Linked Data Semantic Repository

Linked Data Semantic Repository (LDSR) represents a reason-able view to the web of data. It aims to allow users to find resources and facts based on the semantics of the data, like web search engines index WWW pages and facilitate their usage.

LDSR enables users to easily identify resources in the Linking Open Data (LOD) cloud. It provides efficient mechanism to query data from multiple datasets and sources, considering their semantics. LDSR is designed also as a use-case for large-scale reasoning and data integration.

LDSR includes several of the most central datasets of LOD. OWLIM semantic repository is used to load the data and "materialize" the facts that could be inferred from it. It is probably the largest and most heterogeneous body of general factual knowledge that was ever used for logical inference.

The Data

• Datasets included: DBPedia, Freebase, Geonames, UMBEL, Wordnet, CIA World Factbook, Lingvoj, MusicBrainz (RDF from Zitgist).
• Ontologies: several schemata used in the datasets are also loaded into LDSR: Dublin Core, SKOS, RSS, FOAF.
• Size: 1B explicit plus 0.6B inferred statements are indexed; there are 4B different retrievable statements.
• Inference: materialization is performed with respect to the semantics of RDFS, extended with incomplete support for OWL Lite.

Access and Usage

The data is accessible through a web use interface at http://ldsr.ontotext.com, which allows:

• RDF Search - retrieve ranked list of URIs related to literals, which contain specific keywords
• Exploration - traversing the data, one resource at a time
  For instance, one can "browse" Madrid with its DBPedia URI, <http://dbpedia.org/resource/Madrid> or dbpedia:Madrid
• Evaluation of queries in SPARQL and other languages.
  For instance, to obtain a list of entertainers born in Bavaria one can use the following SPARQL query:

                     (...add prefixes here...)
      SELECT * WHERE {
        ?Person dbp-ont:birthPlace [geo-ont:parentFeature dbpedia:Bavaria] ;
                rdf:type opencyc:Entertainer ;
                owlim:hasPageRank ?RR .
      } ORDER BY DESC(?RR) LIMIT 100
  
  

  This is an example of a structured query, the evaluation of which involves data from 4 datasets and interpretation of the semantics of several schemata (i.e. reasoning). Within few seconds it returns results ranked by PageRank (in the RDF graph). OpenCyc's vocabulary is used, although the dataset itself is not loaded in LDSR (it is only referred from UMBEL). Lou Bega appears on the top of the list, because of the data from MusicBrainz, although the latter dataset is not explicitly referred in the query.

Credits and References

"Linked data" represents a set of principles for publishing of structured data they can be explored and navigated in a manner analogous to the HTML WWW. The linked data concept is an enabling factor for the realization of the Semantic Web as a global web of structured data around the Linking Open Data initiative.

LDSR is developed as an evaluation case in the European research project LarKC. The development of OWLIM, as well as other relevant technology and know-how, has been supported by several projects within programs FP5, FP6, and FP7 of the European Commission: RASCALLI, TAO, TripCom, SEKT, On-To-Knowledge.

The Linked Life Data service is similar to LDSR. It represents a reason-able view towards the life science part of LOD, including Uniprot, GeneOntology, and more than 20 other datasets. LDSR and LLD are based on the same technology: Forest semantic web fronts-ends and OWLIM semantic repository. With its 3 billion explicit statements, LLD is probably the largest body of non-synthetic knowledge that was used for inference.

Notes and Disclaimers

• add more datasets and ontologies
• provide better exploration interfaces
• establish a regular update procedure (currenlty, LDSR is updated once per month on average)