Details
| Original language | English |
|---|---|
| Title of host publication | 2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023 |
| Publisher | IEEE Computer Society |
| ISBN (electronic) | 9781665452236 |
| ISBN (print) | 978-1-6654-5224-3 |
| Publication status | Published - 2023 |
| Event | 17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023 - New Orleans, United States Duration: 26 Oct 2023 → 27 Oct 2023 |
Publication series
| Name | International Symposium on Empirical Software Engineering and Measurement |
|---|---|
| ISSN (Print) | 1949-3770 |
| ISSN (electronic) | 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.
Keywords
- empirical research, infrastructure, Knowledge graph, literature review, requirements engineering, sustainability
ASJC Scopus subject areas
- Computer Science(all)
- Computer Science Applications
- Computer Science(all)
- Software
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
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).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
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
KW - literature review
KW - requirements engineering
KW - sustainability
UR - http://www.scopus.com/inward/record.url?scp=85178666312&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2306.16791
DO - 10.48550/arXiv.2306.16791
M3 - Conference contribution
AN - SCOPUS:85178666312
SN - 978-1-6654-5224-3
T3 - International Symposium on Empirical Software Engineering and Measurement
BT - 2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023
PB - IEEE Computer Society
Y2 - 26 October 2023 through 27 October 2023
ER -