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Complete Volume

**Published in:** LIPIcs, Volume 255, 26th International Conference on Database Theory (ICDT 2023)

LIPIcs, Volume 255, ICDT 2023, Complete Volume

Floris Geerts and Brecht Vandevoort. LIPIcs, Volume 255, ICDT 2023, Complete Volume. In 26th International Conference on Database Theory (ICDT 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 255, pp. 1-466, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)

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@Proceedings{geerts_et_al:LIPIcs.ICDT.2023, title = {{LIPIcs, Volume 255, ICDT 2023, Complete Volume}}, booktitle = {26th International Conference on Database Theory (ICDT 2023)}, pages = {1--466}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-270-9}, ISSN = {1868-8969}, year = {2023}, volume = {255}, editor = {Geerts, Floris and Vandevoort, Brecht}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2023}, URN = {urn:nbn:de:0030-drops-177414}, doi = {10.4230/LIPIcs.ICDT.2023}, annote = {Keywords: LIPIcs, Volume 255, ICDT 2023, Complete Volume} }

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Front Matter

**Published in:** LIPIcs, Volume 255, 26th International Conference on Database Theory (ICDT 2023)

Front Matter, Table of Contents, Preface, Conference Organization

Floris Geerts and Brecht Vandevoort. Front Matter, Table of Contents, Preface, Conference Organization. In 26th International Conference on Database Theory (ICDT 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 255, pp. 0:i-0:xvi, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)

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@InProceedings{geerts_et_al:LIPIcs.ICDT.2023.0, author = {Geerts, Floris and Vandevoort, Brecht}, title = {{Front Matter, Table of Contents, Preface, Conference Organization}}, booktitle = {26th International Conference on Database Theory (ICDT 2023)}, pages = {0:i--0:xvi}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-270-9}, ISSN = {1868-8969}, year = {2023}, volume = {255}, editor = {Geerts, Floris and Vandevoort, Brecht}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2023.0}, URN = {urn:nbn:de:0030-drops-177424}, doi = {10.4230/LIPIcs.ICDT.2023.0}, annote = {Keywords: Front Matter, Table of Contents, Preface, Conference Organization} }

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**Published in:** LIPIcs, Volume 155, 23rd International Conference on Database Theory (ICDT 2020)

We investigate when two graphs, represented by their adjacency matrices, can be distinguished by means of sentences formed in MATLANG, a matrix query language which supports a number of elementary linear algebra operators. When undirected graphs are concerned, and hence the adjacency matrices are real and symmetric, precise characterisations are in place when two graphs (i.e., their adjacency matrices) can be distinguished. Turning to directed graphs, one has to deal with asymmetric adjacency matrices. This complicates matters. Indeed, it requires to understand the more general problem of when two arbitrary matrices can be distinguished in MATLANG. We provide characterisations of the distinguishing power of MATLANG on real and complex matrices, and on adjacency matrices of directed graphs in particular. The proof techniques are a combination of insights from the symmetric matrix case and results from linear algebra and linear control theory.

Floris Geerts. When Can Matrix Query Languages Discern Matrices?. In 23rd International Conference on Database Theory (ICDT 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 155, pp. 12:1-12:18, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2020)

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@InProceedings{geerts:LIPIcs.ICDT.2020.12, author = {Geerts, Floris}, title = {{When Can Matrix Query Languages Discern Matrices?}}, booktitle = {23rd International Conference on Database Theory (ICDT 2020)}, pages = {12:1--12:18}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-139-9}, ISSN = {1868-8969}, year = {2020}, volume = {155}, editor = {Lutz, Carsten and Jung, Jean Christoph}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2020.12}, URN = {urn:nbn:de:0030-drops-119361}, doi = {10.4230/LIPIcs.ICDT.2020.12}, annote = {Keywords: matrix query languages, linear algebra, expressive power} }

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**Published in:** LIPIcs, Volume 127, 22nd International Conference on Database Theory (ICDT 2019)

Most graph query languages are rooted in logic. By contrast, in this paper we consider graph query languages rooted in linear algebra. More specifically, we consider MATLANG, a matrix query language recently introduced, in which some basic linear algebra functionality is supported. We investigate the problem of characterising equivalence of graphs, represented by their adjacency matrices, for various fragments of MATLANG. A complete picture is painted of the impact of the linear algebra operations in MATLANG on their ability to distinguish graphs.

