GENDER DATA FUTURES: Chapter 4 & Conclusion

Chapter 4:

Key Strategic Goals for a Gender Transformative Data Governance

A gender transformative approach aims to uncover and address the underlying causes of gender- based inequalities, discrimination, constraints and exclusion. These causes often include entrenched gender norms, stereotypes, sociocultural attitudes and behavior, and power relations at multiple levels, all of which create, reinforce, and sustain gender inequalities.50

Gender inequality and harmful gender norms fuel discrimination and unfairness in the data governance systems and processes as well as limiting access to information and participation for women and other marginalized groups. Interventions which are gender blind risk being exploitative or harmful, as well as ineffective. An effective data governance system must have gender at its centre.

Gender transformative approaches address norms and practices that underlie gender inequality, challenge and ultimately transform the unequal distribution of power in society, benefitting people of all genders. Taking these approaches will help to end discrimination and exclusion in the data governance systems and processes.

In the context of data governance, adopting a gender transformative approach involves working to transform harmful gender norms that promote exclusion of women in data governance processes; remove gender barriers to services and advocate for gender equality.

For example, several African countries have rolled out national digital identification programs. While intended to streamline access to services, civil society has frequently raised concerns that women, especially those in rural areas, were being excluded because of entrenched gender inequalities. Many women lacked the documentation (such as birth certificates or property titles) needed to register; a barrier tied to historic gender discrimination in inheritance and land rights. In response, human rights organizations advanced a gender transformative approach by advocating for reforming policies on identity proof, challenging discriminatory norms, expanding practical access through targeted outreach and mobile registration, and linking digital ID advocacy to broader structural reforms in land and inheritance rights.

A transformative approach therefore promotes gender equality, critically examining inequalities and gender, strengthening positive practices and reshaping social structures, policies and systems that sustain gender inequality.51

The following strategic goals stand out as key considerations raised from the participatory workshops in the three countries: Côte d’Ivoire, Uganda and Zambia that should not be overlooked during a gender transformative data governance. Each of the components is explained and has respective specific actions that users of this handbook can leverage on to improve their gender integration into data governance.

Additionally, each strategic goal includes a checklist with questions to help users assess compliance with data governance processes and ensure their actions align with this handbook’s strategic goals for gender transformative data governance. Furthermore, the checklists will enable users to compare existing data governance practices with the standards highlighted in this handbook, identify gaps, biases across the data value chain and guide the development of gender sensitive policies and programs. The checklists will also serve as a reflective and collaborative tool, encouraging dialogue during consultations, training and stakeholder meetings to promote shared understanding, exchange good practices and co-create solutions.

Strategic Goal 1: Citizen Engagement in Data Governance Practices

Citizen contributions to data, throughout the data value chain, from design, collection to dissemination and use, is vital to ensure that data reflects the lived realities and needs of all people, particularly marginalized groups. Such participation empowers communities to engage meaningfully with public institutions, amplifies marginalized voices, expands citizen ownership of data production and enhances accountability. Citizen contributions to data also help overcome the data challenges, such as invisibility of some categories of people in official statistics, lack of trust in institutions, and the disconnect between local issues and national policymaking, fostering a more inclusive decision-making process.52

In many contexts, women and other marginalized groups are insufficiently engaged in data governance at different levels and they remain unaware of their rights, responsibilities and potential influence over how data is collected, managed and used.53 In practice, their participation is often limited to giving consent during data collection, and only when they are directly involved.54 Broader participation is frequently dominated by international organizations, government ministries and probably a few civil society organizations, leaving these groups of people excluded from deeper involvement in decision making.55

Across Africa, women have participated in activities such as analysing budgets and service delivery data, and co-designing transparency initiatives such as community scorecards and open data dashboards, giving them a direct role in data governance while ensuring gender-specific barriers are identified and addressed.56

Collaborating with women and integrating their ideas improves their visibility in data, highlighting voices often ‘left furthest behind’ and revealing experiences traditional sources miss. Women’s involvement in the data chain enhances decision-making evidence and bridges the trust gap between citizens and governments.57 Women and girls’ contributions to data, such as leading data productions or participating in official statistics production, can be initiated by different stakeholders, whether state (national statistical offices or other government institutions) or non-state actors, including individuals, civil society organizations (CSOs) or academia. This can take place at different stages of the data value chain, from the design of data collection tool, through data production and analysis, until dissemination and uptake.58

Specific Action 1: Partner with women and girls’ movements for participatory data governance.

