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Native Provenance Computation for Federated and Non-Federated SPARQL Queries

Authors: Zubaria Asma, Daniel Hernández, Luis Galárraga, Giorgos Flouris, Irini Fundulaki, and Katja Hose

Published in: TGDK, Volume 4, Issue 1 (2026). Transactions on Graph Data and Knowledge, Volume 4, Issue 1

Abstract

The popularity of knowledge graphs (KGs) owes credit to their flexible data model, which is suitable for data integration from multiple sources. Several KG-based applications, such as trust assessment, view maintenance, or data valuation on dynamic data, rely on the ability to compute provenance explanations for query results. This need becomes more urgent in federated query processing systems, which allow the online consumption of heterogeneous and decentralized Web data. However, the problem of computing and interacting with provenance has received little attention, especially in the federated setting. On those grounds, this paper introduces the NPCS (Native Provenance Computation for SPARQL) approach, and its federated variant Fed-NPCS, that compute provenance for SPARQL query results. Both approaches build upon spm-semirings to annotate the results of monotonic and non-monotonic SPARQL queries with their provenance. Due to their reliance on query rewriting techniques, the approaches are directly applicable to already deployed SPARQL engines and federations using different reification schemes, including RDF-star. Our experimental evaluation shows that our novel query rewriting approach brings significant run-time improvements w.r.t. the state-of-the-art across both centralized and federated settings. In centralized settings, our tests on two popular SPARQL engines (GraphDB and Stardog) reveal substantial runtime gains over existing query rewriting solutions, enabling scalability to RDF graphs with billions of triples. In federated settings, our experiments on the FedShop benchmark with GraphDB show the viability of Fed-NPCS for federations with up to 200 sources.

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Zubaria Asma, Daniel Hernández, Luis Galárraga, Giorgos Flouris, Irini Fundulaki, and Katja Hose. Native Provenance Computation for Federated and Non-Federated SPARQL Queries. In Transactions on Graph Data and Knowledge (TGDK), Volume 4, Issue 1, pp. 4:1-4:43, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@Article{asma_et_al:TGDK.4.1.4,
  author =	{Asma, Zubaria and Hern\'{a}ndez, Daniel and Gal\'{a}rraga, Luis and Flouris, Giorgos and Fundulaki, Irini and Hose, Katja},
  title =	{{Native Provenance Computation for Federated and Non-Federated SPARQL Queries}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{4:1--4:43},
  ISSN =	{2942-7517},
  year =	{2026},
  volume =	{4},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.4.1.4},
  URN =		{urn:nbn:de:0030-drops-259642},
  doi =		{10.4230/TGDK.4.1.4},
  annote =	{Keywords: native provenance computation, federated SPARQL queries, data provenance, NPCS, Fed-NPCS}
}

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DOI: 10.4230/LIPIcs.ICLP.2011.16

Evolution of Ontologies using ASP

Authors: Max Ostrowski, Giorgos Flouris, Torsten Schaub, and Grigoris Antoniou

Published in: LIPIcs, Volume 11, Technical Communications of the 27th International Conference on Logic Programming (ICLP'11) (2011)

Abstract

RDF/S ontologies are often used in e-science to express domain knowledge regarding the respective field of investigation (e.g., cultural informatics, bioinformatics etc). Such ontologies need to change often to reflect the latest scientific understanding on the domain at hand, and are usually associated with constraints expressed using various declarative formalisms to express domain-specific requirements, such as cardinality or acyclicity constraints. Addressing the evolution of ontologies in the presence of ontological constraints imposes extra difficulties, because it forces us to respect the associated constraints during evolution. While these issues were addressed in previous work, this is the first work to examine how ASP techniques can be applied to model and implement the evolution process. ASP was chosen for its advantages in terms of a principled, rather than ad hoc implementation, its modularity and flexibility, and for being a state-of-the-art technique to tackle hard combinatorial problems. In particular, our approach consists in providing a general translation of the problem into ASP, thereby reducing it to an instance of an ASP program that can be solved by an ASP solver. Our experiments are promising, even for large ontologies, and also show that the scalability of the approach depends on the morphology of the input.

Cite as

Max Ostrowski, Giorgos Flouris, Torsten Schaub, and Grigoris Antoniou. Evolution of Ontologies using ASP. In Technical Communications of the 27th International Conference on Logic Programming (ICLP'11). Leibniz International Proceedings in Informatics (LIPIcs), Volume 11, pp. 16-27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)

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@InProceedings{ostrowski_et_al:LIPIcs.ICLP.2011.16,
  author =	{Ostrowski, Max and Flouris, Giorgos and Schaub, Torsten and Antoniou, Grigoris},
  title =	{{Evolution of Ontologies using ASP}},
  booktitle =	{Technical Communications of the 27th International Conference on Logic Programming (ICLP'11)},
  pages =	{16--27},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-31-6},
  ISSN =	{1868-8969},
  year =	{2011},
  volume =	{11},
  editor =	{Gallagher, John P. and Gelfond, Michael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICLP.2011.16},
  URN =		{urn:nbn:de:0030-drops-31747},
  doi =		{10.4230/LIPIcs.ICLP.2011.16},
  annote =	{Keywords: Ontology evolution, Evolution in the presence of constraints, incremental ASP application}
}

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Documents authored by Flouris, Giorgos

Native Provenance Computation for Federated and Non-Federated SPARQL Queries

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Evolution of Ontologies using ASP

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