Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.
© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 28. April 2022)
1Arave, G. ; Jacob, E.K.: Evaluating semantic interoperability across ontologies.
In: Knowledge organization for a sustainable world: challenges and perspectives for cultural, scientific, and technological sharing in a connected society : proceedings of the Fourteenth International ISKO Conference 27-29 September 2016, Rio de Janeiro, Brazil / organized by International Society for Knowledge Organization (ISKO), ISKO-Brazil, São Paulo State University ; edited by José Augusto Chaves Guimarães, Suellen Oliveira Milani, Vera Dodebei. Würzburg : Ergon Verlag, 2016. S.308-316.
(Advances in knowledge organization; vol.15)
Themenfeld: Semantische Interoperabilität
2Ekbia, H. ; Mattioli, M. ; Kouper, I. ; Arave, G. ; Ghazinejad, A. ; Bowman, T. ; Suri, V.R. ; Tsou, A. ; Weingart, S. ; Sugimoto, C.R.: Big data, bigger dilemmas : a critical review.
In: Journal of the Association for Information Science and Technology. 66(2015) no.8, S.1523-1545.
(Advances in information science)
Abstract: The recent interest in Big Data has generated a broad range of new academic, corporate, and policy practices along with an evolving debate among its proponents, detractors, and skeptics. While the practices draw on a common set of tools, techniques, and technologies, most contributions to the debate come either from a particular disciplinary perspective or with a focus on a domain-specific issue. A close examination of these contributions reveals a set of common problematics that arise in various guises and in different places. It also demonstrates the need for a critical synthesis of the conceptual and practical dilemmas surrounding Big Data. The purpose of this article is to provide such a synthesis by drawing on relevant writings in the sciences, humanities, policy, and trade literature. In bringing these diverse literatures together, we aim to shed light on the common underlying issues that concern and affect all of these areas. By contextualizing the phenomenon of Big Data within larger socioeconomic developments, we also seek to provide a broader understanding of its drivers, barriers, and challenges. This approach allows us to identify attributes of Big Data that require more attention-autonomy, opacity, generativity, disparity, and futurity-leading to questions and ideas for moving beyond dilemmas.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23294/abstract.
Themenfeld: Data Mining