Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

How are research data referenced? The use case of the research data repository RADAR

Dorothea Strecker, Kerstin Soltau, Felix Bach

TL;DR

This study investigates how datasets published in the RADAR research data repository are referenced in scholarly outputs to assess data citation practices. By cross-linking RADAR DOIs with Google Scholar, the DataCite Event Data, and the Data Citation Corpus, it quantifies references, their locations (e.g., reference lists vs. data availability statements), and across-year dynamics. Key findings include 27.9% of RADAR datasets being referenced at least once, with 21.4% of references forming data citations and a strong tendency for self-citation (approximately 98.7%), often concentrated in data availability statements. The work highlights fragmentation across data sources, the need for harmonized metrics, and the value of multiple data sources to obtain a fuller picture of data reuse and impact, informing policy and metric development for data usage typologies.

Abstract

Publishing research data aims to improve the transparency of research results and facilitate the reuse of datasets. In both cases, referencing the datasets that were used is recommended. Research data repositories can support data referencing through various measures and also benefit from it, for example using this information to demonstrate their impact. However, the literature shows that the practice of formally citing research data is not widespread, data metrics are not yet established, and effective incentive structures are lacking. This article examines how often and in what form datasets published via the research data repository RADAR are referenced. For this purpose, the data sources Google Scholar, DataCite Event Data and the Data Citation Corpus were analyzed. The analysis shows that 27.9 % of the datasets in the repository were referenced at least once. 21.4 % of these references were (also) present in the reference lists and are therefore considered data citations. Datasets were referenced often in data availability statements. A comparison of the three data sources showed that there was little overlap in the coverage of references. In most cases (75.8 %), data and referencing objects were published in the same year. Two definition approaches were considered to investigate data reuse. 118 RADAR datasets were referenced more than once. Only 21 references had no overlaps in the authorship information -- these datasets were referenced by researchers that were not involved in data collection.

How are research data referenced? The use case of the research data repository RADAR

TL;DR

This study investigates how datasets published in the RADAR research data repository are referenced in scholarly outputs to assess data citation practices. By cross-linking RADAR DOIs with Google Scholar, the DataCite Event Data, and the Data Citation Corpus, it quantifies references, their locations (e.g., reference lists vs. data availability statements), and across-year dynamics. Key findings include 27.9% of RADAR datasets being referenced at least once, with 21.4% of references forming data citations and a strong tendency for self-citation (approximately 98.7%), often concentrated in data availability statements. The work highlights fragmentation across data sources, the need for harmonized metrics, and the value of multiple data sources to obtain a fuller picture of data reuse and impact, informing policy and metric development for data usage typologies.

Abstract

Publishing research data aims to improve the transparency of research results and facilitate the reuse of datasets. In both cases, referencing the datasets that were used is recommended. Research data repositories can support data referencing through various measures and also benefit from it, for example using this information to demonstrate their impact. However, the literature shows that the practice of formally citing research data is not widespread, data metrics are not yet established, and effective incentive structures are lacking. This article examines how often and in what form datasets published via the research data repository RADAR are referenced. For this purpose, the data sources Google Scholar, DataCite Event Data and the Data Citation Corpus were analyzed. The analysis shows that 27.9 % of the datasets in the repository were referenced at least once. 21.4 % of these references were (also) present in the reference lists and are therefore considered data citations. Datasets were referenced often in data availability statements. A comparison of the three data sources showed that there was little overlap in the coverage of references. In most cases (75.8 %), data and referencing objects were published in the same year. Two definition approaches were considered to investigate data reuse. 118 RADAR datasets were referenced more than once. Only 21 references had no overlaps in the authorship information -- these datasets were referenced by researchers that were not involved in data collection.
Paper Structure (13 sections, 4 figures)

This paper contains 13 sections, 4 figures.

Table of Contents

  1. Introduction
  2. Data use
  3. Data referencing
  4. RADAR -- measures to support data use and referencing
  5. Method
  6. Data collection
  7. Results
  8. References to RADAR datasets
  9. Referencing methods
  10. Coverage of data sources
  11. Reuse of RADAR datasets
  12. Discussion
  13. Conclusion

Figures (4)

  • Figure 1: Outline of the data collection process.
  • Figure 2: Distribution of the publication years of referencing objects.
  • Figure 3: A referencing methods (based on gregory_tracing_2023), n = 604 references ; B position of the reference in the referencing object (multiple options can apply).
  • Figure 4: Number of references in the data sources.