• Login
    View Item 
    •   DSpace@RPI Home
    • Tetherless World Constellation
    • Tetherless World Publications
    • View Item
    •   DSpace@RPI Home
    • Tetherless World Constellation
    • Tetherless World Publications
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Abstracting Granular Provenance

    Author
    Lebo, Tim; Wang, Ping; Graves, Alvaro; McGuinness, Deborah
    Thumbnail
    Other Contributors
    Date Issued
    2012-04-18
    Subject
    Inference Web
    Degree
    Terms of Use
    Metadata
    Show full item record
    URI
    https://www.researchgate.net/publication/264890457_Abstracting_Granular_Provenance; https://hdl.handle.net/20.500.13015/4564
    Abstract
    As Open Data becomes commonplace, methods are needed to integrate dis- parate data from a variety of sources. Although Linked Data design has promise for integrating world wide data, integrators often struggle to provide appropriate transparency for their sources and transformations. Without this transparency, cautious consumers are unlikely to find enough information to allow them to trust third party results. While capturing provenance in RPI’s Linking Open Government Data project, we were faced with the common problem that only a portion of provenance that is captured is effectively used. Using our water quality portal’s use case as an example, we argue that one key to enabling provenance use is a better treatment of provenance granularity. To address this challenge, we have designed an approach that supports deriving abstracted provenance from granular provenance in an open environment. We describe the approach, show how it addresses the naturally occurring unmet provenance needs in a fam- ily of applications, and describe how the approach addresses similar problems in open provenance and open data environments.;
    Department
    Relationships
    https://tw.rpi.edu/project/InferenceWeb;
    Access
    Collections
    • Tetherless World Publications

    Browse

    All of DSpace@RPICommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    Login

    DSpace software copyright © 2002-2022  DuraSpace
    Contact Us | Send Feedback
    DSpace Express is a service operated by 
    Atmire NV