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Knowledge organisation by means of concept-process mapping

Knowledge organisation by means of concept process mapping

Knowledge organisation by means of concept process mapping

Knowledge organisation by means of concept-process mapping


ESC Rennes School of Business

Preface to this working paper

Conceprocity concept process reciprocity 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. This working paper introduces, positions, compares and justifies Conceprocity. The paper positions Conceprocity within existing spectra of approaches to data and knowledge organisation. It also introduces some of the more immediate use cases for which it has been created. Specifically it discusses how Conceprocity is to be used in my PhD research and teaching.

Readers of this document might like also to make reference to the online presentations of Conceprocity which can be found on the website In addition to a narrated audio presentation, these presentations include video demonstrating the actual construction of a Conceprocity model using Lucidchart. The presentations are of varying lengths, with the longest being intended only for people who intend actually to learn how to use Conceprocity in anger.

Readers should please understand that this is very much a working paper, not particularly well structured and in places still somewhat tentative. Nevertheless the author would very much appreciate your comments.

Table of Contents

0Preface to this working paper1

1An introduction to Conceprocity6

1.1Why model personal knowledge conceptually?6

1.2Why Conceprocity is important and indeed essential to my work7

1.3Designing your working life: learning how to get things done better7

1.4Simple Conceprocity model7

1.5Positioning Conceprocity as a Knowledge Organisation Representation8

2Conceprocity described9

2.1An example Conceprocity model and how it has been created9

2.2Conceprocity as a modelling language10

2.3Conceprocity: Notions11

2.4Representing Conceprocity relationships12

2.5Why Conceprocity distinguishes concepts, procedures and principles13

2.6Conceprocity relationships14

2.7Events and Logical Connectors18

2.8A summary of Conceprocity grammar rules21

2.9Structuring Conceprocity maps22

2.10Conceprocity Usage Profiles23

2.11Learning to use Conceprocity: moving on from the beginners profile23

2.12Conceprocity for the Right Brain24

2.13Specific PhD research process as a Conceprocity concept map25

3The role of Conceprocity in the PhD research of Mark Gregory: some criticisms and the ways in which they are addressed in the research design26

3.1Why Conceprocity is important in my PhD research26

3.2The challenge according to David Weir26

3.3My response to David Weirs challenge27

3.4Renaud Macgilchrists challenge28

3.5My response to Renaud Macgilchrists challenge29

3.6Recap: why are concept maps essential to this Ph.D. research?29

4Ways of organising personal knowledge and data30

4.1Systems thinking and modelling30

4.2A Wikipedia introduction to Knowledge Organisation31

4.3Schema representation31

4.4Knowledge Representation32

4.5Personal Information Management System PIMS Data Structures34

4.6Knowledge Organisation: an LIS (library and information science) perspective38

5Positioning Conceprocity among Knowledge Organisation Systems39

5.1Knowledge Representation (KR) as the primary dimension for classifying and comparing Knowledge Organisation Systems KOS39

5.2Analytics based on Conceprocity models43

5.3A functional perspective: (Zeng, 2008)43

5.4Some further evaluative comments on concept mapping45

5.5Usage profiles45

5.6How and why Conceprocity differs from G-MOT47

5.7G-MOT strengths48

5.8Conceprocity conceptual data structures49

6A critical evaluation of Conceprocity and some suggestions for future work51

6.1The tentative nature of these initial conclusions: further research proposed51

6.2More fundamental difficulties and objections52

6.3Towards an ontological evaluation of Conceprocity55

6.4Learning by enquiry: some parallels with Checklands LUMAS57

6.5An application to student learning60

6.6Complementary approaches to concept mapping as part of a mixed-methods research approach61

What is the contribution of personal information management systems PIMS to the working model and personal work system of knowledge workers?61

1.Conceprocity concept-process maps. Conceprocity CAPRI or CAPRILOPE models are the result of conscious analysis and specific design by Conceprocity modellers.61