Look to women and girls’ movements and advocates, who have long been at the forefront of driving real change in the data governance ecosystem and collaborate with them/ask for their participation in data governance-related initiatives. These movements and advocates are often experts in the kinds of social mobilization and coalition-building that provide the fertile ground in which the use of data and other transparency and accountability approaches can take root. Engage them in data monitoring approaches such as citizen scorecards, open data platforms, and dashboards, to drive accountability in data governance processes.

Specific Action 2: Build the capacity of women and girls to shape how data is governed.

Provide dedicated capacity building and technical support for women and girls’ movements to help them use data and better engage with data governance processes and practices. Meaningful engagement with women and girls should become a routine standard, not an afterthought. Promoting data governance literacy among women and marginalized groups enhances their ability to contribute meaningfully. Tailored programs, considering literacy levels and cultural nuances, that equip women with skills for collecting, analyzing, and interpreting gender data. Workshops and educational campaigns foster ownership and confidence in gender data generation.

Checklist for Citizen Engagement in Data Governance Practices

Governments and partners can use the following checklist questions to assess whether data governance initiatives centre the voices, expertise, and agency of women and girls.

• Are women and girls’ movements actively involved in designing and implementing data governance initiatives across the data value chain?

• Are there any dedicated training or programs, resources and technical support to ensure women and girls can meaningfully engage with open data, citizen scorecards, and accountability mechanisms?

• Are there mechanisms for women and girls to provide feedback on the value and willingness to continue to participate in data governance processes?

Strategic Goal 2: Ethical Gender Data Governance

As governments modernize their data systems, ethical data governance has emerged as a cornerstone for ensuring fairness, integrity, and inclusion in the use of data. It is increasingly vital for governing data processes across the value chain and driving development and innovation in African governments. However, many existing governance approaches across Africa are adapted from global frameworks that inadequately address the continent’s cultural diversity, infrastructural realities, and socio-political contexts. Current approaches often lack inclusivity and fail to establish sufficient trust between stakeholders, resulting in persistent bias, inequitable access, and limited community engagement.59

Ethical data governance involves establishing appropriate standards to maintain data quality and safeguard the rights of women and girls while ensuring that data is collected and used responsibly.60 It emphasizes standards that the minimum amount of data necessary to accomplish the intended purpose is collected and used responsibly.61 It also involves standards that ensure that data is accurate and of good quality, and that robust security measures are implemented to protect women and girls’ data from unauthorized access, processing or damage.62 Ethical guidelines are vital to ensure the rights and well-being of women and girls are respected, contributing to the credibility and sustainability of generated data.63

However, as data systems evolve and become interconnected, especially through cross-border data flows, there is a need for clearer guidance to manage ethical challenges in data sharing, access and use. Such guidance becomes essential to ensure there are ethical, equitable, and rights-based governance practices that will help to prevent unintentional violations of privacy and community rights.64 For example, there have been cases of health data exploitation, political surveillance, and digital exclusion, which disproportionately affect rural women and marginalized communities across various African countries.65

Ethical data governance for African countries means creating systems and policies that ensure that data on women, girls and marginalized groups is collected, managed and used in ways that promote gender equality, protect rights and avoid harm as well as aligning with international standards.66

Specific Action 1: Integrate gender responsive provisions into data governance. Ensure that data governance processes ensure context specific gender responsive mechanisms. For example, integrate gender responsive provisions into national data governance processes, maintain privacy and security standards, and safeguard data against misuse and discrimination.

