5 Search Results for "Böhlen, Michael H."

Document
DOI: 10.4230/LIPIcs.TIME.2025.9
Temporal GraphQL: A Tree Grammar Approach

Authors: Curtis E. Dyreson and Bishal Sarkar

Published in: LIPIcs, Volume 355, 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)

Abstract
This paper presents a novel system, called Temporal GraphQL, for supporting temporal data in web services. A temporal web service is a service that provides a temporal view of data, that is, a view of the current data as well as past or future states of the data. Capturing the history of the data is important in data forensics, data auditing, and subscriptions, where an application continuously reads data. GraphQL is a technology for improving the development and management of web services. Originally developed by Facebook and widely used in industry, GraphQL is a query language for web services. This paper introduces Temporal GraphQL. We show how to use tree grammars to model GraphQL schemas, data, and queries, and propose temporal tree grammars to model Temporal GraphQL. We extend GraphQL with temporal snapshot, slice, and delta operators. To the best of our knowledge, this is the first work on Temporal GraphQL and temporal tree grammars.
Cite as

Curtis E. Dyreson and Bishal Sarkar. Temporal GraphQL: A Tree Grammar Approach. In 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 355, pp. 9:1-9:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{dyreson_et_al:LIPIcs.TIME.2025.9,
  author =	{Dyreson, Curtis E. and Sarkar, Bishal},
  title =	{{Temporal GraphQL: A Tree Grammar Approach}},
  booktitle =	{32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)},
  pages =	{9:1--9:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-401-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{355},
  editor =	{Vidal, Thierry and Wa{\l}\k{e}ga, Przemys{\l}aw Andrzej},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2025.9},
  URN =		{urn:nbn:de:0030-drops-244556},
  doi =		{10.4230/LIPIcs.TIME.2025.9},
  annote =	{Keywords: Temporal databases, temporal queries, GraphQL, web services}
}
Document
DOI: 10.4230/LIPIcs.ICDT.2025.31
On Deciding the Data Complexity of Answering Linear Monadic Datalog Queries with LTL Operators

Authors: Alessandro Artale, Anton Gnatenko, Vladislav Ryzhikov, and Michael Zakharyaschev

Published in: LIPIcs, Volume 328, 28th International Conference on Database Theory (ICDT 2025)

Abstract
Our concern is the data complexity of answering linear monadic datalog queries whose atoms in the rule bodies can be prefixed by operators of linear temporal logic LTL. We first observe that, for data complexity, answering any connected query with operators ○/○- (at the next/previous moment) is either in AC⁰, or in ACC⁰\AC⁰, or NC¹-complete, or L-hard and in NL. Then we show that the problem of deciding L-hardness of answering such queries is PSpace-complete, while checking membership in the classes AC⁰ and ACC⁰ as well as NC¹-completeness can be done in ExpSpace. Finally, we prove that membership in AC⁰ or in ACC⁰, NC¹-completeness, and L-hardness are undecidable for queries with operators ◇/◇- (sometime in the future/past) provided that NC¹ ≠ NL and L ≠ NL.
Cite as

Alessandro Artale, Anton Gnatenko, Vladislav Ryzhikov, and Michael Zakharyaschev. On Deciding the Data Complexity of Answering Linear Monadic Datalog Queries with LTL Operators. In 28th International Conference on Database Theory (ICDT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 328, pp. 31:1-31:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{artale_et_al:LIPIcs.ICDT.2025.31,
  author =	{Artale, Alessandro and Gnatenko, Anton and Ryzhikov, Vladislav and Zakharyaschev, Michael},
  title =	{{On Deciding the Data Complexity of Answering Linear Monadic Datalog Queries with LTL Operators}},
  booktitle =	{28th International Conference on Database Theory (ICDT 2025)},
  pages =	{31:1--31:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-364-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{328},
  editor =	{Roy, Sudeepa and Kara, Ahmet},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2025.31},
  URN =		{urn:nbn:de:0030-drops-229723},
  doi =		{10.4230/LIPIcs.ICDT.2025.31},
  annote =	{Keywords: Linear monadic datalog, linear temporal logic, data complexity}
}
Document
Survey
DOI: 10.4230/TGDK.1.1.11
How Does Knowledge Evolve in Open Knowledge Graphs?

Authors: Axel Polleres, Romana Pernisch, Angela Bonifati, Daniele Dell'Aglio, Daniil Dobriy, Stefania Dumbrava, Lorena Etcheverry, Nicolas Ferranti, Katja Hose, Ernesto Jiménez-Ruiz, Matteo Lissandrini, Ansgar Scherp, Riccardo Tommasini, and Johannes Wachs

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
Openly available, collaboratively edited Knowledge Graphs (KGs) are key platforms for the collective management of evolving knowledge. The present work aims t o provide an analysis of the obstacles related to investigating and processing specifically this central aspect of evolution in KGs. To this end, we discuss (i) the dimensions of evolution in KGs, (ii) the observability of evolution in existing, open, collaboratively constructed Knowledge Graphs over time, and (iii) possible metrics to analyse this evolution. We provide an overview of relevant state-of-the-art research, ranging from metrics developed for Knowledge Graphs specifically to potential methods from related fields such as network science. Additionally, we discuss technical approaches - and their current limitations - related to storing, analysing and processing large and evolving KGs in terms of handling typical KG downstream tasks.
Cite as

