Embedding Data within Knowledge Spaces

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dc.creatorMyers, James D.
dc.creatorFutrelle, Joe
dc.creatorGaynor, Jeff
dc.creatorPlutchak, Joel
dc.creatorBajcsy, Peter
dc.creatorKastner, Jason
dc.creatorKotwani, Kailash
dc.creatorLee, Jong Sung
dc.creatorMarini, Luigi
dc.creatorKooper, Rob
dc.creatorMcGrath, Robert E.
dc.creatorMcLaren, Terry
dc.creatorRodriguez, Alejandro
dc.creatorLiu, Yong
dc.date2009-02-04
dc.date.accessioned2026-07-07T12:37:36Z
dc.date.available2026-07-07T12:37:36Z
dc.descriptionThe 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.
dc.description10 pages with 1 figure. Corrected incorrect transliteration in abstract
dc.identifierhttps://arxiv.org/abs/0902.0744
dc.identifierhttp://arxiv.org/abs/0902.0744
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/218494
dc.subjectArtificial Intelligence
dc.subjectHuman-Computer Interaction
dc.subjectInformation Retrieval
dc.subjectH.3.5; H.5.3; I.2.4
dc.titleEmbedding Data within Knowledge Spaces
dc.typetext

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