Specific Action 2: Have clear ethical guidelines. Ensure there are clear ethical data guidelines and protocols for transparent data governance processes. Additionally, establish data-sharing protocols for which gender data can be shared and with which institutions, as well as how it should be gathered.

Guidelines should also include monitoring systems to track positive impacts and potential risks against women, girls and other marginalized groups that may arise in data governance processes.

Checklist for Ethical Gender Data Governance

Stakeholders can use this checklist to evaluate whether data governance processes are gender responsive and inclusive. They emphasize safeguarding against discrimination, addressing biases, establishing clear guidelines, monitoring risks and benefits and fostering multi-stakeholder collaboration to ensure accountability and equity in data governance.

• Do national data governance protocols include gender responsive provisions that safeguard against discrimination and misuse of gender data?

• Do governments have mechanisms in place to address particular ethical challenges and biases that affect women, girls and other marginalized groups in data governance?

• Have ethical guidelines and protocols for data governance across the data value chain to ensure gender inclusivity been developed?

• Are monitoring systems in place to track both positive impacts and potential risks to implementing intersectional and gender data practices?

• Is there an established multi-stakeholder platform or mechanism for ongoing collaboration, review and adaptation of gender responsive practices in data governance?

Strategic Goal 3: Strengthening Production and Use of Gender Data

The state of gender data systems in African countries is extremely poor. In most countries, gender data are not readily available, and where they are available, they are often not fully open.67 Furthermore, there is a lack of support throughout the gender data system for the production and use of gender data. Data collection methods take into account stereotypes and social and cultural factors that may induce gender bias in the data.68

Gender data is largely lacking for many African countries, leading to significant gaps in understanding the lived realities of women, girls and gender-diverse groups.69 Women’s productive work and contributions to development are therefore often underreported by official statistics across countries.70 Data on these are not well covered by surveys, and consistent guidelines on gender disaggregated data collection for these topics are also not available.71

Even when data are collected, quality issues arise in the absence of consistent standards for data collection.72 A major concern is the reliance of survey methods on using proxy respondents to report on outcomes for other household members, particularly women.73 This approach frequently introduces measurement errors issues of women, as they remain unreported by the proxy respondent, who is usually the household head/member.74

This absence reinforces gender-blind policymaking and undermines inclusive development. Without reliable data, national governments, development agencies and actors cannot accurately identify or address issues, or evaluate the impact of decisions on the population.75

The way surveys are administered also affects the accuracy of the data collected. Factors such as wording, question framing, presence of others during the interview, and the choice of the interviewer can significantly affect responses, particularly for sensitive questions.76 For instance, in mixed-gender focus groups, women may speak less or refrain from sharing their opinions openly, especially on sensitive topics, due to prevailing social norms and power dynamics. For this reason, data collection exercises, whether through census, specialized population surveys or administrative records, must not create or reinforce existing discrimination, bias or stereotypes exercised against population groups.77 Proper data collection is an essential starting point in realizing gender transformative data governance. It has the potential to reveal how gender-based inequality, discrimination and exclusion are socially constructed by identifying underlying root causes and highlighting the ways by which transformative change and results can be promoted.78 Greater investment in qualitative studies is also critical to ensure a comprehensive understanding of the lived realities of men and women, especially those from marginalized groups.79

Specific Action 1: Co-create and engage women, girls and other marginalized groups in the data production processes, such as designing surveys and other data collection tools to ensure their voices and concerns are accurately represented.

Specific Action 2: Integrate intersectionality right from data collection by ensuring that data goes beyond the binary categories and captures the multiple overlapping identities that shape women’s experiences, such as age, education level, gender, race, socio-economic status, geographic location, among others.

Specific Action 3: Develop and refine research methodologies that capture the full spectrum of gendered experiences, including those from marginalized groups. Research methodologies should be designed in such a way that they have questions and methods that dig deep into gender nuances that reflect the lived realities of women. By adopting this approach, unique barriers faced by women and girls can be uncovered, thereby informing more equitable gender transformative policies and interventions.

