Big Data: Impact on Library and Information Service
Abstract
Libraries play an important role at the intersections of government, universities, research institutes, and the public since they are storing and managing digital assets. The large amount of data and those data in library need to be transformed into information or knowledge which then be used by researchers or users. Librarians might need to understand how to transform, analyze, and present data in order to facilitate knowledge creation. For example, they should know how to make big datasets more useful, visible and accessible. With new and powerful analytics of big data, such as information visualization tools, researchers/users can look at data in new ways and mine it for information they intend to have. This paper discussed the characteristics of datasets in library, the research work on library big data and then summarized the applications in this field.
Keywords: Big data, Big Data Architecture, Hadoop cluster, Big Data and Libraries, Classification and Cataloguing of Big Data, Metadata
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References
2. Snijders, C. Matzat, U. and Reips, U.-D. (2012). 'Big Data': Big gaps of knowledge in the field of Internet. International Journal of Internet Science 7: 1–5.
3. Gartner Group (2011). Pattern Based Strategy: Getting Value From Big Data. Available at: http:/ /www.gartner.com/it/page.jsp?id=1731916 (Accessed on 18.03.2018).
4. Cárdenas, Alvaro A. Manadhata, Pratyusa K. and Rajan, Sree (2013). Big Data Analytics for Security Intelligence. Big DataWorking Group Cloud Security Alliance. Available at: https:// cloudsecurityalliance.org/ download/big-dataanalytics-for-security-intelligence/ (Accessed on 23.01.2018).
5. Sugimoto, Cassidy R. Ding, Ying and Thelwall, Mike (2012). Library and information science in the big data era: Funding, projects, and future [a panel proposal] IN Proceedings of the American Society for Information Science and Technology. Volume 49, Issue 1, pages 1–3.
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