DESCRIPTION

Data papers, sometimes also referred to as data notes or data reports, are defined as 'peer reviewed and citable articles in academic or scholarly journals, whose main content is a description of published research datasets, along with contextual information about the production and the acquisition of the datasets' (Schöpfel et al, 2019, 635-6). As Chavan and Penev note, the purposes of data papers are 'to provide a citable journal publication that brings scholarly credit to data publishers; to describe the data in a structured human-readable form; and to bring the existence of the data to the attention of the scholarly community' (2011, 3). Data papers are a relatively recent development in scholarly communication (Schöpfel et al, 2019, 623). They are published either in dedicated data journals, which may be generalist or discipline-specific, or in 'data sections' of mainstream journals. Examples of (the small number of) dedicated data journals in AHSS include the Journal of Open Humanities Data, the Research Data Journal for the Humanities and Social Sciences and the Journal of Open Archaeology Data.

While there is no standard structure for a data paper across participating journals, common elements include an overview of the dataset detailing its context and scope; a methods section documenting the process of data creation, including the software used, links to processing code as appropriate, and details of quality control mechanisms; a description of the dataset (including its location, structure/s, format/s, creators, provenance, license and other key metadata); and a discussion of its potential for reuse. As Walters notes, data papers 'often include greater methodological detail than would normally be found in a research paper' – for example, 'information on the procedures used to generate or compile the data, the population of interest, the sampling methods, the variable names and response codes, difficulties encountered, decisions made, [and] user notes' (2020, 4).

Various critics note the late adoption of data papers in AHSS relative to other disciplines (McGillivray et al., 2022, 4) and the relatively low number of dedicated data journals in AHSS (Kar & Rath, 2025, 350; Schöpfel et al., 2019, 626; Wigdorowitz et al., 2024). McGillivray et al. link this fact to the heterogeneity of data in these disciplines, the fact that humanities workflows traditionally do not include data sharing, and the lack of appropriateness of existing infrastructure to data in these areas (2022, 5-9). In the social sciences specifically, Kar and Rath suggest that '[c]oncerns over intellectual property, ethical considerations, and the absence of standardised guidelines' have hindered the adoption of data papers (2025, 352), while Long et al. (2025, 2) contend that existing templates for data papers are designed for quantitative datasets and omit attention to key qualitative issues such as the means of protecting participants' identities. Nevertheless, Kar and Rath (2025) identify an increasing role for data papers in the social sciences, while such scholars as Farina et al. (2025) highlight a growing consideration of data journals as a means of promoting data-driven approaches in the humanities.

As an open research practice, publishing data papers has a number of benefits. It supports the FAIRness (Findability, Accessibility, Interoperability and Reusability) of datasets by enhancing discoverability and providing rich documentation to support reuse (Schöpfel et al., 2019, 632; Kim, 2020, 17), in addition to fostering 'a more collaborative and open scholarly environment', as Farina et al. (2025, 16) note. The increase in the dataset's visibility, and the recognition data journals offer to data producers also both incentivise good practice around data sharing and promote a more equitable approach to the recognition of contributions to research, in line with the aims of the CRediT taxonomy. As Chavan and Penev observe, data papers 'acknowledge the efforts of all actors involved in data creation, data management and data publishing' (2011, 10). Data papers also contribute to the positioning of datasets as what Callaghan et al. term 'a first class research output that will be available, peer-reviewed, citable, easily discoverable and reusable' (2012, 113). Van Driel et al. further highlight specific benefits for social sciences research in that the increased transparency data papers enable 'is particularly relevant for projects that include rich process-tracing recording methods which are increasingly used in the educational sciences' (2023, 314).