Specific Action 4: Train researchers/data collectors on gender sensitive and ethical data collection techniques. This will help sustain inclusive data collection practices.

Checklist for Strengthening Production and Use of Gender Data

These checklist questions are designed to guide stakeholders in assessing whether data production systems are gender responsive, inclusive, and aligned with international standards.

• Are survey data collection tools designed, standardized and adapted to reflect the diverse realities of women and other marginalized populations?

• Are women, girls and other marginalized groups actively engaged in the design of surveys and data collection tools?

• Is there intersectional representation in data processes?

• Are women, girls and other marginalized communities engaged to validate data to ensure that their experiences are accurately represented in the data?

• Are data collectors and researchers trained in gender sensitive and ethical data collection techniques?

Strategic Goal 4: Multi-stakeholder Partnerships for Gender Transformative Data Governance

Gender transformative data governance cannot be achieved by one entity alone. It requires a collaborative effort that brings together diverse expertise, sectors, experience and influence. Multi-stakeholder partnerships leverage the unique expertise, resources and capacities of each partner to achieve change.80 Establishing and strengthening such partnerships with a diverse range of stakeholders, especially with civil society and women’s movements, is key for sustainable impact. Multi-stakeholder partnerships can also help shift the balance of power from international organizations to national and, in particular, local and grassroots organizations.

Collaboration between stakeholders including individuals, groups and institutions that collect, manage, regulate, use or are affected by the data is vital for effective data governance with public sector setting frameworks, private sector offering technical expertise and CSOs championing advocacy for privacy, trust and rights ensuring that data governance is inclusive and equitable.81 Such collaborations and partnerships with diverse actors are necessary to address gender-specific needs and integrate gender-transformative approaches into data governance. Key mandates such as the African Union Data Policy Framework promote such multi-stakeholder collaborations to foster exchange and interoperability of data systems.82 All efforts must be made to ensure all stakeholders, including and especially those that are most vulnerable, such as women and girls facing multiple and intersecting forms of discrimination, have genuine ownership and control over data governance processes at all levels, and in all phases of the data value chain.

Stakeholders’ active involvement can help facilitate understanding of the local context by identifying challenges and constraints as well as potentials and opportunities. It can also strengthen ownership of, and support for, development interventions and the identified transformative changes and results.83 For example, in Rwanda the UN Women, collaborates with key partners under the National Gender Machinery comprised of Ministry of Gender and Family Promotion, National Women’s Council, Gender Monitoring Office and Rwanda Women MPs (FFRP) to ensure that all women and girls can fully and equally participate in decision-making, and can benefit from gender-responsive laws, policies, budgets, services, and accountable institutions.84

Specific Action 1: Expand collaborative efforts to champion gender data collection, analysis, use and dissemination. Governments and non-government actors should work together to pool their capacities and expertise.

Specific Action 2: Establish multi-stakeholder gender data task forces at national and regional levels that bring together all stakeholders to co-create and oversee the development of gender transformative data governance

Specific Action 3: Foster multi-stakeholder partnerships to co-fund gender data initiatives and share resources efficiently.

Checklist for Multi-stakeholder Partnerships

These checklist questions guide stakeholders on establishing collaboration and cross-sector partnerships between various stakeholders to ensure innovation, accountability and oversight.

• Are national statistics offices and governments collaborating with women organizations and CSOs to design inclusive data governance processes?

• Has a national or regional multi-stakeholder gender data task force been established to oversee gender transformative data governance processes?

