Fig-Knowledge integration network

Conceptual network as: a) passive network of concepts evolving through scientific inquiry and communication; b) network of interacting agents (scientists who have their own conceptual network {K} evolving through scientific communication).

By: José María Díaz-Nafría (BITrum Research Group, Spain; Madrid Open University, Spain), Mark Burgin (University of California, Los Angeles, USA), Blanca Rodriguez-Bravo (Universidad de León, Spain)

Published in: G. Dodig-Crnkovic, M. Burgin (eds.), Philosophy and Methodology of Information, Singapore: World Scientific Publishing. DOI: https://doi.org/10.1142/9789813277526_0021

Abstract: The chapter addresses the general problem of assessing the integration of knowledge from different scientific disciplines joined in interdisciplinary settings and its specific application to the study of information. The method is based in the development of Interdisciplinary-Glossaries as tools for the elucidation of the network of concepts involved which also serve as proxies of the corresponding knowledge integration. We show the results obtained from the application of the network approach to a specific interdisciplinary-glossary devoted to the study of information. These results show the capacity of the methodology depicted to guide the future development of knowledge integration by the corresponding interdisciplinary or transdisciplinary teams, as well as to assess their integration achievements. However, the results described are rather qualitative with respect to the knowledge integration attainments. In order to offer a quantitative assessment, we propose an enhanced methodology in which each contribution and participant in the elucidation process is identified by the knowledge domains involved using a set of domains adapted from the higher categories of the Universal Decimal Classification. Such identification allows assessing the integration through a multidimensional perspective based on: (i) the diversity of the disciplines involved, measured in terms of Shannon Diversity Index, and (ii) The effective integration achieved through the meeting of different perspectives, measured through the analysis of both the semantic network of elucidated concepts and the network of participant researchers, in terms of the average minimal distance between any two nodes and the clustering coefficient, which are combined through the small-world-coefficient, σ.

Fig-gB.jpg

glossariumBITri’s Co-occurrence network. Term frequency occurrence & co-ocurrence > 50; Colours: semantic clusters determined by intermediation measurements. Adverbial and prepositional categories are excluded.

By: José María Díaz-Nafría (BITrum-Research Group, Spain; Munich University of Applied Sciences, Germany), Teresa Guarda (Universidad Estatal Península de Santa Elena, Ecuador; Algoritmi Centre, Minho University, Portugal), Iván Coronel (Universidad Estatal Península de Santa Elena, Ecuador)

Published in: Smart Innovation, Systems and Technologies, vol 94.
Springer, Cham. DOI: https://doi.org/10.1007/978-3-319-78605-6_31

Abstract: The paper presents a general approach to assess knowledge integration as a basis to evaluate the performance of transdisciplinary and interdisciplinary approaches with respect to their knowledge integration capacity. The method is based on the development of Interdisciplinary-glossaries as tools for the elucidation of the conceptual networks involved in interdisciplinary studies. Such ID-glossaries are used as proxies of the corresponding knowledge integration, which is measured through the structural analysis of the co-occurrence network of terms. This approach is applied to an ID-glossary devoted to the general study of information, called glossariumBITri. The results show the capacity of the approach to detect integration achievements, challenges and barriers. Its qualitative nature is complemented by an enhanced methodology in which both the diversity   of disciplines and the knowledge integration can be measured in a bi-dimensional index. To that purpose each contribution to the target ID-glossary is identified by the knowledge domains involved (using a set of knowledge domains adapted from the higher categories of the Universal Decimal Classification), while the integration is measured in terms of the small-world coefficient of the co-occurrence of terms.