Temporal Extensions to RDF

  • Hsien-Tseng Wang Department of Computer Science, The Graduate Center, The City University of New York, USA
  • Abdullah Uz Tansel Department of Computer Science, The Graduate Center, The City University of New York, USA , Paul H. Chook Department of Information Systems and Statistics, Baruch College, The City University of New York, USA, School of Engineering, Thammasat University Thailand
Keywords: The Semantic Web, Resource Description Framework, Taxonomy, Temporal Data, Temporal Knowledge


The Semantic Web aims at building a foundation of semantic-based data models and languages for not only manipulating data and knowledge, but also in decision making by machines. Naturally, time-varying data and knowledge are required in Semantic Web applications to incorporate time and further reason about it. However, the original specifications of RDF and OWL do not include constructs for handling time-varying data and knowledge. For simplicity, RDF model is confined to binary predicates, hence some form of reification is needed to represent higher-arity predicates. To this date, there are many proposals extending RDF and OWL for handling temporal data and knowledge. They all focus on the valid time. In this paper, we examine each of these proposals and develop a taxonomy to classify them according to the form of reification employed: explicit reification or implicit reification. The implicit reification proposals are further divided into three sub-categories according to semantic constructs they use. Some of these proposals stay compliant to the RDF and OWL standards whereas others add new constructs to RDF model and SPARQL query language. Additionally, we compare these proposed models with respect to characteristics, such as their syntax and semantics, their compliance to RDF and OWL specifications, their need for additional objects, etc. The comparison provides a useful guideline for the researchers and practitioners of the Semantic Web in managing temporal data and knowledge.


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Author Biographies

Hsien-Tseng Wang, Department of Computer Science, The Graduate Center, The City University of New York, USA

Hsien-Tseng Wang received his BS and MS in Civil Engineering from the Central University in Taiwan. He also received an MBA from Baruch College, the City University of New York. He is currently a PhD candidate at the department of Computer Science at the Graduate Center, the City University of New York. Wang’s research interests include machine learning, semantic analytics, temporal aspects of the Semantic Web and simulations.

Abdullah Uz Tansel, Department of Computer Science, The Graduate Center, The City University of New York, USA , Paul H. Chook Department of Information Systems and Statistics, Baruch College, The City University of New York, USA, School of Engineering, Thammasat University Thailand

Abdullah Uz Tansel received his BS in management, and his MS and PhD degrees in computer science from the Middle East Technical University, in Ankara Turkey. He has also received his MBA degree at the University of Southern California. After being a faculty member at the Middle East Technical University, Dr. Tansel joined Baruch College, the City University of New York (CUNY) where he is currently a professor of information systems and also a professor of computer science at The Graduate Center of CUNY. Professor Tansel’s research focus is on temporal databases and he has made significant contributions in this field. He also headed the editorial board that published the first book on ‘Temporal Databases: Theory, Design, and Implementation’ (1993).

Dr. Tansel has a patent on adding temporality to RDF. His research interests are Database Management Systems, Temporal Databases, Semantic Web, and Blockchain Databases. Dr. Tansel has published many articles in the conferences and journals of the ACM, IEEE and other organizations. He is a frequent speaker on time in databases and blockchain as a database. He is also a member of the ACM and the IEEE Computer Society.


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