Data shopping in an open marketplace: Introducing the Ontogrator web application for marking up data using ontologies and browsing using facets

Standards in Genomic Sciences - Tập 4 - Trang 286-292 - 2011
Norman Morrison1,2, David Hancock1,2, Lynette Hirschman3, Peter Dawyndt4, Bert Verslyppe4, Nikos Kyrpides5, Renzo Kottmann6, Pelin Yilmaz6,7, Frank Oliver Glöckner6, Jeff Grethe8, Tim Booth2, Peter Sterk9, Goran Nenadic1, Dawn Field2,9
1School of Computer Science, University of Manchester, Manchester, UK
2NERC Centre for Ecology and Hydrology, Natural Environment Research Council Environmental Bioinformatics Centre, Wallingford, UK
3The MITRE Corporation, Bedford, USA
4Department of Applied Mathematics and Computer Science, Ghent University, Ghent, Belgium
5DOE Joint Genome Institute, Walnut Creek, USA
6Microbial Genomics Group, Max Planck Institute for Marine Microbiology, Bremen, Germany
7Jacobs University Bremen GmbH, Bremen, Germany
8University of California, San Diego, La Jolla, USA
9Molecular Evolution and Bioinformatics Group, NERC Centre for Ecology and Hydrology, Wallingford, UK

Tóm tắt

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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