Strategic Goal 5: Women’s Networks for Data Governance Leadership

Women’s meaningful participation in the decision-making process in data governance is essential for creating inclusive, equitable and effective policies. A limited number of women contribute to data production, analysis and use across sectors, but most importantly, they are equally underrepresented in leadership positions and excluded from high-level decision-making.85 This underrepresentation is driven by barriers such as unequal access to information, limited opportunities for leadership development, lack of women-centered public policies, patriarchal dominance in the operations of governments and persistent gender stereotypes that undermine women’s authority and influence.86 Addressing these challenges requires targeted efforts to create pathways for women not only to participate but also lead in shaping data governance frameworks, standards and priorities.87 Strengthening women’s leadership in data governance demands more than token representation, it involves equipping them with skills, networks and institutional support necessary to influence policy and decision making demands more than token representation, it involves equipping them with skills, networks and institutional support necessary to influence policy and decision making.88

Women’s networks are essential and influence promotion, retention and progression into leadership. Additionally, they create benefits and opportunities not just for individuals, but also for organizations and governments. For example, the Graça Machel Trust (GMT) a South African-based women’s network, supports women’s networks across 20 African countries, enabling women entrepreneurs to succeed from grassroots to international levels.89 Others such as New Faces New Voices (NFNV) operating in Uganda, Nigeria, Cameroon, Kenya, Tanzania, Egypt, Rwanda, Zambia, Mozambique, Zimbabwe, the Democratic Republic of Congo (DRC), promotes women’s financial inclusion, Women in Clean Energy and Climate Action ensures women’s active participation in Africa’s clean energy transition while The African Women in Agribusiness Network supports women in agriculture and agro-processing, and the Network for African Businesswomen (NABW) supports women across broader business sectors.90 These networks have inspired remarkable entrepreneurial innovations, helped women grow their businesses, access new markets locally and internationally, and benefit from training programs to enhance their skills.91 Additionally, networks enable women from diverse backgrounds to connect through summits, workshops, mentorship programs, and digital forums. This collective effort amplifies their impact, providing better access to opportunities, and business innovations.92

In Kenya, the NFNV network introduced exclusive insurance packages tailored to support women entrepreneurs in mitigating business risks. In Uganda, the networks collaborating with the Ministry of Finance led to the establishment of the Citizen’s Financial Reference Bureau (CFRB) to provide financial arbitration and advisory services for women groups.93 The transformative power of women’s networks and collaboration is undeniable. As more women unite to share knowledge, overcome challenges, and seize opportunities, they are collectively shaping a future that is equitable, prosperous, and resilient, a future where the power of collaboration truly transforms the world.94

As such, it is interesting to consider the role women’s networks can play in subverting, dynamics that contribute to gender inequality in data governance. Governments and other stakeholders should intentionally identify and nurture women leaders to ensure their voices are heard in national, regional and global data governance processes. By fostering an environment in data governance where women’s leadership is valued and sustained, data governance can become inclusive for all.

Specific Action 1: Foster strong networks. Establish a women’s network in data science, data governance and digital technology to amplify women’s leadership, build technical capacity, foster mentorship and create a platform for collective advocacy on gender transformative data practices across Africa. This network would work to influence policy, promote research and ensure that women’s perspectives and experiences shape data governance agendas, at local, national and continental levels.

Specific Action 2: Appoint women to decision making bodies. Promote women’s participation in decision-making and management bodies in data governance and technology. Identify obstacles to women’s presence on data governance and tech bodies, including stereotypes and other negative and exclusionary attitudes and practices, and address them. Steps must be taken to ensure that women not only occupy positions on decision making bodies, but that they have a real possibility to participate effectively and influence decisions

Specific Action 3: Establish robust mentorship programs. Create structured and sponsored mentorship programs for women in data governance leadership and decision making. Through these programs pair aspiring women with experienced professionals and leaders in STEM and data governance across the continent who can provide guidance, support and advocacy.

Specific Action 5: Increase visibility of role models. Highlight successful African women in STEM, data governance through various platforms to inspire the next generation and challenge societal norms.

Checklist for strengthening women’s leadership in data governance.

To assess progress in advancing women’s leadership and meaningful participation in data governance, and technology, the following checklist questions can help evaluate representation, mentorship and the strength of supportive networks.

• Are women represented on national and regional data governance decision making bodies?

• Are there transparent mechanisms in place to monitor and track women's inclusion in leadership positions on these bodies in data governance?

• Has a formal network in data governance, science and technology been established?

