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Technology to Represent Scientific Practice: Data, Life Cycles, and Value Chains

Alberto Pepe, University of California - Los Angeles
Matthew Mayernik, University of California - Los Angeles
Christine L. Borgman, University of California, Los Angeles
Herbert van de Sompel, Los Alamos National Laboratories


In the process of scientific research, many artifacts are generated. Until recently, only the final product ¬– the publication ¬– was deemed worthy of curation for future use. Now, the full range of products generated during the research life cycle may remain valuable indefinitely. However, individual artifacts such as instrument data and associated calibration information may have little value alone; their meaning is derived from their relationships to each other. Individual artifacts thus are best described and represented as components of value chains, which may be specific to the life cycle of a given research project. Current cataloging practices do not describe objects at a sufficient level of granularity nor do they offer the globally persistent identifiers necessary to discover and manage scholarly products with World Wide Web standards. The Open Archives Initiative – Object Reuse and Exchange protocol (OAI-ORE) meets these requirements. We demonstrate, through the use of case studies in seismology and environmental engineering, how OAI-ORE can be used to express value chains within a life cycle of scientific research. By establishing the relationships between publications, data, and contextual research information, we can obtain a richer and more realistic view of scholarly practices. That view can be used to facilitate new forms of scientific research and learning. Our analysis is framed by studies of scientific practices in a large, multi-disciplinary, multi-university science and engineering research center, the Center for Embedded Networked Sensing (CENS).

Suggested Citation

Alberto Pepe, Matthew Mayernik, Christine L. Borgman, and Herbert van de Sompel. "Technology to Represent Scientific Practice: Data, Life Cycles, and Value Chains" arXiv (2009).
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