Theoretical Foundations of Information Visualization
Information Visualization
Semantic sitemaps: efficient and flexible access to datasets on the semantic web
ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
XDTM: the XML data type and mapping for specifying datasets
EGC'05 Proceedings of the 2005 European conference on Advances in Grid Computing
A research agenda for data curation cyberinfrastructure
Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
When use cases are not useful: data practices, astronomy, and digital libraries
Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
The conundrum of sharing research data
Journal of the American Society for Information Science and Technology
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The integration of heterogeneous data in varying formats and from diverse communities requires an improved understanding of the concept of a dataset, and of key related concepts, such as format, encoding, and version. Ultimately, a normative formal framework of such concepts will be needed to support the effective curation, integration, and use of shared multi-disciplinary scientific data. To prepare for the development of this framework we reviewed the definitions of dataset found in technical documentation and the scientific literature. Four basic features can be identified as common to most definitions: grouping, content, relatedness, and purpose. In this summary of our results we describe each of these features, indicating the directions a more formal analysis might take.