A1: Query-driven Validation of Distributed DAWs

Lößer, Ansgar; Schlecht, Max; Schintke, Florian; Witzke, Joel; Weidlich, Matthias; Scheuermann, Björn

Fast Min-ε Segmented Regression using Constant-Time Segment Merging Proceedings Article

In: Singh, Aarti; Fazel, Maryam; Hsu, Daniel; Lacoste-Julien, Simon; Berkenkamp, Felix; Maharaj, Tegan; Wagstaff, Kiri; Zhu, Jerry (Ed.): Proceedings of the 42nd International Conference on Machine Learning, pp. 40312–40327, PMLR, 2025.

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Gerlach, Luisa; Köppl, Tobias; Scherzinger, Stefanie; Schweikardt, Nicole; Zander, René

A Quantum-Leap into Schema Matching: Beyond 1-to-1 Matchings Proceedings Article

In: Association for Computing Machinery, New York, NY, USA, 2025.

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Sattler, Rebecca; Kleest-Meißner, Sarah; Lange, Steven; Schmid, Markus L.; Schweikardt, Nicole; Weidlich, Matthias

DISCES: Systematic Discovery of Event Stream Queries Journal Article

In: Proc. ACM Manag. Data, vol. 3, no. 1, pp. 32:1–32:26, 2025.

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Sattler, Rebecca; Kleest-Meißner, Sarah; Lange, Steven; Schmid, Markus L.; Schweikardt, Nicole; Weidlich, Matthias

Embracing Change: Incremental Updates of Discovered Event Queries Proceedings Article

In: Klettke, Meike; Schenkel, Ralf; Henrich, Andreas; Nicklas, Daniela; Schüle, Maximilian E.; Meyer-Wegener, Klaus (Ed.): Datenbanksysteme für Business, Technologie und Web (BTW 2025), 21. Fachtagung des GI-Fachbereichs ,,Datenbanken und Informationssysteme" (DBIS), 03.-07, März 2025, Bamberg, Germany, Proceedings, pp. 417–437, Gesellschaft für Informatik e.V., 2025.

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Frochaux, André; Kleest-Meißner, Sarah; Scheidt, Benjamin

Reaching New Limits: Discovery of Multi-Dimensional Disjunctive Subsequence-Queries with Intervals Proceedings Article

In: Klettke, Meike; Schenkel, Ralf; Henrich, Andreas; Nicklas, Daniela; Schüle, Maximilian E.; Meyer-Wegener, Klaus (Ed.): Datenbanksysteme für Business, Technologie und Web (BTW 2025), 21. Fachtagung des GI-Fachbereichs ,,Datenbanken und Informationssysteme" (DBIS), 03.-07, März 2025, Bamberg, Germany, Proceedings, pp. 49–70, Gesellschaft für Informatik e.V., 2025.

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Schintke, Florian; Belhajjame, Khalid; Mecquenem, Ninon De; Frantz, David; Guarino, Vanessa Emanuela; Hilbrich, Marcus; Lehmann, Fabian; Missier, Paolo; Sattler, Rebecca; Sparka, Jan Arne; Speckhard, Daniel T.; Stolte, Hermann; Vu, Anh Duc; Leser, Ulf

Validity constraints for data analysis workflows Journal Article

In: Future Generation Computer Systems, vol. 157, pp. 82–97, 2024, ISSN: 0167-739X.

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@article{SCHINTKE2024,

title = {Validity constraints for data analysis workflows},

author = {Florian Schintke and Khalid Belhajjame and Ninon De Mecquenem and David Frantz and Vanessa Emanuela Guarino and Marcus Hilbrich and Fabian Lehmann and Paolo Missier and Rebecca Sattler and Jan Arne Sparka and Daniel T. Speckhard and Hermann Stolte and Anh Duc Vu and Ulf Leser},

url = {https://www.sciencedirect.com/science/article/pii/S0167739X24001079},

doi = {https://doi.org/10.1016/j.future.2024.03.037},

issn = {0167-739X},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {Future Generation Computer Systems},

volume = {157},

pages = {82--97},

abstract = {Porting a scientific data analysis workflow (DAW) to a cluster infrastructure, a new software stack, or even only a new dataset with some notably different properties is often challenging. Despite the structured definition of the steps (tasks) and their interdependencies during a complex data analysis in the DAW specification, relevant assumptions may remain unspecified and implicit. Such hidden assumptions often lead to crashing tasks without a reasonable error message, poor performance in general, non-terminating executions, or silent wrong results of the DAW, to name only a few possible consequences. Searching for the causes of such errors and drawbacks in a distributed compute cluster managed by a complex infrastructure stack, where DAWs for large datasets typically are executed, can be tedious and time-consuming. We propose validity constraints (VCs) as a new concept for DAW languages to alleviate this situation. A VC is a constraint specifying logical conditions that must be fulfilled at certain times for DAW executions to be valid. When defined together with a DAW, VCs help to improve the portability, adaptability, and reusability of DAWs by making implicit assumptions explicit. Once specified, VCs can be controlled automatically by the DAW infrastructure, and violations can lead to meaningful error messages and graceful behaviour (e.g., termination or invocation of repair mechanisms). We provide a broad list of possible VCs, classify them along multiple dimensions, and compare them to similar concepts one can find in related fields. We also provide a proof-of-concept implementation for the workflow system Nextflow.},

