Yurong He
ABSTRACT
In the absence of systematic knowledge about the characteristics and practices of data collections, successful data hubs and other platforms that support collaborative data sharing are unlikely to be designed and built. We begin to fill this gap by performing an in depth case study of a global scientific data hub -- the Encyclopedia of Life -- in which we analyzed the organizational-level identities of 259 data providers and developing a typology of the identities, including: Venerable organizations, Repositories, Citizen science initiatives, Social media platforms, Education communities, and Subsidiaries. This study will provide data aggregation and integration technology designers with background information on data collections.
- Albert, S. and Whetten, D. (1985). Organizational Identity. Research in Organizational Behavior, 7, 263--295.Google Scholar
- Ashforth, B. E., Harrison, S. H., & Corley, K. G. (2008). Identification in Organizations: An Examination of Four Fundamental Questions. Journal of Management, 34(3), 325--374.Google ScholarCross Ref
- Gaiji S., et al.(2013) Content assessment of the primary biodiversity data published through GBIF network: Status, Challenges and Potentials. Biodiversity \ Informatics 8 (2): 94--172.Google Scholar
- Krippendorff, K. (2012). Content analysis: An introduction to its methodology. Sage. pp: 88--90.Google Scholar
- Parr, C. S., et al. (2014). The Encyclopedia of Life v2: Providing Global Access to Knowledge About Life on Earth. Biodiversity Data Journal, (2).Google Scholar
- Rotman, D., et al. (2012). Supporting content curation communities: The case of the Encyclopedia of Life. Journal of the American Society for Information Science and Technology, 63(6), 1092--1107. Google ScholarDigital Library
- U.S. National Science Board. (2005). Long-lived digital data collections: Enabling research and education in the 21st century: Report of the National Science Board. Arlington, VA: National Science Foundation.Google Scholar
- Wiggins, A., & Crowston, K. (2011). From conservation to crowdsourcing: A typology of citizen science. In System Sciences (HICSS), 2011 44th Hawaii International Conference on (pp. 1--10). IEEE. Google ScholarDigital Library
- Wilson E. O. (2003) The encyclopedia of life. Trends Ecol Evol 18: 77--80.Google ScholarCross Ref
Index Terms
- Understanding Data Providers in a Global Scientific Data Hub
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