• Does the network provide mentorship and capacity strengthening opportunities for women in data governance?

• Are women perspectives from diverse regions across the continent represented within the network?

• Are there targeted interventions in place to support women's roles in decision making and leadership as well as increasing women's own awareness of their rights and strengthening their self-esteem and confidence?

Strategic Goal 6: Capacity Building

Building the capacity of diverse actors is central to achieving gender transformative data governance. Capacity building should be a key national and regional priority, and resources will need to be allocated in this regard in the areas of data, skills and an understanding of gender transformative data governance. Meaningful participation of women, girls and marginalized groups in data governance requires more than inclusion; it demands skills, confidence, and institutional support to engage, question and influence how data is collected, managed and used. Strengthening capacities at individual, institutional and systemic levels ensures that gender perspectives are not merely added on but embedded throughout the data processes. From promoting data literacy to ethical awareness, data analysis, reporting and use, capacity building empowers stakeholders to co- create equitable, inclusive and accountable data systems that serve everyone. For example, there have been capacity building efforts by various African governments on enforcing data protection laws and managing cross-border data flows by UNECA,95 and capacity building for youth and local academic institutions to improve data demand and supply at all levels by the African Population and Health Research Center.96 Equipping both policymakers and community members with the skills they need not only empowers them but also bridges the gap between ambition and reality, driving tangible progress.

Specific Action 1: Build capacity for intersectional data use. Without adequate skills and resources, even the best-intentioned efforts to apply intersectional data will fall short. Investments in user training and data literacy are essential to turn data into actionable insights.

Specific Action 2: Invest in gender responsive capacity building. Governments should invest in building capacity and strengthening national statistical systems and harmonizing data collection tools to eliminate bias and gaps, particularly for women and other marginalized populations. This includes enhancing skills in data analysis, production of gender responsive reports and integrating gender data into national and regional statistics to improve data availability and inform inclusive decision making.

Specific Action 3: Support the development of feminist and gender data curricula and training toolkits tailored for public institutions, civil society organizations, and academia, to build a critical mass of gender data champions equipped to drive inclusive, ethical and rights-based data governance practices.

Checklist for Capacity Building

To strengthen gender transformative data governance, it is essential to assess whether training systems and resources adequately integrate gender and intersectionality. The following questions help to evaluate the extent to which capacity programs are designed, updated and applied across institutions.

• Are there national and regional training programs in place that include gender and intersectionality modules?

• Have curricula and toolkits been developed specifically to train gender transformative and intersectional data governance?

• Is the training content updated regularly to reflect emerging best practices in gender responsive and intersectional data governance?

• Are public institutions, CSOs, and academia using these training materials to strengthen inclusive, ethical and rights-based data governance practices?

Strategic Goal 7: Budgetary Allocation for Gender Transformative Processes

While over 90% of countries globally examined by a recent UN Women report have policies and programs to address gender equality, only 53% of them go ahead to report having sufficient resources allocated for that purpose.97 What is more surprising is that only a minority of countries present government expenditures by gender, obscuring potential cues to how the bulk of government spending can address gender gaps.

Adequate and sustained budgetary allocation is essential for advancing gender transformative data governance.98 Without dedicated funding, initiatives promoting gender equality in data collection and use often remain under-prioritized or unsustainable. Gender transformative processes require investment in human and technical capacity, development of inclusive tools, continuous stakeholder engagement and monitoring mechanisms that ensure that women and girls experiences are reflected in data systems and policy outcomes.99 The budget should therefore consider such investments to enable equitable allocation of resources.

Specific Action 1: Institutionalize gender transformative budgeting within national and institutional data governance processes to ensure consistent budget allocation for gender transformative initiatives.

Specific Action 2: Designate budget lines specifically for gender data production, analysis, and dissemination within various institutions and relevant government agencies.

Specific Action 3: Conduct regular audits and reporting on expenditure related to gender equality and data governance.

Specific Action 4: Build capacity of stakeholder on gender transformative planning, budgeting and monitoring so as to integrate gender considerations into planning, budgeting and resource allocation.

