Knowledge organisation by means of concept process mapping Knowledge organisation by means of concept-process mapping
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- 12.1My response to Renaud Macgilchrist’s challenge
- 12.2Recap: why are concept maps essential to this Ph.D. research
- §13Ways of organising personal knowledge and data
11.4Renaud Macgilchrist’s challengeAccording to my colleague Renaud Macgilchrist, I need clearly to distinguish between
and: §12The infinite range of specific models, instances of models, which can be constructed using those language systems. I need to set out a Table of Criteria for choosing a language system which gives a weighted evaluation of the various alternative language systems.
An initial table of criteria for choosing a language system appears as Table . The remainder of this paper can be regarded as my more general response to this challenge.
“Thomas Kuhn (1922–1996) … developed a theory of concepts that corresponds with his theory of paradigms and that has been considered an important contribution to concept theory. This connection between “paradigms” and “concepts” is the point of departure for the present article. An important view of concepts today can be said to be “post-Kuhnian” in the sense that it is recognized that different theories and “paradigms” may be considered the most important mechanism for the development of concepts. However… different “paradigms” do not totally replace each other but exist together and compete with each other in all domains all the time (see, e.g., Mayr, 1997, pp. 98–994). These criticisms are the reason for using the term “post-Kuhnian” rather than “Kuhnian” in the present article. The term “post- Kuhnian” should not, however, be seen as an indication that the underlying view is primarily taken from Kuhn. There are perspectives, such as pragmatism, activity theory, and hermeneutics that are both older and have played a greater role for the views developed in the present article.” My own stance here is both pragmatic and pragmatist. I can illustrate the pragmatic by drawing an analogy between my work here on personal information management systems within the context of personal knowledge work and that of librarians and information scientists in cataloguing and classifying knowledge made explicit as books. It is no coincidence that the majority of serious academic writing about concept mapping is associated with library and information science (but also with cognitive science). Writing a Ph.D. about personal information management is an exercise in personal knowledge management. Much of social science concerns itself with constructs and their relationships. In areas of enquiry such as that of personal information management systems - where I hold that the understanding of the field of enquiry is as yet too imprecise and incomplete to admit of the possibility of traditional positivist research - what is instead necessary is to identify and to map out concepts. Thus pragmatically I need to carry out concept mapping. The prototype pragmatist, Charles Peirce, created what he called existential graphs and on what (Sowa, 1992) has more recently renamed conceptual graphs. A conceptual graph (CG) is a graph representation for logic based on the semantic networks of artificial intelligence and on existential graphs. Conceptual graphs are admirably precise - they can be directly transposed into the RDF semantic Web knowledge representation because both have formal semantics. I prefer concept maps because it is possible to start from the informal stance adopted by people who are not specialists in logic or computer science and then gradually, often by means of dialogue or even by dialogic mentoring, to refine what is understood into ever more precise knowledge maps. These too can be formalised and directly transposed into RDF and OWL if that is appropriate. It is not appropriate when the primary purpose of concept maps is to attempt to give greater precision to the sometimes essentially imprecise or ambiguous notions partially and incompletely understood by individual knowledge workers. We are modelling to understand, to learn and perhaps to act. Thus pragmatically I have preferred Conceprocity concept and process maps to more formal knowledge representation techniques. I am aware that the notion of concepts presented in this paper is very impoverished when compared with the analytical philosopher’s point of view. See for example (Hjørland, 2009) and ??? §13Ways of organising personal knowledge and data13.1Systems thinking and modelling(Stowell and Welch, 2012, p.xiv) following (Checkland, 1981); see also (Stowell, 2013); identify as the basic building blocks of systems thinking (1) emergence, (2) hierarchy, (3) communication and (4) control. They discuss how a system is defined from the perspective of an observer, who chooses to draw a boundary reflecting a field of interest and giving to the system so defined a name. They remind us of the taxonomy of three systemic models originally identified by Russell Ackoff (Ackoff, Gupta and Minas, 1962) and they extend it with a fourth following Brian Wilson (Wilson, 1984) to yield:
(Stowell and Welch, 2012) present modelling as a kind of surrogate representation of some situation. It is in the process of forming, reforming and structuring that model that we begin to learn about the situation of interest and its similarities and differences to the situation that we are modelling. Among the dangers inherent in such modelling are that it becomes an end in and of itself. Instead a model is only an abstraction of our perception of reality. As a simplification it is also often subjective. Conceprocity enables the creating and maintenance of shared conceptual models. Directory: 2015 2015 -> 587 Return function, r i(X) r i(0) r i(1) r i(2) r i(3) 1 0 2 4 6 Thermal Station, I 2 0 1 5 6 3 0 3 5 6 10 2015 -> Fall 2013 Spring 2014 Program Data: Standard 1 Exhibit 4d 2015 -> Police Militarization 2015 -> Medical Radiography Program 2015 -> 2015 ihbb championships: hs history Bowl Round 4 – Prelims First Quarter 2015 -> Desk review yemen 2015 -> Wrtp/big step · 3841 W. Wisconsin Ave., Milwaukee, wi 53208 2015 -> 1. naclo 2015 – North American Computational Linguistics Olympiad 2015 -> Rao bulletin 1 December 2015 html edition this bulletin contains the following articles 2015 -> Volume Ⅴ (2015) On The 2015 China Victory Day Parade Download 395.15 Kb. Share with your friends:
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