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Barriers to Data Access and Use for Women

Published onDec 28, 2019
Barriers to Data Access and Use for Women


  • Opening data is meaningless without its usage by women and other marginalised groups whose lives it impacts.

  • Women from low income groups, those in rural areas, indigenous women, women with disabilities, and those that speak underrepresented languages face intersectional barriers in being connected and using open data.

  • Women are poorly represented within government, corporates, and civil society that use open data and make policy decisions.

  • Very few countries have the necessary policy frameworks to lower the cost of data and improve digital literacy, knowledge, and skills in deprived communities.


Open data is not useful without meaningful usage by diverse groups of stakeholders. Users must include the target group represented in the data and the groups that advocate for them - in the case of gender open data, women, people from non-binary genders, and other marginalised groups. These groups often encounter economic, infrastructural, and sociocultural barriers in meaningful usage. Users of data within government, civil society and businesses are still disproportionately men, whereas women face barriers to their entry into tech and open data industries, as well as their use of civic tech and open data.1 Non-usage by critical stakeholders can undermine the value of open datasets, defeating the goal of increasing transparency of public and private systems. This entry seeks to discuss infrastructural and other barriers to the use of open data by women.

The Digital Gender Gap

Access to and use of open data is mediated by gendered structures of power and resource distribution.2 The “volume, frequency, and quality” of digital access varies significantly along gender, particularly in low and middle income countries in Asia.3 Known as the ‘digital gender gap’, this has been attributed to a number of reasons. The World Wide Web Foundation, in their report on open data for women in Africa identify four broad daily challenges that women face which limits their time, access and use of data, and the internet as a whole.4

As a result of women’s weaker economic position, they are less likely to be online.5 This is correlated with unequal distribution of financial resources, including income,6 and ownership of land and other economic assets.7 The proportion of unpaid care and domestic work done by women, often in addition to performing income-generating activities, constrains time available to invest in gaining digital skills.8 Research has also indicated sociocultural barriers to access for women, even in households where income barriers do not exist.9 Women are often not the primary owners of phones and digital devices when these do exist in the household.10

In another study on access to the internet, it was found that the most important socioeconomic drivers of the gender gap in ICT access are education and age which directly determine the level of access women will have to the internet.11 Power imbalances in the offline sphere, including that of gender, are refracted onto the digital space.12 The benefits of digital technologies are not evenly distributed between women - poor women are much less likely to have access to the internet due to high broadband prices and therefore less likely to use open data resources.13 The mobile-first growth in the Asia-Pacific region has brought many women online - but this does not lead to growth in use of open data as many applications are not optimised for phones.14

In the 2014 survey of the Alliance for Affordable Internet (A4AI), countries on average scored 2.73 out of 10 on a measure of concrete policy goals for gender equity in internet access and use.15 This indicates “little to no discussion on digital gender gap and possible responses”.16

In recognition of the importance of digital equality for socioeconomic growth and opportunity, affordable and universal internet access by 2030 is set as a target in the Sustainable Development Goals.17 This goal will remain unachievable as long as significant digital gender gap remains and therefore “closing the digital divide means closing the gender digital divide”.18

A major barrier in collecting open data on the digital gender gap is the source of data and research methodology. The supply-side data collected by the International Telecommunications Union, which is one of the primary sources of information on usage of mobile phones within national populations, does not enable gendered aggregation by basic indicators of use and access.19 This affects data on the digital gender gap in the Global South, as it is characterised by high phone usage.20 A demand-side survey funded by the International Development Research Centre has been instrumental in closing some of this data gap by collecting demand-side data from 16 countries across the Global South as data was collected both online and offline, allowing the disaggregation of data based on sex and thus providing an accuate picture of gender differences in access, and use in pre-paid mobile environments.21 However, this remains an expensive way to collect data on the digital gender gap.