Checklist for Budgetary allocation for Gender Transformative processes

Ensuring that sufficient resources are allocated to gender transformative data governance is critical for translating commitments into action. These checklist questions help stakeholders assess whether financial planning, budgeting and resource allocation processes meaningfully support gender transformative processes in data governance.

• Is there a dedicated budget line for gender transformative data governance processes? Are gender considerations integrated into financial planning and resource allocation processes?

• Are statistical systems adequately funded and strengthened to systematically collect gender disaggregated data across all sectors?

• Are there transparent mechanisms to track and report spending on gender transformative data governance initiatives?

• Have financial personnel received training on gender transformative budgeting?

Strategic Goal 8: Research and Development

Strengthen research and innovation ecosystems that prioritize gender transformative data governance by promoting feminist and intersectional knowledge production, evidence generation and technological advancement. Investments in data-related innovation and research and development as well as in capabilities to harmonize standards, skills and infrastructures, can enable stakeholders to develop better data related policies across the board. Additionally, invest in research that exposes gender biases and innovations that address gender data gaps across sectors.

Specific Action 1: Establish national and regional hubs focused on gender data governance to facilitate cross-sectoral knowledge exchange, peer learning and collaboration between researchers, CSOs and policy makers.

Specific Action 2: Fund participatory research on gender data gaps to generate evidence that informs policy and program design, particularly those in under-researched categories.

Checklist for Research and Development

The following checklist questions help assess whether participatory research initiatives are in place to strengthen collaboration and evidence-based policymaking in data governance.

• Have national and regional hubs on gender data been established?

• Do these hubs facilitate cross-sector learning and knowledge exchange between researchers, CSOs, policy makers, and other stakeholders?

• Are women's rights organizations and marginalized communities meaningfully represented in these hubs?

• Is there a funding mechanism dedicated to participatory research on gender data gaps?

• Are research findings disseminated in accessible formats for policy makers, CSOs, and communities?

Conclusion

A gender transformative approach in data governance goes beyond addressing inequality gaps, it confronts the systemic and structural causes of gender-based discrimination, exclusion, and power disparities. This means challenging the entrenched norms, practices, and institutional arrangements perpetuating inequality. Importantly, gender transformative change must occur in the design of data governance interventions by governments, private sector actors, civil society, and international development partners. By strengthening the gender responsiveness of policies, strategies, processes, and procedures whilst ensuring accountability for equitable outcomes, data governance systems that are fair, transparent, and inclusive can be built.

Ultimately, gender transformative approaches are a foundational requirement for sustainable and equitable development in the digital age. When women and other underrepresented voices have equal voice, agency and leadership, in shaping how data is collected, governed and used, societies are better positioned to harness data for public good, safeguard rights and drive inclusive agendas. This handbook calls stakeholders to commit to this vision as an ongoing collective responsibility that shapes the future of data governance.

