Journal review: International Journal of Knowledge and Systems Science (IJKSS)
This article is part of a series that is progressively reviewing journals for their KM content.
|Official Journal Synopsis||The International Journal of Knowledge and Systems Science (IJKSS) serves as a multi-disciplinary platform and adopts a systems approach to the theory and practice of managing information and people in knowledge intensive activities and processes, emphasizing the understanding of humans and their environment as part of interacting systems from both soft and hard systems science. A quarterly journal that publishes theoretical, experimental, and experiential papers, practice notes, case studies, and innovative methodologies, IJKSS provides a forum for academicians, scientists, practitioners, and industry professionals to integrate diversity and fragments of knowledge from mathematical, technical, social, psychological, and philosophical frameworks.|
|Significant Figures||Launched by the International Society of Knowledge and Systems Science, which was initiated in 2000 in Japan
Journal founded by Professor Y Nakamori, Professor ZT Wang and Professor J Gu in 2003
Founding editor Professor ZT Wang
Current Editor-in-Chief Van Nam Huynh (JAIST, Japan)
Contributors were noted to be from a diverse range of countries including Japan, Vietnam, India and UAE. Full tables of contents, abstracts and introductory text is available for all issues and articles, but the lack of full open access text inhibits knowledge sharing among the KM community.
Based on an informal assessment of several articles available online via other means through DOI references, the IJKSS journal appears to mostly focus on mathematical and ontological modelling applied to a range of practical contexts.
There is little attempt to offer systematic hypotheses based on KM or other theoretical frameworks, or to validate the accuracy of observed outcomes. However the articles do present detailed information about technical implementation considerations such as underlying mathematical formula, technology stacks utilised, and techniques for mapping of source data to outputs. These would all be valuable to others seeking to develop and implement their own systematic knowledge processes based on similar organisational needs.