DATA SHARING ACROSS RESEARCH AND PUBLIC COMMUNITIES
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For several decades, the intensifying trend of researchers to believe that sharing research data is “good” has overshadowed the belief that sharing data is “bad.” However, sharing data is difficult even though an impressive effort has been made to solve data sharing issues within the research community, but relatively little is known about data sharing beyond the research community. This dissertation aims to address this gap by investigating how data are shared effectively across research and public communities.
The practices of sharing data with both researchers and non-professionals in two comparative case studies, Encyclopedia of Life and CyberSEES, were examined by triangulating multiple qualitative data sources (i.e., artifacts, documentation, participant observation, and interviews). The two cases represent the creation of biodiversity data, the beginning of the data sharing process in a home repository, and the end of the data sharing process in an aggregator repository. Three research questions are asked in each case:
• Who are the data providers?
• Who are the data sharing mediators?
• What are the data sharing processes?
The findings reveal the data sharing contexts and processes across research and public communities. Data sharing contexts are reflected by the cross-level data providers and human mediators rooted in different groups, whereas data sharing processes are reflected by the dynamic and sustainable collaborative efforts made by different levels of human mediators with the support of technology mediators.
This dissertation provides theoretical and practical contributions. Its findings refine and develop a new data sharing framework of knowledge infrastructure for different-level data sharing across different communities. Both human and technology infrastructure are made visible in the framework. The findings also provide insight for data sharing practitioners (i.e., data providers, data mediators, data managers, and data contributors) and information system developers and designers to better conduct and support open and sustainable data sharing across research and public communities.