From artifacts to aggregations: Modeling scientific life cycles on the semantic Web
Identifieur interne : 000213 ( Istex/Corpus ); précédent : 000212; suivant : 000214From artifacts to aggregations: Modeling scientific life cycles on the semantic Web
Auteurs : Alberto Pepe ; Matthew Mayernik ; Christine L. Borgman ; Herbert Van De SompelSource :
- Journal of the American Society for Information Science and Technology [ 1532-2882 ] ; 2010-03.
Abstract
In the process of scientific research, many information objects are generated, all of which may remain valuable indefinitely. However, artifacts such as instrument data and associated calibration information may have little value in isolation; their meaning is derived from their relationships to each other. Individual artifacts are best represented as components of a life cycle that is specific to a scientific research domain or 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's Object Reuse and Exchange data model (OAI‐ORE) meets these requirements. We demonstrate a conceptual implementation of OAI‐ORE to represent the scientific life cycles of embedded networked sensor applications in seismology and environmental sciences. By establishing relationships between publications, data, and contextual research information, we illustrate how to obtain a richer and more realistic view of scientific practices. That view can facilitate new forms of scientific research and learning. Our analysis is framed by studies of scientific practices in a large, multidisciplinary, multi‐university science and engineering research center, the Center for Embedded Networked Sensing.
Url:
DOI: 10.1002/asi.21263
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ISTEX:CA65452B2791E841347C98CA2EB312C78C1517ABLe document en format XML
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By establishing relationships between publications, data, and contextual research information, we illustrate how to obtain a richer and more realistic view of scientific practices. That view can facilitate new forms of scientific research and learning. 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Borgman</name><affiliations><json:string>Center for Embedded Networked Sensing and Department of Information Studies, University of California Los Angeles, CA 90095</json:string></affiliations></json:item><json:item><name>Herbert Van de Sompel</name><affiliations><json:string>Digital Library Research and Prototyping Team, Los Alamos National Laboratory, Los Alamos, NM 87545</json:string></affiliations></json:item></author><articleId><json:string>ASI21263</json:string></articleId><language><json:string>eng</json:string></language><originalGenre><json:string>article</json:string></originalGenre><abstract>In the process of scientific research, many information objects are generated, all of which may remain valuable indefinitely. However, artifacts such as instrument data and associated calibration information may have little value in isolation; their meaning is derived from their relationships to each other. 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By establishing relationships between publications, data, and contextual research information, we illustrate how to obtain a richer and more realistic view of scientific practices. That view can facilitate new forms of scientific research and learning. 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