Divide and Conquer the EmpiRE: A Community-Maintainable Knowledge Graph of Empirical Research in Requirements Engineering

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

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  • Technische Informationsbibliothek (TIB) Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
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OriginalspracheEnglisch
Titel des Sammelwerks2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023
Herausgeber (Verlag)IEEE Computer Society
ISBN (elektronisch)9781665452236
ISBN (Print)978-1-6654-5224-3
PublikationsstatusVeröffentlicht - 2023
Veranstaltung17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023 - New Orleans, USA / Vereinigte Staaten
Dauer: 26 Okt. 202327 Okt. 2023

Publikationsreihe

NameInternational Symposium on Empirical Software Engineering and Measurement
ISSN (Print)1949-3770
ISSN (elektronisch)1949-3789

Abstract

[Background.] Empirical research in requirements engineering (RE) is a constantly evolving topic, with a growing number of publications. Several papers address this topic using literature reviews to provide a snapshot of its 'current' state and evolution. However, these papers have never built on or updated earlier ones, resulting in overlap and redundancy. The underlying problem is the unavailability of data from earlier works. Researchers need technical infrastructures to conduct sustainable literature reviews. [Aims.] We examine the use of the Open Research Knowledge Graph (ORKG) as such an infrastructure to build and publish an initial Knowledge Graph of Empirical research in RE (KG-EmpiRE) whose data is openly available. Our long-term goal is to continuously maintain KG-EmpiRE with the research community to synthesize a comprehensive, up-to-date, and long-term available overview of the state and evolution of empirical research in RE. [Method.] We conduct a literature review using the ORKG to build and publish KG-EmpiRE which we evaluate against competency questions derived from a published vision of empirical research in software (requirements) engineering for 2020-2025. [Results.] From 570 papers of the IEEE International Requirements Engineering Conference (2000-2022), we extract and analyze data on the reported empirical research and answer 16 out of 77 competency questions. These answers show a positive development towards the vision, but also the need for future improvements. [Conclusions.] The ORKG is a ready-to-use and advanced infrastructure to organize data from literature reviews as knowledge graphs. The resulting knowledge graphs make the data openly available and maintainable by research communities, enabling sustainable literature reviews.

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Divide and Conquer the EmpiRE: A Community-Maintainable Knowledge Graph of Empirical Research in Requirements Engineering. / Karras, Oliver; Wernlein, Felix; Klunder, Jil et al.
2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023. IEEE Computer Society, 2023. (International Symposium on Empirical Software Engineering and Measurement).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Karras, O, Wernlein, F, Klunder, J & Auer, S 2023, Divide and Conquer the EmpiRE: A Community-Maintainable Knowledge Graph of Empirical Research in Requirements Engineering. in 2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023. International Symposium on Empirical Software Engineering and Measurement, IEEE Computer Society, 17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023, New Orleans, USA / Vereinigte Staaten, 26 Okt. 2023. https://doi.org/10.48550/arXiv.2306.16791, https://doi.org/10.15488/16378, https://doi.org/10.1109/ESEM56168.2023.10304795
Karras, O., Wernlein, F., Klunder, J., & Auer, S. (2023). Divide and Conquer the EmpiRE: A Community-Maintainable Knowledge Graph of Empirical Research in Requirements Engineering. In 2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023 (International Symposium on Empirical Software Engineering and Measurement). IEEE Computer Society. https://doi.org/10.48550/arXiv.2306.16791, https://doi.org/10.15488/16378, https://doi.org/10.1109/ESEM56168.2023.10304795
Karras O, Wernlein F, Klunder J, Auer S. Divide and Conquer the EmpiRE: A Community-Maintainable Knowledge Graph of Empirical Research in Requirements Engineering. in 2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023. IEEE Computer Society. 2023. (International Symposium on Empirical Software Engineering and Measurement). doi: 10.48550/arXiv.2306.16791, 10.15488/16378, 10.1109/ESEM56168.2023.10304795
Karras, Oliver ; Wernlein, Felix ; Klunder, Jil et al. / Divide and Conquer the EmpiRE : A Community-Maintainable Knowledge Graph of Empirical Research in Requirements Engineering. 2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023. IEEE Computer Society, 2023. (International Symposium on Empirical Software Engineering and Measurement).
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title = "Divide and Conquer the EmpiRE: A Community-Maintainable Knowledge Graph of Empirical Research in Requirements Engineering",
abstract = "[Background.] Empirical research in requirements engineering (RE) is a constantly evolving topic, with a growing number of publications. Several papers address this topic using literature reviews to provide a snapshot of its 'current' state and evolution. However, these papers have never built on or updated earlier ones, resulting in overlap and redundancy. The underlying problem is the unavailability of data from earlier works. Researchers need technical infrastructures to conduct sustainable literature reviews. [Aims.] We examine the use of the Open Research Knowledge Graph (ORKG) as such an infrastructure to build and publish an initial Knowledge Graph of Empirical research in RE (KG-EmpiRE) whose data is openly available. Our long-term goal is to continuously maintain KG-EmpiRE with the research community to synthesize a comprehensive, up-to-date, and long-term available overview of the state and evolution of empirical research in RE. [Method.] We conduct a literature review using the ORKG to build and publish KG-EmpiRE which we evaluate against competency questions derived from a published vision of empirical research in software (requirements) engineering for 2020-2025. [Results.] From 570 papers of the IEEE International Requirements Engineering Conference (2000-2022), we extract and analyze data on the reported empirical research and answer 16 out of 77 competency questions. These answers show a positive development towards the vision, but also the need for future improvements. [Conclusions.] The ORKG is a ready-to-use and advanced infrastructure to organize data from literature reviews as knowledge graphs. The resulting knowledge graphs make the data openly available and maintainable by research communities, enabling sustainable literature reviews.",
keywords = "empirical research, infrastructure, Knowledge graph, literature review, requirements engineering, sustainability",
author = "Oliver Karras and Felix Wernlein and Jil Klunder and S{\"o}ren Auer",
note = "Funding Information: ACKNOWLEDGMENT The authors thank the Federal Government, the Heads of Government of the L{\"a}nder, as well as the Joint Science Conference (GWK), for their funding and support within the NFDI4Ing and NFDI4DataScience consortia. This work was funded by the German Research Foundation (DFG) - project numbers 442146713 and 460234259, by the European Research Council for the project ScienceGRAPH (Grant agreement ID: 819536), and by the TIB - Leibniz Information Centre for Science and Technology. ; 17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023 ; Conference date: 26-10-2023 Through 27-10-2023",
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series = "International Symposium on Empirical Software Engineering and Measurement",
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Download