50 Open Data Watch S Data 2X, (2019),Bridging the Gap: Mapping Gender Data Availability in Africa Technical Report
51 Maina, S., S Rooney,L.(2024). Gender data is not just valuable; it is essential in preventing and responding to gen- der-based violence. But there are gaps; UN Women and Lauren Rooney, iMMAP Inc.
52 UNSD (2024), The Copenhagen Framework on Citizen Data
53 Chowdhury, R. Misrepresentation of Marginalized Groups: A Critique of Epistemic Neocolonialism. J Bus Ethics 186, 553–570 (2023). https://doi.org/10.1007/s10551-022-05229-4
54 Data2X, (2022), Transforming the Data Landscape. Solutions to Close Gender Data Gaps. https://data2x.org/wp-con- tent/uploads/2022/04/Solutions-to-Close-Gender-Data-Gaps-FINAL.pdf
55 Focus Group Zambia
56 Albert Meijer, Suzanne Potjer, (2018) Citizen-generated open data: An explorative analysis of 25 cases, Government Information Quarterly, Volume 35, Issue 4, Pages 613-621, ISSN 0740-624X, https://doi.org/10.1016/j.giq.2018.10.004.
57 UNESCO (2024), Empowering Voices: Citizen-Generated Gender Data for Inclusive Governance
58 Ibid
59 George, Patrick. (2023). Inclusive, Trustworthy Data Governance in Africa - Designing governance frameworks tailored
for underrepresented regions.
60 Teanna Barrett, Chinasa T. Okolo, B. Biira, Eman Sherif, Amy Zhang, and Leilani Battle. 2025. African Data Ethics: A Dis- cursive Framework for Black Decolonial AI. In The 2025 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’25), June 23–26, 2025, Athens, Greece. ACM, New York, NY, USA, 16 pages. https://doi.org/10.1145/3715275.3732023
61 WHO (2016), Putting women first: ethical and safety recommendations for research on domestic violence against women: Ethical and safety recommendations for intervention research on violence against women. Building on lessons from the WHO publication
62 Adele V. (2022), A_study_on_information_privacy_concerns_and_expectations_of_demographic_groups_in_South_Africa
63 Appiah R, Raviola G, Weobong B. (2024), Balancing Ethics and Culture: A Scoping Review of Ethico-Cultural and Im- plementation Challenges of the Individual-Based Consent Model in African Research. Journal of Empirical Research on Human Research Ethics;19(3):143-172
64 OECD, (2021), Good Practice Principles for Data Ethics in the Public Sector,
65  AFIC (2024), Data is power but who controls it? https://www.africafoicentre.org/data-is-power-but-who-controls-it-dialogue-on-data-governance/
66 ibid
67 UNFPA (2014), Guide on the Gender Analysis of Census Data
68 Beegle, K., Serajuddin, U., Stacy, B., S Wadhwa, D. (2023). Missing SDG Gender Indicators.
69 Participant Uganda workshop
70 UNFPA (2024), Guide on the Gender Analysis of Census Data
71 Ibid
72 Kabir, Sajjad. (2016). Methods of Data Collection
73 Cobb, Curtiss. (2017). Answering for Someone Else: Proxy Reports in Survey Research
74 Ibid
75 Africa Development Bank (2016), Using data to close gender gaps and accelerate women’s empowerment in Africa
76 Open Data Watch and Data2x (n.d), Integrating Intersectionality in Data Systems: Prepared by Open Data Watch and Data2X A Practical Guide Across the Data Value Chain,
77 UNITED NATIONS (2024), Principles and Recommendations for Population and Housing Censuses,
78 UN Women (2022), Handbook on Gender Mainstreaming for Gender Equality Results,
79 Ibid
80 Spotlight Initiative (2022), Global Annual Progress Report 202
81 Digital Impact Alliance (2024), Effective Data Governance in Africa Demands Collaborative Growth.ADLI Helps Pave the Way.
82 African Union (2022), African Union Data Policy Framework
83 Participant _Senegal Workshop
84 Ibid
85 Susan Etlinger, Nanjala Nyabola,Teresa Scassa, (2021),How Women Are Shaping Technology and Data Gover- nance:https://www.cigionline.org/articles/how-women-are-shaping-technology-and-data-governance/
86 Baba Musami, Hauwa S Abdullahi, Muhammad. (2023). Women Participation In Governance: Prospects And Chal- lenges.
87 Participant_Uganda Workshop
88 Participant_Zambia Workshop
89 Temitope Ogunlela (2025), The Transformative Power of Networks: Advancing women Entrepreneurs in Africa
90 Ibid
91 Ibid
92 Ibid
93 Ibid
94 UNDP (2025), The power of networks: building connections, building a sisterhood
95 UNECA (2025), Mozambique hosts data governance workshop to strengthen national digital capacity
96 APHRC (2023), Strengthening Sub-National Data Value Chains in Sub-Saharan Africa
97 World Economic Forum (2024) Global Gender Report 2024
98 Femnet (2019), Gender Transformative Budgeting: A guide for Pan African Parliamentarians
99 Participant_Uganda