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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 www.MarkRogerGregory.net. 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
2.1An example Conceprocity model and how it has been created9
2.2Conceprocity as a modelling language10
2.4Representing Conceprocity relationships12
2.5Why Conceprocity distinguishes concepts, procedures and principles13
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
4.5Personal 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
5.6How and why Conceprocity differs from G-MOT47
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 introduce a new modelling language: Conceprocity. This modelling language is intended to allow novice and experienced knowledge mapping workers to create a myriad of models. The purpose of these models may vary. Sometimes a model will represent a means of communication between stakeholders in a situation. Sometimes the process of modelling will increase the understanding of a complex situation and lead to better learning by stakeholders.
Why Conceprocity is important and indeed essential to my work
Pragmatism (following Pierce as collected by (Hartshorne et al., 1931)) leads us to suggest:
No model means no regulation and imperfect understanding.
Abductively, we conclude that we all have a personal work system and we must therefore have a model but what is that model? Can we surface it, as individuals and as researchers? Surfacing this model is at the heart of my PhD research.
Designing your working life: learning how to get things done better
The act of living our lives involves:
Your working model: your mental view of who you are and how you act
Your personal work system: how you act to get things done (Allen, 2003)
Your personal information management system: how you keep things found (Jones, 2007)
Your use of technology
Simple Conceprocity model
Figure 1 The Working Model of a knowledge worker. Source: author
Easy to criticise but any model is better than the alternative, which is not none, but an inexplicit one!
An initial model is refined in use, in action
How you can design a better work system
You can choose between:
Explicit personal information system designHowever, for most of us with our current state of learning this is unlikely to be an option.
Serendipitous bricolage: (Ciborra and Jelassi, 1994)
My research largely takes the form of action research (design school) or observation (behaviour school) see (Hevner et al., 2004). The work of (Hevner and Chatterjee, 2010; Hevner, 2010; Hevner et al., 2004) on design science in IS research, and of (Wand and Weber, 2002) on conceptual modelling and information systems have informed both this paper and the design of Conceprocity. To the extent that one potential use of Conceprocity is to conceptualise and therefore support the design of target personal information management systems, the design perspective identified by Hevner and his colleagues is perhaps sometimes appropriate. However, since we suspect that most personal information management systems are the result of serendipitous bricolage rather than the product of deliberate design, it is the more behavioural perspective identified by Hevner which is likely to be significant in the study of actual personal information management systems.
Positioning Conceprocity as a Knowledge Organisation Representation
Concepts may be held both visually and linguistically. Indeed, some hold that there exists right brain and left brain thinking. This notion has developed from the late-1960s research of psycho-biologist Roger W Sperry (see for example the popular presentation (Sperry, 1975)), who discovered that the human brain has two very different ways of thinking corresponding more-or-less to the two separate brain hemispheres):
Right brain thinking is visual and processes information in an intuitive and simultaneous way, looking first at the whole picture then the details
Left brain thinking is verbal and processes information in an analytical and sequential way, looking first at the pieces then putting them together to get the whole
There are various approaches that have been developed to represent knowledge in ways which explicitly exploit right-brain approaches or seek to stimulate right-brain reactions. These include:
Mind Maps Tony Buzan (Buzan and Buzan, 1996)
Concept maps Joseph Novak and collaborators (Novak and Caas, 2008) following David Ausubel (Ausubel, 2000, 1963)
Concept maps with typed concepts and relationships: LICEF (Paquette, 2010); (Basque, 2013)
Concept Process maps: Conceprocity: Mark Gregory (www.markrogergregory.net)
Using both the visual and the linguistic (written and spoken language) stimulates better understanding of a situation and perhaps later better learning.
All these approaches are based on the active creation by individuals of specifically-crafted or designed maps of concepts and their relationships. An alternative and, we believe, complementary approach is discussed below in section 4.4 and included in Table 3.
Conceprocity describedAn example Conceprocity model and how it has been created
Start with a simple English sentence: The cat sat on the mat
Give a specific instance: The cat called Kat sat on the mat in my lounge
A concrete Conceprocity map follows:
Figure 2 A concrete model: Kat sitting in Mark's lounge
Identify concepts, any static relationships and any activities
Create a specific and a more general model using the meta-concepts (Conceprocity calls them notions) of concept, procedure and relationship
Consider concrete and abstract representations
Observe, maybe discuss and then refine the resulting map
Here we choose to remove the concrete and retain the abstract elements in a conceptual model of the general situation of creatures acting in a geographical context
Figure 3 More general Conceprocity map
The model that results depends upon the viewpoint and the purpose of the modeller what (Checkland, 1981) identified as the Weltanschauung of this im...