properties the corresponding instances

Either can be represented as a table on a diagram Will more normally be represented in separate tables

Sub-typing of major notions This permits a distinction between, for example, concrete (Bunge)

and social (Searle) notions Representation of nugget, system and subsystem

boundaries by means of swimlanes or nested diagrams Rationalisation of logical connectors and relationship types

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Evaluating Conceprocity philosophically Cf. (Wand and Weber, 2002) who insist on:

Grammar – constructs and rules Method – ways of using the grammar Script – models produced Context – modelling setting

The Conceprocity language, dictionary and documentation address all of these

Conceprocity is ontologically informed (but neutral on scientific versus social ontology)

Inevitably epistemologically; can also be: ontologically: relativist You could use Conceprocity to model Tolkien’s Middle Earth!

A fuller evaluation – and exploitation - is a required post-PhD development

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Recap: problem context and statement An abductive insight following Peirce:

It is a surprising fact that people get things done despite not having an explicit regulatory model nor an obvious personal information management system

Possible abductive explanation: people must and do have implicit regulators, perhaps in the form of so-called mental models which are homomorphic (somewhat isomorphic) with the reality

Prediction: people possess model-informed & regulated actions and processes

So what are the models and what PWS / PIMS have they de facto constructed? And how can they be “surfaced” (made explicit) and improved?

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A plausible conjectured meta-model

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Heuristics: by means of which the individual manages tasks and

projects within small-group and larger (departmental, corporate…) contexts as she stores data and

obtains information

Formal education and lifelong learning

Life and work of individual: task focus

Corporate and “office” information systems based on bespoke and procured “systems” and ad-hoc

assemblies of useful tools / apps

Evolving individual working model

The work system and the

information system used

by the individual.

The Personal Working Model: a conceptual model

that a person maintains. Initially

no more than a mental model.

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A plausible conjectured Personal Working Model - recap

Research objectives Objective 1 - To uncover and design my own PWS

and PIMS Objective 2 - To discover by mixed research

methods: How each individual’s Personal (Baskerville 2011)

Work System (Alter 1999, 2010) PWS can better be supported by her Personal Information Management System PIMS

How to help people to improve their PIMS and PWS via explicit modelling and implicit learning (by both research volunteer and researcher mentor)

Specifically, to understand how to “surface” the Working Model that underlies the PIMS and PWS

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Research motivation Desire to be engaged in relevant and passionate

research and related teaching or consultancy Desire to influence teaching and practice How?

Forums E-publication Academic journal articles Educating the educators: working with teacher -

researchers Executive education

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The research epistemology Exploratory research Essentially multi-method

Auto-ethnography, action design research, content analysis by means of textual analysis, model-based reasoning

Framework: (Psillos, 2009) following C.S. Peirce Abduction Induction Deduction? First we explore, then we zero-in on

more precise questions – hypothetico-deductive. Post-PhD.

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Methodology and techniques - 1 Action design research in the direct form of auto-

ethnography (structured self observation (Rodriguez and Ryave, 2002)): telling my own action-story as I seek to understand and to prototype better techniques

Means: PhD journal – cf. (Schultze, 2000) Outcome: textual analysis of PhD journal (2011 to

2015; 300000 words) Outcome: proof of concept PIMS

Based in part on serendipitous bricolage (Ciborra and Jelassi, 1994)

Outcome: Conceprocity sketches

Methodology and techniques - 2(Gregory, Kehal and Descubes, 2012) Currently: Working with some research participants

leading to co-designed Conceprocity maps and targeted PIMS improvement Outcome: a small number of cases, illustrated by narrative

and conceptual models

Post-PhD: fuller mentored action research – in particular, educating the educators

Findings: A Model of a Personal Working Model

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The Personal Work System PWS of a knowledge worker

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Some details concerning my personal work system PWS

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Procedures: use cases / processes1. Day-to-day time management2. Identification & planning of projects (e.g. PhD)3. Managing programmes4. Delivering teaching modules5. Managing research6. Career management7. Household management and family matters8. Involvement in voluntary organisations General form: nuggets of actionable knowledge, each

represented by a CPR model and by other resources such as a dictionary and a hierarchical outline

