Literature DB >> 25750938

Don't Like RDF Reification? Making Statements about Statements Using Singleton Property.

Vinh Nguyen1, Olivier Bodenreider2, Amit Sheth1.   

Abstract

Statements about RDF statements, or meta triples, provide additional information about individual triples, such as the source, the occurring time or place, or the certainty. Integrating such meta triples into semantic knowledge bases would enable the querying and reasoning mechanisms to be aware of provenance, time, location, or certainty of triples. However, an efficient RDF representation for such meta knowledge of triples remains challenging. The existing standard reification approach allows such meta knowledge of RDF triples to be expressed using RDF by two steps. The first step is representing the triple by a Statement instance which has subject, predicate, and object indicated separately in three different triples. The second step is creating assertions about that instance as if it is a statement. While reification is simple and intuitive, this approach does not have formal semantics and is not commonly used in practice as described in the RDF Primer. In this paper, we propose a novel approach called Singleton Property for representing statements about statements and provide a formal semantics for it. We explain how this singleton property approach fits well with the existing syntax and formal semantics of RDF, and the syntax of SPARQL query language. We also demonstrate the use of singleton property in the representation and querying of meta knowledge in two examples of Semantic Web knowledge bases: YAGO2 and BKR. Our experiments on the BKR show that the singleton property approach gives a decent performance in terms of number of triples, query length and query execution time compared to existing approaches. This approach, which is also simple and intuitive, can be easily adopted for representing and querying statements about statements in other knowledge bases.

Entities:  

Keywords:  Meta triples; RDF; RDF Singleton Property; Reification; SPARQL; Semantic Web

Year:  2014        PMID: 25750938      PMCID: PMC4350149          DOI: 10.1145/2566486.2567973

Source DB:  PubMed          Journal:  Proc Int World Wide Web Conf


  2 in total

1.  Provenance Context Entity (PaCE): Scalable Provenance Tracking for Scientific RDF Data.

Authors:  Satya S Sahoo; Olivier Bodenreider; Pascal Hitzler; Amit Sheth; Krishnaprasad Thirunarayan
Journal:  Sci Stat Database Manag       Date:  2010

2.  A unified framework for managing provenance information in translational research.

Authors:  Satya S Sahoo; Vinh Nguyen; Olivier Bodenreider; Priti Parikh; Todd Minning; Amit P Sheth
Journal:  BMC Bioinformatics       Date:  2011-11-29       Impact factor: 3.169

  2 in total
  3 in total

1.  Automated identification of molecular effects of drugs (AIMED).

Authors:  Safa Fathiamini; Amber M Johnson; Jia Zeng; Alejandro Araya; Vijaykumar Holla; Ann M Bailey; Beate C Litzenburger; Nora S Sanchez; Yekaterina Khotskaya; Hua Xu; Funda Meric-Bernstam; Elmer V Bernstam; Trevor Cohen
Journal:  J Am Med Inform Assoc       Date:  2016-04-23       Impact factor: 4.497

2.  Knowledge will Propel Machine Understanding of Content: Extrapolating from Current Examples.

Authors:  Amit Sheth; Sujan Perera; Sanjaya Wijeratne; Krishnaprasad Thirunarayan
Journal:  Proc IEEE WIC ACM Int Conf Web Intell Intell Agent Technol       Date:  2017-08

3.  RDF2Graph a tool to recover, understand and validate the ontology of an RDF resource.

Authors:  Jesse Cj van Dam; Jasper J Koehorst; Peter J Schaap; Vitor Ap Martins Dos Santos; Maria Suarez-Diez
Journal:  J Biomed Semantics       Date:  2015-10-23
  3 in total

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