FactForge - Fast Track to The Center of the Data Web

FactForge (formerly 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.

FactForge 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. FactForge is designed also as a use-case for large-scale reasoning and data integration.

FactForge 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. Read more: presentation, brochure, presentation.

The Data

FactForge has the following characteristics:

Access: Public Service at

The data is accessible through a web use interface at, 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, <> or dbpedia:Madrid
  • Evaluation of queries in SPARQL and other languages. 
    For instance, to obtain a list of politicians born in Germany one can use the following SPARQL query:
    (...add prefixes here...)SELECT * WHERE { 
     ?Person dbp-ont:birthPlace [geo-ont:parentFeature dbpedia:Germany] ; 
             rdf:type dbp-ont:Politicians ; 
             om:hasRDFRank ?RR . 
    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).
  • Reference layer - using PROTON to access FactForge datasets

    The same query can be formulated using the PROTON reference layer predicates only: 
    (...add prefixes here...)SELECT * WHERE { 
     ?Person pext:birthPlace [ptop:subRegionOf dbpedia:Germany] ; 
             pext:hasProfession pext:Politician ;
             om:hasRDFRank ?RR .
    } ORDER BY DESC(?RR)  

         Note that the conceptualization of Politician in this model is a profession, whereas in the first query, Politician is  
         defined as a person. Additionally, executing the second query retrieves 35% more results over the entire FactForge

A public SPARQL end-point is available at, allowing FactForge to be used as a query evaluation web service.

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.

FactForge has been initially developed as an evaluation case in the European research project LarKC. It has been extended, improved and build into the data layer infrastructure of RENDER FP7 European research project.  The development of OWLIM, as well as other relevant technology and know-how, has been supported by several projects within programs FP5FP6, and FP7 of the European Commission: RASCALLI, TAO, TripCom, SEKT, On-To-Knowledge.

The Linked Life Data service is similar to FactForge. It represents a reason-able view towards the life science part of LOD, including UniProtGeneOntology, and more than 20 other datasets. FactForge and LLD are based on the same technology: Forest semantic web fronts-ends and OWLIM semantic repository. With its 5 billion explicit statements, LLD is probably the largest body of non-synthetic knowledge that was used for inference.

Notes and Disclaimers

FactForge is an experimental project from Ontotext. The access to this demonstration service is free of charge. Ontotext does not provide any guarantees for quality, availability, or fitness for particular purpose. FactForge is far from perfect. Here are few comments on known shortcomings and development plans:

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