Components of a personal information management system PIMS

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Components of my proof-of-concept personal information management system PIMS - 1

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Zotero: reference management Whence the References at the end of this presentation

ABBYY PDF Transformer+: PDF; OCR InfoQube: data in grids (tables; Gantt view, etc.) - Used

very extensively in the PhD research, e.g. for Lists of nuggets and resources Classification (Jacob, 2004) Categorisation (tagging) Day-to-day and PhD planning

Basis for choice of InfoQube: outlining with columns (fields) and the possibility of incorporating own-code (VBScript)

A nugget: part of the plan stored in InfoQube

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Item % Complete Days left to do

Notes

Complete PhD thesis 0 136This is six months work at 23 days per month, which takes me to the end of August. I believe that I have built sufficient optimism bias into the timescales, but I certainly have my work cut out for me.

Obtain a new desktop computer, in order to have better system performance particularly for voice recognition. This is essential to complete the PhD thesis quickly. This is the computer called Fujitsu.

100 1Done, 03 to 07/10/2014. This new computer is referred to as Fujitsu. However, for now, there are no data files on the Fujitsu computer. See below.

Install Dragon NaturallySpeaking service pack 1 to take it to version 12.5 on Acer and to version 13 on Fujitsu.

100   

Restore Leximancer and Conceprocity access. Move Leximancer to Fujitsu computer.

100   

Install Camtasia Studio on Fujitsu. 95 1Maybe just a little more familiarisation required here.

Flesh out my personal working model with a real description of how I get things done and how I keep found things found. This should be in the form of a website-accessible nugget as should nearly all �subsequent work.

15 4Conceprocity TROPICPEA. Based on an analysis of my PhD journal.

Designing and building a nugget

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Frame the topic question and its parameters: what do we need to learn as we act?

Identify the vocabulary surrounding the nugget Assemble sources – using tagged classification and original

information searching Create putative model: dictionary, outline, map and tables Identify and carry out original research or initial problem-

solving Analyse data and refine model Present findings Applicable both to research and, in modified form, to teaching

and to other practice

Components of my proof-of-concept personal information management system PIMS - 2

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Zotero: reference management ABBYY PDF Transformer+: PDF; OCR InfoQube: data in grids (tables; Gantt view, etc.) Acquis: a Microsoft Access implementation of an

academic quality information system – an example situational application

Cloud-based apps: Lucidchart for Conceprocity (etc.) Website: www.MarkRogerGregory.net Textual analysis and concept identification: Leximancer

(Smith and Humphreys, 2006)

My use of Leximancer1. An overall analysis of the entire PhD journal

and of the papers that I have written during the PhD

Purpose: to discover the vocabulary that I have used and how that has evolved over time

2. An overall analysis of a large part of the PIM literature corpus – for comparison, showing how small is the overlap with my work

3. A focussed analysis of my work at a much finer level of granularity, individual journal entries

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A Leximancer analysis of my PhD journal

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My use of InfoQube Grids:

Nuggets and resources: tagged as nuggets Projects and tasks: tag planning InfoQube dictionary: tags IQDict, IQstd Conceprocity dictionary: tag Conceprocity Diary: tag diary

Aspects of personal ontology: Classification by Kind Categorisation by Tag Tagged classification

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Significance of Conceprocity to this PhD Making sense of complex scientific papers Analysing requirements and synthesising

design approaches Modelling working models, PWS and PIMS

both as-is and as-ought

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Existing and developing contributions from my Ph.D. research to date Initial diffusion

Twelve conference papers Website: www.markrogergregory.net, designed to

draw in volunteers Conceprocity’s principal dialects

CIAOPEA: for students Empirical investigation in S1 2013/4 as M2 students had to

model the concepts and relationships present in an academic paper concerning e-commerce – loose guidance

