=Paper=
{{Paper
|id=Vol-3801/invited1
|storemode=property
|title=Explaining Answers to Datalog Queries (Invited Talk)
|pdfUrl=https://ceur-ws.org/Vol-3801/invited1.pdf
|volume=Vol-3801
|authors=Andreas Pieris
|dblpUrl=https://dblp.org/rec/conf/datalog/Pieris24
}}
==Explaining Answers to Datalog Queries (Invited Talk)==
<pdf width="1500px">https://ceur-ws.org/Vol-3801/invited1.pdf</pdf>
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                         Explaining Answers to Datalog Queries (Invited Talk)
                         Andreas Pieris
                         University of Cyprus, Cyprus
                         University of Edinburgh, UK


                                      Abstract
                                      Datalog emerged in the 1970s as a prominent logic-based query language from Logic Programming and has
                                      found numerous applications over the years. It essentially extends the language of unions of conjunctive queries,
                                      which corresponds to the select-project-join-union fragment of Relational Algebra, with the important feature of
                                      recursion much needed to express some natural queries. As for every other query language, explaining why a
                                      result to a Datalog query is obtained is an essential task towards explainable and transparent query evaluation.
                                      Several natural explainability notions for Datalog queries have been proposed in the literature that can be captured
                                      via the unifying framework of semiring provenance. The goal of this invited talk is to give an overview of those
                                      explainability notions and present very recent results concerning their computational complexity, as well as
                                      discussing interesting open problems. We will also discuss the possibility of devising algorithms for explaining
                                      answers to Datalog queries based on sophisticated SAT solvers.
                                      This talk is based on joint work with Marco Calautti, Ester Livshits and Markus Schneider.




                          Datalog 2.0 2024: 5th International Workshop on the Resurgence of Datalog in Academia and Industry, October 11, 2024, Dallas,
                          Texas, USA
                          $ apieris@inf.ed.ac.uk.it (A. Pieris)
                                   © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).


CEUR
                  ceur-ws.org
Workshop      ISSN 1613-0073
Proceedings

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