BibSonomy publications for /concept/tag/database+semanticMon Aug 18 13:50:49 CEST 2008Journal of Biomedical Informatics--Bio2RDF: Towards a mashup to build bioinformatics knowledge systemsIn Press, Corrected Proof2008Bioinformatics web database Ontology Mashup Knowledge Semantic integration Presently, there are numerous bioinformatics databases available on different websites. Although RDF was proposed as a standard format for the web, these databases are still available in various formats. With the increasing popularity of the semantic web technologies and the ever growing number of databases in bioinformatics, there is a pressing need to develop mashup systems to help the process of bioinformatics knowledge integration. Bio2RDF is such a system, built from rdfizer programs written in JSP, the Sesame open source triplestore technology and an OWL ontology. With Bio2RDF, documents from public bioinformatics databases such as Kegg, PDB, MGI, HGNC and several of NCBI's databases can now be made available in RDF format through a unique URL in the form of http://bio2rdf.org/namespace:id. The Bio2RDF project has successfully applied the semantic web technology to publicly available databases by creating a knowledge space of RDF documents linked together with normalized URIs and sharing a common ontology. Bio2RDF is based on a three-step approach to build mashups of bioinformatics data. The present article details this new approach and illustrates the building of a mashup used to explore the implication of four transcription factor genes in Parkinson's disease. The Bio2RDF repository can be queried at http://bio2rdf.org.Fri Nov 23 20:14:26 CET 2007IEEE Trans. Knowl. Data Eng.81089-1101A Method for Estimating the Precision of Placename Matching.192007database integration one-to-one alexandria data precision linkage placename cleaning gazetteer mapping semantics inconsistency estimating method matching record semantic information digital Fri Sep 07 17:29:28 CEST 2007The Semantic Web: Research and ApplicationsThe Semantic Web: Research and Applications624--639Integrating Folksonomies with the Semantic Web2007folksonomy ontology semanticweb semantic discovery database While tags in collaborative tagging systems serve primarily an indexing purpose, facilitating search and navigation of resources, the use of the same tags by more than one individual can yield a collective classification schema. We present an approach for making explicit the semantics behind the tag space in social tagging systems, so that this collaborative organization can emerge in the form of groups of concepts and partial ontologies. This is achieved by using a combination of shallow pre-processing strategies and statistical techniques together with knowledge provided by ontologies available on the semantic web. Preliminary results on the del.icio.us and Flickr tag sets show that the approach is very promising: it generates clusters with highly related tags corresponding to concepts in ontologies and meaningful relationships among subsets of these tags can be identified.Fri May 04 05:48:10 CEST 2007Knowledge and Data Engineering, IEEE Transactions on2271--294Uniform techniques for deriving similarities of objects and subschemes in heterogeneous databases152003homonymies, maximum cooperative object database weight bipartite sources, information matchings, conflicts warehouses, data semantics, type databases, weighted graphs, techniques, semantic heterogeneous closeness, metrics, graph-based distributed systems, similarities, subscheme synonymies, schemes, The availability of automatic tools for inferring semantics of database schemes is useful to solve several database design problems such as that of obtaining cooperative information systems or data warehouses from large sets of data sources. In this context, a main problem is to single out similarities or dissimilarities among scheme objects (interscheme properties). This paper presents graph-based techniques for a uniform derivation of interscheme properties including synonymies, homonymies, type conflicts, and subscheme similarities. These techniques are characterized by a common core: the computation of maximum weight matchings on some bipartite weighted graphs derived using a suitable metrics to measure semantic closeness of objects. The techniques have been implemented in a system prototype. Several experiments conducted with it, and (in part) accounted for in the paper, confirmed the effectiveness of our approach.