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A comprehensive record of research data provenance is essential for the successful curation, management, and reuse of data over time. However, creating such detailed metadata can be onerous, and there are few structured methods for doing so. In this case study of data curation in support of geobiology research conducted at Yellowstone National Park, we describe a method of “Research Process Modeling”...
The Site‐Based Data Curation (SBDC) project is developing a framework of guidelines and processes for the curation of research data generated at scientifically significant sites. SBDC will advance the professional work of curation by articulating principles, workflows and inter‐institutional relationships essential for site‐based curation. Work to date has concentrated on stakeholder analysis, with...
Heterogeneous digital data that has been produced by different communities with varying practices and assumptions, and that is organized according to different representation schemes, encodings, and file formats, presents substantial obstacles to efficient integration, analysis, and preservation. This is a particular impediment to data reuse and interdisciplinary science. An underlying problem is...
The concept of a collection plays key roles in library, museum, and archival practice, and is arguably fundamental to information organization systems in general. Locating collection concepts in a reasonably robust ontology should have a number of practical advantages, including revealing inferencing opportunities and supporting consistency and coherence in system design and modeling. Although research...
Collections of artifacts, images, texts, and other cultural objects are not arbitrary aggregations, but are designed to support specific research and scholarly activities. Collection‐level metadata directly supports this objective, providing critical contextual information. However, exploiting this information, especially in a semantic web environment of linked data, requires a precise formalization...
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...
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