Knowledge organisation by means of concept process mapping Knowledge organisation by means of concept-process mapping
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- 6.3Why Conceprocity distinguishes concepts, procedures and principles
- 10.1Main notions and the symbols used to represent them
- 10.2Additional notions in Conceprocity and why they have been added
- 10.2.2Data
- 10.2.3Forms to model interactions
- 10.2.4Logical operations
6.2G-MOT strengthsG-MOT has many strengths, some of which are not matched in Conceprocity. Its visual editor, although restricted to the Windows desktop, enforces grammar rules much more effectively than does Conceprocity. A notion similar to that of usage profile does exist in G-MOT. One usage profile that exists in G-MOT which has no direct equivalent in Conceprocity is that of an ontology builder and the automatic generation of OWL language statements from the ontology model which is so built. 6.3Why Conceprocity distinguishes concepts, procedures and principlesIn his book (Paquette, 2010) Gilbert Paquette suggests as a reason for distinguishing the notions of concepts, procedures and principles the need to address the weaknesses of existing modelling approaches – such as flowcharts and decision trees: §7Imprecise meaning of the links between the entities that compose the model. §8The ambiguities in graphs where objects, actions on objects and statements of properties that those objects possess are all mixed up and are not represented in a way that helps to differentiate them and uncover their relationships. Paquette suggests distinguishing classes of objects as concepts, actions on concepts as procedures and statements of properties as principles. §9The difficulty of combining in one model objects which at a high summary level in the model need to be developed at a lower level with sub-models whose nature is not the same. Thus for example a principle at a high level might need to be developed as a procedural or conceptual sub-model. §10Existing visual representation formalisms have emerged largely from the computer science and software engineering communities. Formalisms such as Entity Relationship models, modern structured systems analysis, conceptual graphs (John Sowa (Sowa, 2000b, 1984) following Charles Pierce, the object modelling technique and the successor Unified Modelling Language UML are all representation approaches which have been built primarily for the analysis and architectural design of complex software systems. Even to read such diagrams and the links between them is hard, and to create such models requires considerable expertise and an abstraction and conceptualisation capability which may be lacking among the more general knowledge workers whom Paquette (and I) wish to address and empower. Paquette states: “Our goal is different. We need a visual representation system that is both simple enough to be used by educational specialists and learners who are not computer scientists, yet general and powerful enough to represent the structure of knowledge and learning / working scenarios. The distinction and the integration of basic types of knowledge and links in the same language are essential… We present three major steps starting with (1) informal visual modelling for the educated layperson, to help represent interesting knowledge. We then (2) move onto semi-formal modelling to help define target competencies and activity scenarios for knowledge and competency acquisition by learners and workers. Finally (3) we present the more formal visual models (Ontologies) that can be used by software agents to ensure execution of knowledge-based processes on the semantic web.” (Paquette, 2010) slightly amended for clarity.] 10.1Main notions and the symbols used to represent themThe main symbols used include: 
Figure Principal symbols used in Conceprocity 10.2Additional notions in Conceprocity and why they have been addedConceprocity goes even further than G-MOT in distinguishing between different notions. 10.2.1EventsThe existence of events in Conceprocity is directly influenced by event process chain diagrams (Scheer, Thomas and Adam, 2005). The success of event process chain diagrams owes much to their simplicity and the self-imposed constraint of chaining event to function to event to function. We admire that, and note in passing that business students seem much more adept at event process chain diagrams that they are at other formalisms such as entity relationship diagrams. Thus we have introduced events into Conceprocity. This permits us to restrict the use and meaning of arrows in Conceprocity to a single reading for each direction of the arrow, “gives rise to” or “is the result of”. Temporal precedence is indicated by using either a procedure – whose inputs are indicated by an arrow in and whose output is indicated by an arrow out – or an event. 10.2.2DataData and concepts are closely related but not exactly equivalent. For this reason, we represent data in much the same way as concepts making as a visual distinction the fact that they are dark blue in colour rather than light blue. In addition, we recommend that data notions be maintained in a separate data swimlane when Conceprocity is being used to model information systems. 10.2.3Forms to model interactionsThis notion is introduced for the purpose of Information Systems modelling, specifically to extend use case diagrams in what we call usage diagrams. We have made this extension because use case or usage models are intended to model interactions between actors and processes; when a process is computerised, that interaction normally involves completing a form or using a view. An interaction is a representation of a form or view or report. 10.2.4Logical operationsAn important usage of Conceprocity is in modelling algorithms and heuristics. In modelling algorithms, it is necessary to represent sequence, condition and iteration. We prefer to make condition explicit in the form of XOR, OR or AND, and NOT. (G-MOT uses principles for this purpose.) Conceprocity does not introduce a specific visual representation for iteration. There are a number of iteration primitives, which include do while, repeat until, for and for each. Rather than seek to introduce visual symbols for all of these forms of iteration, we have decided to use logical operators either as means of splitting – that is, the logical operator has one input and two or more outputs; or as a means of joining – that is, the logical operator has multiple inputs and only one output. Iteration can then be represented using a backward precedence arrow (typically the arrow goes up the page) and a joining XOR logical operator. Because Conceprocity encourages the use of visual elements, there is nothing to prevent specific sub-communities from introducing their own conventions. We are giving consideration to the introduction of further logical connectors, in particular to represent set operations. This is likely to have particular value in showing how concepts relate to one another, for showing for example UNIONs. 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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