Intersectional Digital Divide

When it comes to the digital divide, gender functions both as a dependent and independent variable, which is to say that women from marginalised groups face double or triple the barriers in getting connected. Geographical location, language skills, education and income levels, and disability can determine the extent to which communities have access to connectivity, with women in these communities facing higher barriers than men. There are also stark variations within the Asia-Pacific region, with high-income countries having better infrastructure and a larger proportion of population digitally connected than low-income countries.22 The top five most connected countries are New Zealand, Japan, Republic of Korea, Singapore and Malaysia, with upto 80 percent of their population connected, while the average connectivity in the region remains at 20 percent.23

The urban-rural digital divide in Asia and the Pacific is even worse than the gender digital divide, which makes creates further barriers for connecting women in rural areas.24 More than 70% of Cambodians, Indonesians, Burmese and Laotian people remain offline, largely from rural areas.25 Access to supporting infrastructure, such as stable electricity and data speeds is also critical in internet use26, and is also found to be poorer in rural and border regions - in Southeast Asia, 65 million people do not have access to electricity.27 Infrastructure in disaster-prone areas has to face natural phenomena, which makes access more unstable.28

Research has found that education and literacy plays a key role in access to and relevance of digital connectivity.29 In South Asia, it has been found that English language knowledge is a key “enabling variable” for internet use.30 Out of approximately 6000 languages spoken in the world today, 10 contribute towards 82% of content on the internet.31 This makes it much more difficult for other language-speaking communities to find relevant content on the internet, including open data and information that is available in a usable format. Income also remains a key determinant of digital access32, despite South Asia having some of the cheapest rates of data in the world.33 There are also severe accessibility barriers for people with disabilities in the Asia-Pacific region - this is particularly because connectivity in Asia has been mobile-first.34

National Policy Frameworks

The World Wide Web Foundation with A4AI have also attempted to outline a path to close the gender data gap.35 In order to close the gender digital divide, not only do countries have to adopt clearly outlined targets and strategies for improving internet access, they also have to adopt gender-responsive approaches to development and implementation of policy frameworks.36 Gender-responsive policy making identifies and prioritises the needs of and challenges faced by marginalised groups in the use of ICTs.37 Keeping this in mind, A4AI recommends an affordability target of 1GB of prepaid mobile data costing no more than 2% of the average per capita monthly income.38 This has also been adopted as an affordability target by the United Nations.39 Additionally, governments need to provide gender-responsive models of public access and infrastructure, design, development of affordable technologies and services.40

National ICT policies need to address digital gender gap.41 Of the 10 countries reviewed in the Digital Gender Gap Audit (2016), only 4 countries - Colombia, Nigeria, India, and Ghana, have “national or sub-national policies to increase access, training, and use of the web by women and girls”.42 Policy frameworks need to be designed to critically lower the cost of data, as well as simultaneously improve digital literacy, knowledge, and skills distribution across deprived communities.4344 Gender responsive open data policies can provide both policy and technical framework that could support and monitor government performance for improved service delivery.

Policy frameworks should ensure equitable digital access in a meaningful and safe environment for women and other marginalised groups. An example of such a framework can be found in the ‘Action Plan to close the Digital Gender Gap’ of the International Telecommunications Unit. The framework, which includes better access and meaningful use for women, and promoting more women in the technology sector, is designed to support SDGs by closing the gender gap.45 Finally, there is a need to better implement information disclosure law across government and private bodies to enable availability of data on the digital gender gap.46


Data does not only need to be representative of women and non-binary gender, it needs to be used by them as well. It has been observed that opening access to data tends to follow the power and structural dynamics of wider society wherein women and non-binary genders face marginalisation. Conversely, access and use of the internet in general and open data in particular are themselves an important factor to undo these power and structural dynamics and fight discrimination by influencing policy. The article discusses the ‘digital gender gap’ which is a consequence of such marginalisation. Equal access and participation in data generation and its use are imperative to achieve the target of closing the digital divide and achieving the targets of gender equality.

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