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Data shopping in an open marketplace: Introducing the Ontogrator web application for marking up data using ontologies and browsing using facets
Author(s) -
Norman Morrison,
David G. Hancock,
Lynette Hirschman,
Peter Dawyndt,
Bert Verslyppe,
Nikos C. Kyrpides,
Renzo Kottmann,
Pelin Yilmaz,
Frank Oliver Glöckner,
Jeffrey S. Grethe,
Tim Booth,
Peter Sterk,
Goran Nenadić,
Dawn Field
Publication year - 2011
Publication title -
standards in genomic sciences
Language(s) - English
Resource type - Journals
ISSN - 1944-3277
DOI - 10.4056/sigs.1344279
Subject(s) - computer science , thriving , world wide web , information retrieval , quality (philosophy) , data science , annotation , product (mathematics) , artificial intelligence , sociology , geometry , mathematics , social science , philosophy , epistemology
In the future, we hope to see an open and thriving data market in which users can find and select data from a wide range of data providers. In such an open access market, data are products that must be packaged accordingly. Increasingly, eCommerce sellers present heterogeneous product lines to buyers using faceted browsing. Using this approach we have developed the Ontogrator platform, which allows for rapid retrieval of data in a way that would be familiar to any online shopper. Using Knowledge Organization Systems (KOS), especially ontologies, Ontogrator uses text mining to mark up data and faceted browsing to help users navigate, query and retrieve data. Ontogrator offers the potential to impact scientific research in two major ways: 1) by significantly improving the retrieval of relevant information; and 2) by significantly reducing the time required to compose standard database queries and assemble information for further research. Here we present a pilot implementation developed in collaboration with the Genomic Standards Consortium (GSC) that includes content from the StrainInfo, GOLD, CAMERA, Silva and Pubmed databases. This implementation demonstrates the power of ontogration and highlights that the usefulness of this approach is fully dependent on both the quality of data and the KOS (ontologies) used. Ideally, the use and further expansion of this collaborative system will help to surface issues associated with the underlying quality of annotation and could lead to a systematic means for accessing integrated data resources.

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