Critics have noted that there are challenges and limitations to the data paper as an open and equitable practice, including the additional workload created for authors and reviewers, and the fact that most are subject to Article Processing Charges (Schöpfel et al., 2019, 626). Their impact has also been questioned, with Kar and Rath noting a 'citation paradox' whereby data papers receive 'fewer citations than traditional articles but [achieve] higher Altmetric attention due to reuse in policy and education' (2025, 351-2). In terms of traction, Wigdorowitz et al. note that the status of dedicated data journals 'has not yet been fully consolidated', making it crucial to 'consider the sustainability of data journals and data papers' (2024, 7). Others have emphasised the importance of raising researchers' awareness of data journals (Walters, 2020, 5), developing more standardised approaches to their content (Candela et al., 2015, 1755; Kim, 2020, 21; Schöpfel et al., 2019, 632), and more widespread adoption of open peer review for these outputs (Wang and Xu, 2025, 2).

References

Callaghan, S. et al. (2012). 'Making Data a First Class Scientific Output: Data Citation and Publication by NERC's Environmental Data Centres', International Journal of Digital Curation, 7(1), 107–113. https://doi.org/10.2218/ijdc.v7i1.218

Candela, L. et al. (2015). 'Data Journals: A survey', Journal of the Association for Information Science and Technology, 66(9), 1747–1762. https://doi.org/10.1002/asi.23358

Chavan, V. and Penev, L. (2011). 'The Data Paper: A Mechanism to Incentivize Data Publishing in Biodiversity Science', BMC Bioinformatics, 12(S15). https://doi.org/10.1186/1471-2105-12-S15-S2

Farina, A. et al. (2025). 'When Data Meets the Past: Data Collection, Sharing, and Reuse in Ancient World Studies', Open Information Science, 9(1). https://doi.org/10.1515/opis-2025-0014

Kar, S. and Rath, D.S. (2025). 'Open Data in Social Sciences: Growth, Impact, and Equity in Data Paper Publishing', DESIDOC Journal of Library & Information Technology, 45(4), 358–374. https://doi.org/10.14429/djlit.21026

Kim, J. (2020). 'An Analysis of Data Paper Templates and Guidelines: Types of Contextual Information Described by Data Journals', Science Editing, 7(1), 16–23. https://doi.org/10.6087/kcse.185

Long, H.A. et al. (2025). 'Developing a Data Note Reporting Guideline for Qualitative Health and Social Care Research Datasets (the DeNOTE Study): A Study Protocol', Health Psychology & Behavioral Medicine, 13(1). https://doi.org/10.1080/21642850.2025.2532792

McGillivray, B. et al. (2022). 'Deep Impact: A Study on the Impact of Data Papers and Datasets in the Humanities and Social Sciences', Publications (Basel), 10(4). https://doi.org/10.3390/publications10040039

Schöpfel, J., et al. (2019). 'Data Papers as a New Form of Knowledge Organization in the Field of Research Data.' Knowledge Organization, 46(8), 622–638. https://doi.org/10.5771/0943-7444-2019-8-622 Open access version available here: https://hal.univ-lille.fr/hal-02994295v1/file/Schopfel_Farace_Prost_Zane_isko19.pdf

van Driel, S. et al. (2023). 'Capturing and Characterizing Teachers' Noticing as Basis for their Classroom Management in Different Career Stages: A Data Paper', International Journal of Research & Method in Education, 46(3), 313–325. https://doi.org/10.1080/1743727X.2022.2110230

Wang, X. and Xu, L. (2025). 'What Are Journals and Reviewers Concerned About in Data Papers? Evidence From Journal Guidelines and Review Reports', Learned Publishing, 38(2). https://doi.org/10.1002/leap.2001

Walters, W.H. (2020). 'Data Journals: Incentivizing Data Access and Documentation within the Scholarly Communication System', Insights: The UKSG Journal, 33(1), 1–20. https://doi.org/10.1629/uksg.510

Wigdorowitz, M. et al. (2024). 'It Takes a Village! Editorship, Advocacy, and Research in Running an Open Access Data Journal', Publications (Basel), 12(3). https://doi.org/10.3390/publications12030024