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pubstate = {published},

tppubtype = {article}

}

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Frochaux, André; Kleest-Meißner, Sarah

Puzzling over Subsequence-Query Extensions: Disjunction and Generalised Gaps Proceedings Article

In: Kimelfeld, Benny; Martinez, Maria Vanina; Angles, Renzo (Ed.): Proceedings of the 15th Alberto Mendelzon International Workshop on Foundations of Data Management {(AMW} 2023), Santiago de Chile, Chile, May 22-26, 2023, CEUR-WS.org, 2023.

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Kleest-Meißner, Sarah; Sattler, Rebecca; Schmid, Markus L.; Schweikardt, Nicole; Weidlich, Matthias

Discovering Multi-Dimensional Subsequence Queries from Traces - From Theory to Practice Proceedings Article

In: König-Ries, Birgitta; Scherzinger, Stefanie; Lehner, Wolfgang; Vossen, Gottfried (Ed.): Datenbanksysteme für Business, Technologie und Web (BTW 2023), 20. Fachtagung des GI-Fachbereichs ,,Datenbanken und Informationssysteme" (DBIS), 06.-10, März 2023, Dresden, Germany, Proceedings, pp. 511-533, Gesellschaft für Informatik e.V., 2023.

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@inproceedings{DBLP:conf/btw/Kleest-Meissner23,

title = {Discovering Multi-Dimensional Subsequence Queries from Traces - From Theory to Practice},

author = {Sarah Kleest-Meißner and Rebecca Sattler and Markus L. Schmid and Nicole Schweikardt and Matthias Weidlich},

editor = {Birgitta König-Ries and Stefanie Scherzinger and Wolfgang Lehner and Gottfried Vossen},

doi = {10.18420/BTW2023-24},

year  = {2023},

date = {2023-02-23},

urldate = {2023-02-23},

booktitle = {Datenbanksysteme für Business, Technologie und Web (BTW 2023), 20. Fachtagung des GI-Fachbereichs ,,Datenbanken und Informationssysteme" (DBIS), 06.-10, März 2023, Dresden, Germany, Proceedings},

volume = {P-331},

pages = {511-533},

publisher = {Gesellschaft für Informatik e.V.},

series = {LNI},

abstract = {Subsequence-queries with wildcards and gap-size constraints (swg-queries, for short) are an expressive model for sequence data, in which queries are described by patterns over an alphabet of variables and types, along with a global window size and a number of gap-size constraints. They are evaluated over a trace, i.e., a sequence of types, by replacing variables by single types, while satisfying the window and the gap-size constraints. Kleest-Meißner et al. (Proc. ICDT 2022) formalised the task of discovering an swg-query that describes best a given sample consisting of a finite number of traces, and developed a discovery algorithm solving this task. However, in practical application scenarios, traces are often multi-dimensional, i.e., a trace corresponds to a sequence of tuples of types, which renders the existing technique inapplicable.In this paper, we lift the notion of swg-queries to such a multi-dimensional setting, thereby enlarging the applicability of the query model and the techniques for query discovery. We introduce a mapping between one-dimensional and multi-dimensional sequence data, such that a multi-dimensional trace matches a multi-dimensional query if and only if the corresponding one-dimensional trace matches the corresponding one-dimensional query. We complement our formal results with a description of our prototypical implementation of query discovery for multi-dimensional sequence data. Results from evaluation experiments with real-world data indicate feasibility of our approach.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

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Schintke, Florian; De Mecquenem, Ninon; Frantz, David; Guarino, Vanessa Emanuela; Hilbrich, Marcus; Lehmann, Fabian; Sattler, Rebecca; Sparka, Jan Arne; Speckhard, Daniel T.; Stolte, Hermann; Vu, Anh Duc; Leser, Ulf

Validity Constraints for Data Analysis Workflows Miscellaneous

2023.

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Kleest-Meißner, Sarah; Sattler, Rebecca; Schmid, Markus L.; Schweikardt, Nicole; Weidlich, Matthias

Discovering Event Queries from Traces: Laying Foundations for Subsequence-Queries with Wildcards and Gap-Size Constraints Proceedings Article

In: Olteanu, Dan; Vortmeier, Nils (Ed.): 25th International Conference on Database Theory, ICDT 2022, March 29 to April 1, 2022, Edinburgh, UK (Virtual Conference), pp. 18:1–18:21, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022.

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