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• Rationale
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• Timetable
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• Why Submit to Data & Policy
• Open Access
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Rationale

This special collection (SC) explores the critical role, collection, and use of sex-disaggregated data and gender statistics (S/GDD) in evidence-informed policy-making, particularly in social policy. The analyses span the global level framing in the Sustainable Development Goals (SDGs), the regional manifestation through EU-level indices and datasets, and mechanisms and best practices in gender budgeting and programme planning. Accurate S/GDD are essential for addressing gender inequalities and supporting the EU’s commitment to gender equality, as outlined in its founding treaties and the Gender Equality Strategy 2020–2025. Despite these commitments, many member states lag behind in achieving gender parity, highlighting gaps in data availability and quality necessary to frame targeted and transformative policies. This SC focuses on such data in social outcomes, examining data pathways that include institutions, processes, and networks involved in data collection and management. It aims to address data gaps and identify best practices to ensure gender-specific needs are accurately captured, ultimately supporting data-driven policies that foster social change and equality.

Prior research shows that gender biases in data, i.e., data where men are the norm, fail to adequately reflect women’s lived experiences (see Criado Perez 2019; D'Ignazio & Klein 2020). In 2022, UN Women estimated that it would take 22 years to close the gender data gap to adequately assess the implementation of the SDGs and concluded that no one country had all the necessary data available (UN Women, 2022). The UN Women’s Women Count initiative (UN Women, 2024) which aims to support countries in defining, collecting and using gender statistics identified the following overarching challenges which lead to the lack of gender data: a) weak policy space; b) technical and financial barriers; c) lack of access and limited capacity of users.

The proposed SC aims to address these challenges in several ways. Firstly, it will help understand the gender data reality and rhetoric of official statistics providers in selected countries. It will conduct an assessment of existing resources (e.g., United Nations Sustainable Development Indicators, Eurostat) in terms of sex-disaggregated data and gender statistics availability.

Secondly, the SC will help understand the policy and legal space which underpin data management, i.e., data pathways. These relate to existing institutions, processes, networks, and initiatives of data collection, curation, and use to inform policy-making on women’s wellbeing. The analysis focuses on the quality of data used to assess human and in particular women’s well-being, the structure and governance of data, open access, and data sharing by policy-making bodies for the public good. This will help identify best practices and relevant data gaps in measuring women’s wellbeing.

Thirdly, it is shown how the gaps in data availability, as well as complicated pathways to these data, manifest in social realities of everyday lives, capturing the broader well-being of women and girls in terms of their political participation, equality before the law, health, education, freedom from violence, access to public finances, and more. Thanks to the contributions, the SC show how the lack of S/GDD availability is the outcome of long-term processes and developments. Pathways to S/GDD have been highly fragmented for decades in terms of the actors involved, data collection processes, and data production governance (UN Statistics Division, 2016, pp. 15-19).

The SC’s relevance lies in its commitment to enhancing representation and participation, aiming to de-bias data collection and democratize societal data practices (Viljoen 2020; Batarseh & Yang 2020). By addressing the systemic absence of sex-disaggregated data and gender statistics, it aims to make women visible in social policy analysis and foster interest in this crucial area among young academics. Central to the SC is the improvement of gender data parity in social policies. While some tools already exist (e.g., the EIGE Gender Equality Index) and provide baseline knowledge, a comprehensive understanding of gender-relevant data collection, management, and coverage remains insufficient.

The SC attempts to fill this gap by providing a platform to analyze and possibly tackle (some) gender data deficiencies. Inspired by Criado-Perez’s concept of the ‘invisible women’ 3 in data (2019), it highlights the policy distortions that arise from missing gender-disaggregated data and seeks to enhance the role of women in societal development through accurate representation. Additionally, the SC emphasizes participation by analyzing data pathways, open data infrastructures, and collaborative data communities to improve democratic practices and EU social policy frameworks (Thoneick et al. 2022). 

References

Batarseh, F.A., Yang, R. (2020). Data democracy for you and me (bias, truth, and context), in:Batarseh, F.A., Yang, R. (Eds.), Data Democracy: At the Nexus of Artificial Intelligence, Software Development, and Knowledge Engineering. Elsevier, pp. 3–8.

