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arXiv · 2105.10923

Towards Knowledge Organization Ecosystems

Mayukh Bagchi
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Abstract

It is needless to mention the (already established) overarching importance of knowledge organization and its tried-and-tested high-quality schemes in knowledge-based Artificial Intelligence (AI) systems. But equally, it is also hard to ignore that, increasingly, standalone KOSs are becoming functionally ineffective components for such systems, given their inability to capture the continuous facetization and drift of domains. The paper proposes a radical re-conceptualization of KOSs as a first step to solve such an inability, and, accordingly, contributes in the form of the following dimensions: (i) an explicit characterization of Knowledge Organization Ecosystems (KOEs) (possibly for the first time) and their positioning as pivotal components in realizing sustainable knowledge-based AI solutions, (ii) as a consequence of such a novel characterization, a first examination and characterization of KOEs as Socio-Technical Systems (STSs), thus opening up an entirely new stream of research in knowledge-based AI, and (iii) motivating KOEs not to be mere STSs but STSs which are grounded in Ethics and Responsible Artificial Intelligence cardinals from their very genesis. The paper grounds the above contributions in relevant research literature in a distributed fashion throughout the paper, and finally concludes by outlining the future research possibilities.

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Mayukh Bagchi. 2021-05-23. Towards Knowledge Organization Ecosystems. https://arxiv.org/abs/2105.10923

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