Embedding Data within Knowledge Spaces

Details Embedding Data within Knowledge Spaces Embedding Data within Knowledge Spaces

2009-02-04

arxiv.org/abs/0902.0744v1

Computer Science

Artificial Intelligence

10 pages with 1 figure. Corrected incorrect transliteration in abstract

Scientific paper

The promise of e-Science will only be realized when data is discoverable, accessible, and comprehensible within distributed teams, across disciplines, and over the long-term--without reliance on out-of-band (non-digital) means. We have developed the open-source Tupelo semantic content management framework and are employing it to manage a wide range of e-Science entities (including data, documents, workflows, people, and projects) and a broad range of metadata (including provenance, social networks, geospatial relationships, temporal relations, and domain descriptions). Tupelo couples the use of global identifiers and resource description framework (RDF) statements with an aggregatable content repository model to provide a unified space for securely managing distributed heterogeneous content and relationships.

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