Floris Geerts. On the Expressive Power of Linear Algebra on Graphs. In 22nd International Conference on Database Theory (ICDT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 127, pp. 7:1-7:19, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2019)

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@InProceedings{geerts:LIPIcs.ICDT.2019.7, author = {Geerts, Floris}, title = {{On the Expressive Power of Linear Algebra on Graphs}}, booktitle = {22nd International Conference on Database Theory (ICDT 2019)}, pages = {7:1--7:19}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-101-6}, ISSN = {1868-8969}, year = {2019}, volume = {127}, editor = {Barcelo, Pablo and Calautti, Marco}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2019.7}, URN = {urn:nbn:de:0030-drops-103093}, doi = {10.4230/LIPIcs.ICDT.2019.7}, annote = {Keywords: matrix query languages, graph queries, graph theory, logics} }

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**Published in:** LIPIcs, Volume 98, 21st International Conference on Database Theory (ICDT 2018)

We investigate the expressive power of MATLANG, a formal language for matrix manipulation based on common matrix operations and linear algebra. The language can be extended with the operation inv of inverting a matrix. In MATLANG + inv we can compute the transitive closure of directed graphs, whereas we show that this is not possible without inversion. Indeed we show that the basic language can be simulated in the relational algebra with arithmetic operations, grouping, and summation. We also consider an operation eigen for diagonalizing a matrix, which is defined so that different eigenvectors returned for a same eigenvalue are orthogonal. We show that inv can be expressed in MATLANG + eigen. We put forward the open question whether there are boolean queries about matrices, or generic queries about graphs, expressible in MATLANG + eigen but not in MATLANG + inv. The evaluation problem for MATLANG + eigen is shown to be complete for the complexity class Exists R.

Robert Brijder, Floris Geerts, Jan Van den Bussche, and Timmy Weerwag. On the Expressive Power of Query Languages for Matrices. In 21st International Conference on Database Theory (ICDT 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 98, pp. 10:1-10:17, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)

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@InProceedings{brijder_et_al:LIPIcs.ICDT.2018.10, author = {Brijder, Robert and Geerts, Floris and Van den Bussche, Jan and Weerwag, Timmy}, title = {{On the Expressive Power of Query Languages for Matrices}}, booktitle = {21st International Conference on Database Theory (ICDT 2018)}, pages = {10:1--10:17}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-063-7}, ISSN = {1868-8969}, year = {2018}, volume = {98}, editor = {Kimelfeld, Benny and Amsterdamer, Yael}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2018.10}, URN = {urn:nbn:de:0030-drops-86007}, doi = {10.4230/LIPIcs.ICDT.2018.10}, annote = {Keywords: matrix query languages, relational algebra with aggregates, query evaluation problem, graph queries} }

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Invited Talk

**Published in:** LIPIcs, Volume 48, 19th International Conference on Database Theory (ICDT 2016)

Large datasets introduce challenges to the scalability of query answering. Given a query Q and a dataset D, it is often prohibitively costly to compute the query answers Q(D) when D is big. To this end, one may want to use heuristics, "quick and dirty" algorithms which return approximate answers. However, in many applications it is a must to find exact query answers. So, how can we efficiently compute Q(D) when D is big or when we only have limited resources?
One idea is to find a small subset D_Q of D such that Q(D_Q)=Q(D) where the size of D_Q is independent of the size of the underlying dataset D. Intuitively, when such a D_Q can be found for a query Q, the query is said to be scale independent (Armbrust et al. 2011, Armbrust et al. 2013, Fan et al. 2014). Indeed, for answering such queries the size of the underlying database does not matter, i.e., query processing is independent of the scale of the database.
In this talk, I will survey various formalisms that enable large classes of queries to be scale independent. These formalisms primarily rely on the availability of access constraints, a combination of indexes and cardinality constraints, on the data (Fan et al. 15, Fan et al. 14). We will take a closer look at how, in the presence of such constraints, queries can often be compiled into efficient query plans that access a bounded amount data (Cao et al. 2014, Fan et al. 2015), and how these techniques relate to query processing in the presence of access patterns (Benedikt et al. 2015, Benedikt et al. 2014, Deutsch et al. 2007). Finally, we illustrate that scale independent queries are quite common in practice and that they indeed can be efficiently answered on big datasets when access constraints are present (Cao et al. 2015, Cao et al. 2014).

Floris Geerts. Scale Independence: Using Small Data to Answer Queries on Big Data (Invited Talk). In 19th International Conference on Database Theory (ICDT 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 48, pp. 2:1-2:2, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2016)

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@InProceedings{geerts:LIPIcs.ICDT.2016.2, author = {Geerts, Floris}, title = {{Scale Independence: Using Small Data to Answer Queries on Big Data}}, booktitle = {19th International Conference on Database Theory (ICDT 2016)}, pages = {2:1--2:2}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-002-6}, ISSN = {1868-8969}, year = {2016}, volume = {48}, editor = {Martens, Wim and Zeume, Thomas}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2016.2}, URN = {urn:nbn:de:0030-drops-57715}, doi = {10.4230/LIPIcs.ICDT.2016.2}, annote = {Keywords: Scale independence, Access constraints, Query processing} }

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