A product perspective on total data quality management
Communications of the ACM
Temporal and Real-Time Databases: A Survey
IEEE Transactions on Knowledge and Data Engineering
Data Quality in Web Information Systems
ER '02 Proceedings of the 21st International Conference on Conceptual Modeling
An ontology of time for the semantic web
ACM Transactions on Asian Language Information Processing (TALIP) - Special Issue on Temporal Information Processing
Duplicate Record Detection: A Survey
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering
Ontology Matching
Quality-driven information filtering using the WIQA policy framework
Web Semantics: Science, Services and Agents on the World Wide Web
Methodologies for data quality assessment and improvement
ACM Computing Surveys (CSUR)
Applied Temporal RDF: Efficient Temporal Querying of RDF Data with SPARQL
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
Discovering and Maintaining Links on the Web of Data
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Timely YAGO: harvesting, querying, and visualizing temporal knowledge from Wikipedia
Proceedings of the 13th International Conference on Extending Database Technology
When owl: sameAs isn't the same: an analysis of identity in linked data
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part I
Linked Data
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Since the Linked Data is continuously growing on the Web, the quality of overall data can rapidly degrade over time. The research proposed here deals with the quality assessment in the Linked Data and the temporal linking techniques. First, we conduct an in-depth study of appropriate dimensions and their respectively metrics by defining a data quality framework that evaluates, along these dimensions, linked published data on the Web. Second, since the assessment and improvement of the Linked Data quality such as accuracy or the resolution of heterogeneities is performed through record linkage techniques, we propose an extended technique that apply time in similarity computation which can improve over traditional linkage techniques. This paper describes the core problem, presents the proposed approach, reports on initial results, and lists planned future tasks.