Criado Perez, C. (2019). Invisible women: Exposing data bias in a world designed for men. Random House.

D’Ignazio, C., & Klein, L. F. (2020). Data feminism. MIT press.

Thoneick, R., Degkwitz, T., Lieven, C. (2022). Advancing Participatory Democracy through Collaborative Data Platforms, in: Schwegmann, R., Ziemer, G., Noening, J.R. (Eds.), Perspectives in Metropolitan Research. Digital City Science. JOVIS Verlag, Berlin, pp. 93–105.

United Nations Statistics Division. (2016). Integrating a Gender Perspective into Statistics.

United Nations Women (2022). It will take 22 years to close SDG gender data gaps. Available at www.unwomen.org. United Nations Women (2024). Women Count.

Viljoen, S. (2021). A relational theory of data governance. Yale Law Journal, 131(2), 573-654.

Timetable

The deadline for submissions is the 9th January 2026. 

Articles will be published as soon as possible after acceptance and added to a collection page; earlier submission therefore may result in earlier publication.

How to Submit

Authors should submit articles through the Data & Policy ScholarOne site, using the special collection tag when prompted.

Please feel free to use the journal's LaTeX or Word templates. Note also that we have a template in Overleaf, a cloud-based, which has collaborative features and enables authors to submit directly into the Data & Policy system without having to re-upload files.

Note that Data & Policy publishes the following types of articles, which authors will be prompted to select from on submission:

• Research articles that use rigorous methods that demonstrate how data science can inform or impact policy by, for example, improving situation analysis, predictions, public service design, and/or the legitimacy and/or effectiveness of policy making. Published research articles are typically reviewed by three peer reviewers: two assessing the academic or methodological rigour of the paper; and one providing an interdisciplinary or policy-specific perspective.
• Commentaries are shorter articles that discuss and/or problematize an issue relevant to the Data & Policy scope. Commentaries are typically reviewed by two peer reviewers.
• Translational papers are contributions that show how data science principles, techniques and technologies are being used in practice in organisational settings to improve policy outcomes. They may present original findings but are less embedded in the scholarly literature as research articles. They are typically reviewed by two peer reviewers, who assess the rigour and policy significance of the paper.
• Data papers that provide a structured description of an openly available dataset with the aim of encouraging its re-use for further research.

You can read more on the Instructions for Authors here.

Data & Policy strongly encourages authors to make replication data and code available in an open repository, where this is possible (see the research transparency policy). All authors must provide a Data Availability Statement in their article that explains where the replication material resides, if it is available, and if not, the reason why it cannot be made accessible. Authors who link to replication materials will be awarded Open Data and/or Open Materials badges that display on the published article.

Why Submit to Data & Policy?

✔ A venue developed for and expanding the community working at the data science for governance interface, established by the Data for Policy Conference.
✔ Welcomes research, translational articles, commentaries and data papers, plus the Data & Policy blog for more immediate reflections.
✔ Well-cited (2024 Impact Factor: 2.7 and Cite Score: 3.6) and indexed in Web of Science, Scopus and Directory of Open Access Journals.
✔ Open Access with support for authors who do not have access to funding to pay publishing charges.
✔ Promotes open sharing of data and code through Open Science Badges.

Open Access

Any author can publish on an open access basis in Data & Policy, irrespective of their funding or institutional affiliation. Many articles have publishing costs covered through the Transformative Agreements that Cambridge has set up with universities worldwide. Authors not affiliated with these agreements can still publish open access. Authors who have a grant that specifically budgets for open access publication are expected to pay an article processing charge (APC). However, if an author has no funding to pay an APC and no institutional agreement, the charge will be waived. Please feel free to submit to this special collection irrespective of where you are based and whether or not you have research funding.

Guest Editors

Gaby Umbach, Part-time Professor, Robert Schuman Centre for Advanced Studies, European University Institute, Data & Policy Advisory Board 

Bogna Kietlińska-Radwańska, Assistant Professor, University of Warsaw

Jaromir Harmáček, Associate Professor, Palacky University Olomouc