Nodes and arcs: concept map, semiotics, and knowledge organization

Abstract

Purpose-The purpose of the research reported here is to improve comprehension of the socially-negotiated identity of concepts in the domain of knowledge organization. Because knowledge organization as a domain has as its focus the order of concepts, both from a theoretical perspective and from an applied perspective, it is important to understand how the domain itself understands the meaning of a concept. Design/methodology/approach-The paper provides an empirical demonstration of how the domain itself understands the meaning of a concept. The paper employs content analysis to demonstrate the ways in which concepts are portrayed in KO concept maps as signs, and they are subjected to evaluative semiotic analysis as a way to understand their meaning. The frame was the entire population of formal proceedings in knowledge organization-all proceedings of the International Society for Knowledge Organization's international conferences (1990-2010) and those of the annual classification workshops of the Special Interest Group for Classification Research of the American Society for Information Science and Technology (SIG/CR). Findings-A total of 344 concept maps were analyzed. There was no discernible chronological pattern. Most concept maps were created by authors who were professors from the USA, Germany, France, or Canada. Roughly half were judged to contain semiotic content. Peirceian semiotics predominated, and tended to convey greater granularity and complexity in conceptual terminology. Nodes could be identified as anchors of conceptual clusters in the domain; the arcs were identifiable as verbal relationship indicators. Saussurian concept maps were more applied than theoretical; Peirceian concept maps had more theoretical content. Originality/value-The paper demonstrates important empirical evidence about the coherence of the domain of knowledge organization. Core values are conveyed across time through the concept maps in this population of conference papers.

Nursing identity and patient-centredness in scholarly health services research: a computational text analysis of PubMed abstracts 1986–2013

“…Sentiment analysis is about understanding the extent to which a concept is semantically proximate to sentiment words generally, as well as the extent to which a concept is semantically proximate to positive versus negative words. In terms of our theoretical framework, we agree that the definition of a concept used in concept mapping is itself the result of epistemologies [ 75 ].…”

Ontological realism and classification: Structures and concepts in the Gene Ontology

“…There are different understandings of what a concept, in the context of a vocabulary or ontology, is, and systems for knowledge organization differ accordingly; see, for example, Hjørland () and Friedman and Smiraglia (). Concept analysis is here used to test the extent to which concepts in the GO are stable, context‐free, and value‐free, as its declared basis of ontological realism would seem to require.…”

Construction method of a reconfigurable Process Knowledge Map

“…Abroad study on knowledge map is conducted deeply. Microsoft started to Supported by the National Science and Technology Major Project (2012ZX04011-011) construct knowledge map as early as 1995 while Siemens took the knowledge map as a principle part of their knowledge management system [17][18][19] . In the research area of process knowledge in China, Xue Hao built a process knowledge map model contains resources layer, attribute layer, and display layer to resolve problems of knowledge sharing and reusing [20] .…”