Named graphs, provenance and trust
WWW '05 Proceedings of the 14th international conference on World Wide Web
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
On explicit provenance management in RDF/S graphs
TAPP'09 First workshop on on Theory and practice of provenance
Scalable join processing on very large RDF graphs
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Querying Trust in RDF Data with tSPARQL
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
ACM Transactions on Computational Logic (TOCL)
A demonstration of SciDB: a science-oriented DBMS
Proceedings of the VLDB Endowment
Coloring RDF Triples to Capture Provenance
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Provenance in Databases
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
The Foundations for Provenance on the Web
Foundations and Trends in Web Science
On Provenance of Queries on Semantic Web Data
IEEE Internet Computing
The Open Provenance Model core specification (v1.1)
Future Generation Computer Systems
dipLODocus[RDF]: short and long-tail RDF analytics for massive webs of data
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
A general framework for representing, reasoning and querying with annotated Semantic Web data
Web Semantics: Science, Services and Agents on the World Wide Web
YAGO2: A spatially and temporally enhanced knowledge base from Wikipedia
Artificial Intelligence
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
Algebraic structures for capturing the provenance of SPARQL queries
Proceedings of the 16th International Conference on Database Theory
Transparency and Reliability in the Data Supply Chain
IEEE Internet Computing
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Given the heterogeneity of the data one can find on the Linked Data cloud, being able to trace back the provenance of query results is rapidly becoming a must-have feature of RDF systems. While provenance models have been extensively discussed in recent years, little attention has been given to the efficient implementation of provenance-enabled queries inside data stores. This paper introduces TripleProv: a new system extending a native RDF store to efficiently handle such queries. TripleProv implements two different storage models to physically co-locate lineage and instance data, and for each of them implements algorithms for tracing provenance at two granularity levels. In the following, we present the overall architecture of our system, its different lineage storage models, and the various query execution strategies we have implemented to efficiently answer provenance-enabled queries. In addition, we present the results of a comprehensive empirical evaluation of our system over two different datasets and workloads.