Practical Lineage Tracing in Data Warehouses
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
CS AKTive space: representing computer science in the semantic web
Proceedings of the 13th international conference on World Wide Web
A proof markup language for semantic web services
Information Systems - Special issue: The semantic web and web services
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Management of Meta Knowledge for RDF Repositories
ICSC '07 Proceedings of the International Conference on Semantic Computing
Explaining answers from the Semantic Web: the Inference Web approach
Web Semantics: Science, Services and Agents on the World Wide Web
Semantics and complexity of SPARQL
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Explaining conclusions from diverse knowledge sources
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Reasoning Web
An Approach to Description Logic with Support for Propositional Attitudes and Belief Fusion
Uncertainty Reasoning for the Semantic Web I
Metalevel information in ontology-based applications
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Towards Lightweight and Robust Large Scale Emergent Knowledge Processing
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Biomedical publication knowledge acquisition, processing and dissemination with CORAAL
OTM'10 Proceedings of the 2010 international conference on On the move to meaningful internet systems: Part II
Don't like RDF reification?: making statements about statements using singleton property
Proceedings of the 23rd international conference on World wide web
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The Semantic Web is based on accessing and reusing RDF data from many different sources, which one may assign different levels of authority and credibility. Existing Semantic Web query languages, like SPARQL, have targeted the retrieval, combination and reuse of facts, but have so far ignored all aspects of meta knowledge, such as origins, authorship, recency or certainty of data, to name but a few. In this paper, we present an original, generic, formalized and implemented approach for managing many dimensions of meta knowledge, like source, authorship, certainty and others. The approach re-uses existing RDF modeling possibilities in order to represent meta knowledge. Then, it extends SPARQL query processing in such a way that given a SPARQL query for data, one may request meta knowledge without modifying the original query. Thus, our approach achieves highly flexible and automatically coordinated querying for data and meta knowledge, while completely separating the two areas of concern.