S2: tighter guidance to M1 students TROPICPEA: for and with practitioners; empirical

work with research volunteers as I and they model their personal work systems

Conceprocity dialects

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Usage Profile Acronym

Simple concept process mapping

CIAOPEA: Concepts Images Associations Operations Procedures Events Actors

Knowledge modelling

TROPICPEA: Typed-Relationships Operators Principles Images Concepts Procedures Events Actors

IS Usage modelling

Form Relationships Actors Procedures FRAP

IS Event Process modelling

Events Procedure-as-process Actors-as-swimlanes-or-org-units Views Operators EPAVO

IS Data modelling

eNtity Relationship Attribute View NRAV

Contributions from my Ph.D. A language and method for explicating and modelling personal

knowledge in a visual form: Conceprocity A thorough literature review, indicating the existing absence and

current need for a philosophically-informed systems perspective on personal information management PIM

A justification for an insistence on modelling – not an optional extra…

Modelling must be based on an identified personal ontological stance

Conceptualisation and illustration of the individual working models of certain individuals, starting with me: structured self observation

Analysis of unschooled and schooled Conceprocity mapping by students: how useful? action learning

Use of an evolving PIMS: design science (Hevner and Chatterjee, 2010)

Evidence for semantic morphogenesis in at least one individual case - mine - emergence

Future developments from my Ph.D. Practically relevant teaching, learning, mentoring and

self-evaluation approach Recognise shortcomings in this research and set out a

Programme for Later Research, following two lines of enquiry: That was the abduction; now what about other logics of

enquiry into PIMS? For example, how many people are dependent to what extent on PIMS?

Ongoing Mentored Action Research, enabled by an active web forum

A synthesised Statement of Requirements for effective PIM tools and systems - based on action learning outcomes

So what, and what next? The beginnings of an understanding of personal

information management systems Bootstrapped by the use and investigation of my own personal

information management system Under-researched by academia Massively significant to the ICT and consumer electronics industries

Visual modelling (“knowledge mapping”) with a strong ontological and epistemological basis Valuable in teaching, research and practice

The next steps Mentored action research based on a forum whose content

combines academic and experience-based learning together with tools for model building which enable model-based reasoning

Educating the educators? Working with teacher / researchers

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Papers I hope to publish

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Title Current co-authorsMentored action learning applied to personal knowledge management Gregory, Mark

Descubes, IrenaA Personal Working Model Gregory, Mark

Macgilchrist, RenaudDescubes, Irena

Structured reflection in Information Systems teaching and research Gregory, MarkDescubes, Irena

Knowledge Organisation by Concept Process Mapping Gregory, MarkConjectures on the morphogenesis of meaning and its part in learning Macgilchrist, Renaud

Gregory, MarkA complex adaptive systems perspective on personal information management systems

Gregory, MarkMacgilchrist, Renaud

An evolutionary model-driven approach to information systems construction and procurement

Gregory, Mark

End user oriented requirements specification and analysis by means of Concept Process Reciprocity modelling

Gregory, Mark

Model-based reasoning in the service of conceptualisation: a concept <-> process reciprocity approach

Gregory, Mark

Personal Information Management Systems Gregory, MarkDescubes, Irena

Titles in italics have yet to be written; others have either been presented as conference papers and / or are ready for submission to a journal.

Some take-home messages - 1 Philosophy (sometimes) matters

Especially if trying to get articles published in top IS journals! Only by taking a systems perspective can we recognise

the existence of personal work and information systems, their overlap and their distinctions

Even then, we need to take care to align the content and structure of our PIMS to the world that we recognise

Thus personal ontological categories can be of the real, purely conceptual or indeed fictional

A suitably-ambiguous example: storing details about a household – the people who live at an address

Similarly, models – which are always conceptual abstractions – can be of the real, conceptual or fictional

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Some take-home messages - 2 Models are necessary; the IS community with which I

identify has a duty to help people understand that Models take different forms but must be “surfaced”; we

must help to make them more explicit and perhaps to improve them Conceptual modelling, for example Conceprocity,

can greatly help here Control – management – needs and should mandate

good modelling aiding requisite variety We should endeavour to build good regulators – a

good Working Model – and to help others to do so

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In Summary:

Learning Informed Action

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