Document (#40623)

Author
Ibekwe-SanJuan, F.
Bowker, G.C.
Title
Implications of big data for knowledge organization
Source
Knowledge organization. 44(2017) no.3, S.187-198
Year
2017
Abstract
In this paper, we propose a high-level analysis of the implications of big data for knowledge organisation (KO) and knowledge organisation systems (KOSs). We confront the current debates within the KO community about the relevance of universal bibliographic classifications and the thesaurus in the web with the ongoing discussions about the epistemological and methodological assumptions underlying data-driven inquiry. In essence, big data will not remove the need for humanly-constructed KOSs. However, ongoing transformations in knowledge production processes entailed by big data and Web 2.0 put pressure on the KO community to rethink the standpoint from which KOSs are designed. Essentially, the field of KO needs to move from laying down the apodictic (that which we know for all time) to adapting to the new world of social and natural scientific knowledge by creating maximally flexible schemas-faceted rather than Aristotelean classifications. KO also needs to adapt to the changing nature of output in the social and natural sciences, to the extent that these in turn are being affected by the advent of big data. Theoretically, this entails a shift from purely universalist and normative top-down approaches to more descriptive bottom-up approaches that can be inclusive of diverse viewpoints. Methodologically, this means striking the right balance between two seemingly opposing modalities in designing KOSs: the necessity on the one hand to incorporate automated techniques and on the other, to solicit contributions from amateurs (crowdsourcing) via Web 2.0 platforms.
Content
Beitrag in einem Special Issue "New Trends for Knowledge Organization, Guest Editor: Renato Rocha Souza".

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