Axel Polleres, Romana Pernisch, Angela Bonifati, Daniele Dell'Aglio, Daniil Dobriy, Stefania Dumbrava, Lorena Etcheverry, Nicolas Ferranti, Katja Hose, Ernesto Jiménez-Ruiz, Matteo Lissandrini, Ansgar Scherp, Riccardo Tommasini, and Johannes Wachs. How Does Knowledge Evolve in Open Knowledge Graphs?. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 11:1-11:59, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{polleres_et_al:TGDK.1.1.11,
  author =	{Polleres, Axel and Pernisch, Romana and Bonifati, Angela and Dell'Aglio, Daniele and Dobriy, Daniil and Dumbrava, Stefania and Etcheverry, Lorena and Ferranti, Nicolas and Hose, Katja and Jim\'{e}nez-Ruiz, Ernesto and Lissandrini, Matteo and Scherp, Ansgar and Tommasini, Riccardo and Wachs, Johannes},
  title =	{{How Does Knowledge Evolve in Open Knowledge Graphs?}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{11:1--11:59},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.11},
  URN =		{urn:nbn:de:0030-drops-194855},
  doi =		{10.4230/TGDK.1.1.11},
  annote =	{Keywords: KG evolution, temporal KG, versioned KG, dynamic KG}
}
Document
Invited Talk
DOI: 10.4230/LIPIcs.TIME.2019.1
Computing the Fourier Transformation over Temporal Data Streams (Invited Talk)

Authors: Michael H. Böhlen and Muhammad Saad

Published in: LIPIcs, Volume 147, 26th International Symposium on Temporal Representation and Reasoning (TIME 2019)

Abstract
In radio astronomy the sky is continuously scanned to collect frequency information about celestial objects. The inverse 2D Fourier transformation is used to generate images of the sky from the collected frequency information. We propose an algorithm that incrementally refines images by processing frequency information as it arrives in a temporal data stream. A direct implementation of the refinement with the discrete Fourier transformation requires O(N^2) complex multiplications to process an element of the stream. We propose a new algorithm that avoids recomputations and only requires O(N) complex multiplications.
Cite as

Michael H. Böhlen and Muhammad Saad. Computing the Fourier Transformation over Temporal Data Streams (Invited Talk). In 26th International Symposium on Temporal Representation and Reasoning (TIME 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 147, pp. 1:1-1:4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{bohlen_et_al:LIPIcs.TIME.2019.1,
  author =	{B\"{o}hlen, Michael H. and Saad, Muhammad},
  title =	{{Computing the Fourier Transformation over Temporal Data Streams}},
  booktitle =	{26th International Symposium on Temporal Representation and Reasoning (TIME 2019)},
  pages =	{1:1--1:4},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-127-6},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{147},
  editor =	{Gamper, Johann and Pinchinat, Sophie and Sciavicco, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2019.1},
  URN =		{urn:nbn:de:0030-drops-113595},
  doi =		{10.4230/LIPIcs.TIME.2019.1},
  annote =	{Keywords: Data streams, Fourier transform, time-varying data}
}
Document
Invited Paper
DOI: 10.4230/LIPIcs.TIME.2018.2
Database Technology for Processing Temporal Data (Invited Paper)

Authors: Michael H. Böhlen, Anton Dignös, Johann Gamper, and Christian S. Jensen

Published in: LIPIcs, Volume 120, 25th International Symposium on Temporal Representation and Reasoning (TIME 2018)

Abstract
Despite the ubiquity of temporal data and considerable research on processing such data, database systems largely remain designed for processing the current state of some modeled reality. More recently, we have seen an increasing interest in processing historical or temporal data. The SQL:2011 standard introduced some temporal features, and commercial database management systems have started to offer temporal functionalities in a step-by-step manner. There has also been a proposal for a more fundamental and comprehensive solution for sequenced temporal queries, which allows a tight integration into relational database systems, thereby taking advantage of existing query optimization and evaluation technologies. New challenges for processing temporal data arise with multiple dimensions of time and the increasing amounts of data, including time series data that represent a special kind of temporal data.
Cite as

Michael H. Böhlen, Anton Dignös, Johann Gamper, and Christian S. Jensen. Database Technology for Processing Temporal Data (Invited Paper). In 25th International Symposium on Temporal Representation and Reasoning (TIME 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 120, pp. 2:1-2:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{bohlen_et_al:LIPIcs.TIME.2018.2,
  author =	{B\"{o}hlen, Michael H. and Dign\"{o}s, Anton and Gamper, Johann and Jensen, Christian S.},
  title =	{{Database Technology for Processing Temporal Data}},
  booktitle =	{25th International Symposium on Temporal Representation and Reasoning (TIME 2018)},
  pages =	{2:1--2:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-089-7},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{120},
  editor =	{Alechina, Natasha and N{\o}rv\r{a}g, Kjetil and Penczek, Wojciech},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2018.2},
  URN =		{urn:nbn:de:0030-drops-97674},
  doi =		{10.4230/LIPIcs.TIME.2018.2},
  annote =	{Keywords: Temporal databases, temporal query processing, sequenced semantics, SQL}
}
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