AbiNader, M.A., Graham, L.M. & Kafka, J.M. (2023). Examining intimate partner violence-related fatalities: Past lessons and future directions using U.S. national data. Journal of Family Violence, 38, 1243–1254. https://doi.org/10.1007/s10896-022-00487-2
Bentley, C., Muyoya, C., Vannini, S., Oman, S., & Jimenez, A. (2023). Intersectional approaches to data: The importance of an articulation mindset for intersectional data science. Big Data & Society, 10(2). https://doi.org/10.1177/20539517231203667
Cookson, T. P., & Fuentes, L. (2026). Gender data, intersectionality, and a feminist politics of “negotiated refusal”. Violence Against Women, 32(2), 347-373. https://doi.org/10.1177/10778012241309362
Darian, A., Chauhan, A., Marton, R., Ruppert, J., et al. (2023). Enacting data feminism in advocacy data work. Proceedings of the ACM on Human-Computer Interaction, 7(CSCW1), Article 47, 1 – 28. https://doi.org/10.1145/3579480
Davies, S.E., True, J., Shiri, F., & Riveros-Morales, Y. (2025). Using data science to examine conflict-related sexual violence. Violence Against Women. https://doi.org/10.1177/10778012251395025
Doğan, A.L., Stevens, N., & D’Ignazio, C. (2025) Trans data: A research and design agenda from trans activists’ transformative data science. Proceedings of the ACM on Human-Computer Interaction, 9(7), 1-21. https://doi.org/10.1145/3757682
Edwards, D., Cooper, Z.G.T., & Hogan, M. (2025). The making of critical data center studies. Convergence: The International Journal of Research into New Media Technologies, 31(2), 429-446. https://doi.org/10.1177/13548565231224157
Fileborn, B., & Trott, V. (2022). “It ain’t a compliment”: Feminist data visualisation and digital street harassment advocacy. Convergence: The International Journal of Research into New Media Technologies, 28(1), 127-149. https://doi.org/10.1177/13548565211045536
Kasirzadeh, A. (2022). Algorithmic fairness and structural injustice: Insights from feminist political philosophy. AIES ’22: Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 349 – 356. https://doi.org/10.1145/3514094.353418
Klein, L., & D’Ignazio, C. (2024, June 5). Data feminism for AI. In FAccT ’24: Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency (pp. 100-112). https://doi.org/10.1145/3630106.3658543
Lameiro, F., Dunagan, L., Card, D., et al. (2025). TIDEs: A transgender and nonbinary community-labeled dataset and model for transphobia identification in digital environments. FAccT ’25: Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 1411-1423. https://doi.org/10.1145/3715275.373209
Lopes Heimer, R. dos V., McIlwaine, C., Rizzini Ansari, M., Peppl, R., et al. (2025). Embodied counter-mapping of gendered urban violence and resistance across body-community–city territories in Rio de Janeiro. Urban Geography, 46(4), 957–981. https://doi.org/10.1080/02723638.2024.2422208
Marčetić, H., & Nolin, J. (2022). Feminist data studies and the emergence of a new data feminist knowledge domain. First Monday, 27(7). https://doi.org/10.5210/fm.v27i7.12295
McIlwaine, C., Ansari, M.R., Leal, J.G., Vieira, F., & dos Santos, J.S. (2023). Countermapping SDG 5 to address violence against women and girls in the favelas of Maré, Rio de Janeiro, Brazil. Journal of Maps, 19(1). https://doi.org/10.1080/17445647.2023.2178343
Middleweek, B., & Klinger, L. (2025). ‘I just LOVE data’: Perceptions and practices of data sharing and privacy among users of the Lioness. Culture, Health & Sexuality, 27(3), 253–271. https://doi.org/10.1080/13691058.2024.2369596
Rocha, F., Diaz, M.D.M., Pereda, P.C., et al. (2024). COVID-19 and violence against women: Current knowledge, gaps, and implications for public policy. World Development, 174. https://doi.org/10.1016/j.worlddev.2023.106461
Tsaknaki, V., Reime, L., Cohn, M., and Pérez-Bustos, T. (2024). Knotting data as a feminist approach to data materialization. In C. Gray, E. Ciliotta Chehade, P. Hekkert, et al (Eds.), DRS2024, Boston, 23–28 June, Boston, USA. https://doi.org/10.21606/drs.2024.879
Young, E., Wajcman, J., & Sprejer, L. (2023). Mind the gender gap: Inequalities in the emergent professions of artificial intelligence (AI) and data science. New Technology, Work and Employment, 38(3), 391-414. https://doi.org/10.1111/ntwe.12278
Books, Chapters, and Theses
Amelang, K. (2022). (Not) safe to use: Insecurities in everyday data practices with period-tracking apps. In A. Hepp, J. Jarke, & L. Kramp. (Eds.), New perspectives in critical data studies. Palgrave Macmillan. https://doi.org/10.1007/978-3-030-96180-0_13
Broussard, M. (2023). More than a glitch: Confronting race, gender, and ability bias in tech. MIT Press.
Carlson, B. (2021). Data silence in the settler archive: Indigenous femicide, deathscapes and social media. In S. Perera & J. Pugleise (Eds.), Mapping deathscapes: Digital geographies of racial and border violence (pp. 84-105). Routledge.
D’Ignazio, C. (2024). Counting feminicide: Data feminism in action. The MIT Press.
D’Ignazio, C., & Bhargava, R. (2020). Data visualization literacy: A feminist starting point. In M. Engebretsen & H. Kennedy (Eds.), Data visualisation in society (pp. 208-223). Amsterdam University Press.
Guyan, K. (2022). Queer data: Using gender, sex and sexuality data for action. Bloomsbury.
Perez, C.C. (2021). Invisible women: Data bias in a world designed for men. Harry N. Abrams.
Suárez, V.H. (2023). Caring, with data : An exploration of the affective politicality of feminicide data [Doctoral dissertation, University of Warwick]. University of Warwick Repository. https://wrap.warwick.ac.uk/182622/
Other
Data against feminicide is a South-North participatory action research and design project that supports the work of activists and civil society organizations that produce data on gender-related violence and its most lethal expression: feminicide.
Data2X is a civil society organization and gender data alliance, working with partners to improve the production and use of gender data through strategic partnerships, research, advocacy, and communications.