TY - GEN

T1 - Divide and Conquer the EmpiRE

T2 - 17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023

AU - Karras, Oliver

AU - Wernlein, Felix

AU - Klunder, Jil

AU - Auer, Sören

N1 - Funding Information: ACKNOWLEDGMENT The authors thank the Federal Government, the Heads of Government of the Länder, as well as the Joint Science Conference (GWK), for their funding and support within the NFDI4Ing and NFDI4DataScience consortia. This work was funded by the German Research Foundation (DFG) - project numbers 442146713 and 460234259, by the European Research Council for the project ScienceGRAPH (Grant agreement ID: 819536), and by the TIB - Leibniz Information Centre for Science and Technology.

PY - 2023

Y1 - 2023

N2 - [Background.] Empirical research in requirements engineering (RE) is a constantly evolving topic, with a growing number of publications. Several papers address this topic using literature reviews to provide a snapshot of its 'current' state and evolution. However, these papers have never built on or updated earlier ones, resulting in overlap and redundancy. The underlying problem is the unavailability of data from earlier works. Researchers need technical infrastructures to conduct sustainable literature reviews. [Aims.] We examine the use of the Open Research Knowledge Graph (ORKG) as such an infrastructure to build and publish an initial Knowledge Graph of Empirical research in RE (KG-EmpiRE) whose data is openly available. Our long-term goal is to continuously maintain KG-EmpiRE with the research community to synthesize a comprehensive, up-to-date, and long-term available overview of the state and evolution of empirical research in RE. [Method.] We conduct a literature review using the ORKG to build and publish KG-EmpiRE which we evaluate against competency questions derived from a published vision of empirical research in software (requirements) engineering for 2020-2025. [Results.] From 570 papers of the IEEE International Requirements Engineering Conference (2000-2022), we extract and analyze data on the reported empirical research and answer 16 out of 77 competency questions. These answers show a positive development towards the vision, but also the need for future improvements. [Conclusions.] The ORKG is a ready-to-use and advanced infrastructure to organize data from literature reviews as knowledge graphs. The resulting knowledge graphs make the data openly available and maintainable by research communities, enabling sustainable literature reviews.

AB - [Background.] Empirical research in requirements engineering (RE) is a constantly evolving topic, with a growing number of publications. Several papers address this topic using literature reviews to provide a snapshot of its 'current' state and evolution. However, these papers have never built on or updated earlier ones, resulting in overlap and redundancy. The underlying problem is the unavailability of data from earlier works. Researchers need technical infrastructures to conduct sustainable literature reviews. [Aims.] We examine the use of the Open Research Knowledge Graph (ORKG) as such an infrastructure to build and publish an initial Knowledge Graph of Empirical research in RE (KG-EmpiRE) whose data is openly available. Our long-term goal is to continuously maintain KG-EmpiRE with the research community to synthesize a comprehensive, up-to-date, and long-term available overview of the state and evolution of empirical research in RE. [Method.] We conduct a literature review using the ORKG to build and publish KG-EmpiRE which we evaluate against competency questions derived from a published vision of empirical research in software (requirements) engineering for 2020-2025. [Results.] From 570 papers of the IEEE International Requirements Engineering Conference (2000-2022), we extract and analyze data on the reported empirical research and answer 16 out of 77 competency questions. These answers show a positive development towards the vision, but also the need for future improvements. [Conclusions.] The ORKG is a ready-to-use and advanced infrastructure to organize data from literature reviews as knowledge graphs. The resulting knowledge graphs make the data openly available and maintainable by research communities, enabling sustainable literature reviews.

KW - empirical research

KW - infrastructure

KW - Knowledge graph

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DO - 10.48550/arXiv.2306.16791

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SN - 978-1-6654-5224-3

T3 - International Symposium on Empirical Software Engineering and Measurement

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Y2 - 26 October 2023 through 27 October 2023

ER -

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