2.Leximancer fuzzy concept maps.61


Table of Figures

Figure 1 The Working Model of a knowledge worker. Source: author7

Figure 2 A concrete model: Kat sitting in Mark's lounge9

Figure 3 More general Conceprocity map10

Figure 4 Conceprocity representation of abstract notions and concrete facts12

Figure 5 Conceprocity relationship syntax13

Figure 6 An association between two concepts14

Figure 7 An aggregation relationship15

Figure 8 A composition relationship15

Figure 9 Specialisation / generalisation relationship16

Figure 10 Regulation relationships for actors17

Figure 11 Regulation relationships for principles17

Figure 12 Precedence relationships17

Figure 13 Basic sequence of events and procedures19

Figure 14 AND logical connector19

Figure 15 Inclusive OR logical connector20

Figure 16 An example of combining events, procedures and logical connectors20

Figure 17 Summary of Grammar Rules22

Figure 18 Concepts and procedures which are expanded elsewhere - signified by highlighted border22

Figure 19 The PhD research process of the author represented as a Conceprocity concept process map25

Figure 20 A tentative set of types of KOS (from Rocha Souza et al., 2010, FIG 1)40

Figure 21 KOS Spectrum Source: (Daconta et al., 2003)41

Figure 22 Levels of ontological precision - (Guarino, 2006)42

Figure 23 KOS Spectrum from (Zeng, 2008, p.161) with suggested functional effectiveness44

Figure 24 Illustrative summary of some of our propositions58

Figure 25 Checkland's LUMAS model Source: (Checkland, 2000)59

Figure 26 Fuzzy concept map of the author's PhD journal produced using Leximancer62

Table of Tables

Table 1 Conceprocity Usage Profiles24

Table 2 How the current research design addresses Delamonts objections to auto-ethnography. Source: author27

Table 3 Knowledge representation according to (Hjrland and Nicolaisen, 2005) with additional commentary in italics32

Table 4 A suggested positioning of Conceprocity and other KOS in Functional Effectiveness terms44

Table 5 Conceprocity Usage Profiles46

Table 6 How Conceprocity differs from G-MOT47

Table 7 Conceptual data structures and their associated metadata49

Table 8 Conceptual Modelling Framework Elements (based on (Wand and Weber, 2002, p.364))56

Table 9 Experiments planned or underway in the current research of Mark Gregory63

An introduction to Conceprocity

Conceprocity is an essentially pragmatic approach to the representation and organisation of explicit knowledge. It is based on the earlier work by the Canadian research centre LICEF (Paquette, 2010). Version 1.0 of Conceprocity was introduced on 09/05/2013. Conceprocity concept process reciprocity 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. The modeller decides the vocabulary and constructs a Conceprocity model in accordance with what can be very simple grammar rules. If the modeller is prepared to learn a little bit more about Conceprocity, then more sophisticated semiotics are available to her as she take advantage of more advanced usage profiles.

Why model personal knowledge conceptually?

We want to achieve models which are isomorphic with the situation that we are seeking to regulate or control. Why? (Conant and Ashby, 1970) tell us that:

The design of a complex regulator often includes the making of a model of the system to be regulated. The making of such a model has hitherto been regarded as optional, as merely one of many possible ways A theorem is presented which shows, under very broad conditions, that any regulator that is maximally both successful and simple must be isomorphic with the system being regulated Making a model is thus necessary. The theorem has the interesting corollary that the living brain, so far as it is to be successful and efficient as a regulator for survival, must proceed, in learning, by the formation of a model (or models) of its environment.

Each of us needs to regulate our own working lives. Modelling for action requires conceptual modelling of the personal work system (Baskerville, 2011) which embodies:

The explicit elements of a persons personal information


Their intentions and means of enacting the knowledge which governs the derivation and use of that personal information.

We need a modelling formalism for concepts and behavioural elements processes acting on concepts.

The authors pragmatic choice is to introd


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