# Narratives and Counternarratives on Data Sharing in Africa

Rediet Abebe  University of California, Berkeley ,  Kehinde Aruleba
University of the Witwatersrand ,  Abeba Birhane  University College Dublin &
Lero ,  Sara Kingsley  Carnegie Mellon University ,  George Obaido  University
of the Witwatersrand ,  Sekou L. Remy  IBM Research - Africa and  Swathi
Sadagopan  Deloitte

(2021)

###### Abstract.

As machine learning and data science applications grow ever more prevalent,
there is an increased focus on data sharing and open data initiatives,
particularly in the context of the African continent. Many argue that data
sharing can support research and policy design to alleviate poverty,
inequality, and derivative effects in Africa. Despite the fact that the
datasets in question are often extracted from African communities,
conversations around the challenges of accessing and sharing African data are
too often driven by non-African stakeholders. These perspectives frequently
employ a _deficit narratives_ , often focusing on lack of education, training,
and technological resources in the continent as the leading causes of friction
in the data ecosystem.

We argue that these narratives obfuscate and distort the full complexity of
the African data sharing landscape. In particular, we use _storytelling_ via
fictional personas built from a series of interviews with African data experts
to complicate dominant narratives and to provide counternarratives. Coupling
these personas with research on data practices within the continent, we
identify recurring barriers to data sharing as well as inequities in the
distribution of data sharing benefits. In particular, we discuss issues
arising from power imbalances resulting from the legacies of colonialism,
ethno-centrism, and slavery, disinvestment in building trust, lack of
acknowledgement of historical and present-day extractive practices, and
Western-centric policies that are ill-suited to the African context. After
outlining these problems, we discuss avenues for addressing them when sharing
data generated in the continent.

Data sharing, data access, open data, storytelling, decolonial theory

††copyright: acmcopyright††journalyear: 2021††copyright:
acmcopyright††conference: Conference on Fairness, Accountability, and
Transparency; March 3–10, 2021; Virtual Event, Canada††booktitle: Conference
on Fairness, Accountability, and Transparency (FAccT ’21), March 3–10, 2021,
Virtual Event, Canada††price: 15.00††doi: 10.1145/3442188.3445897††isbn:
978-1-4503-8309-7/21/03††ccs: Computing methodologies Artificial
intelligence††ccs: Social and professional topics Government technology policy

##  1\. Introduction

Data sharing is often regarded as a crucial element of research and scientific
advancements, a hallmark of transparency, and a key to economic growth (Anane-
Sarpong et al., 2018; Batuo et al., 2018; Bezuidenhout and Chakauya, 2018).
Data sharing expands knowledge and contributes to a better science (Chawinga
and Zinn, 2019; Lemarchand, 2007; Sebake, 2013). Recent years have seen
increased global momentum for improving data sharing and, in some cases, a
push for open data and lowered barries to data access (Bezuidenhout, 2019;
Mwelwa et al., 2020; of Science of South Africa et al., 2019; Zaba et al.,
2013; Afful-Dadzie and Afful-Dadzie, 2017; Onyancha, 2016).111While data
sharing often focuses on facilitating ease of data transfers between
individual scientists, institutes, and/or organizations, truly open data goes
beyond that by making data ‘freely’ available for use to a wider-range of
populations, rendering it a public good. In this work, we primarily focus on
data sharing practices, although many of the insights we draw also apply to
arguments for opening data. However, concerns such as privacy, intellectual
property rights, organizational and structural challenges, cultural and social
contexts, unjust historical pasts, and potential harms to marginalized
communities all make improving data access a highly complex and at times
contentious issue (Afful-Dadzie and Afful-Dadzie, 2017; Bezuidenhout and
Rappert, 2016; Kaye, 2012; Makulilo, 2016).

Data sharing challenges are further exacerbated in the African context:
Historical and present-day colonial-era practices and ideologies force us to
confront a reality characterized by _data colonialism_ (Birhane, 2020;
Coleman, 2018; Mkono, 2019; Taiwo, 2010). Countless data sharing initiatives
as well as a growing enthusiasm for data sharing movements can be found
throughout the 54 distinct nations in the continent (Anane-Sarpong et al.,
2018; Batuo et al., 2018; Chawinga and Zinn, 2019; Tchamyou and Asongu, 2017).
At the same time, various obstacles limit equitable data sharing practices;
entire heterogeneous geographies of people have their data accessed and
shared, yet do not reap the same benefits as the data collectors and owners of
data infrastructures (Mwaka, 2017; Denny et al., 2015). These communities can
face harm as a result of their data being accessed, shared, and used (Munung
et al., 2016; Nyangulu et al., 2019). At its core, various structural and
relational challenges plague the relationships between entities based outside
of the continent and the African communities whose data is being accessed. The
continent’s plural and at times divergent norms, practices, and traditions
furthermore complicate the African data access and sharing ecosystem. In sum,
data sharing in Africa poses a unique set of challenges that remain
understudied.

Figure 1. Stakeholders in the African data sharing ecosystem. Those at the top
of the iceberg hold significant power and leverage in guiding data sharing
practices and policy compared to those in the hidden part of the iceberg.
(Image adapted from (D’Ignazio and Klein, 2020))

The African data sharing ecosystem involves numerous stakeholders, including
communities, companies, government bodies, policymakers, non-government
organizations (NGOs), data collectors, data labellers, data brokers, data
subjects, archivists, researchers, and many others (Adekunle et al., 2013;
Mwaka, 2017; Musesengwa et al., 2018; Swemmer et al., 2015). Responsible data
sharing requires a harmonious partnership between all stakeholders, both under
and on top of the iceberg, as depicted in Figure 1. Consideration of the
interests, values, and needs of all — and especially those whose data is being
collected — is a vital step in fostering responsible data sharing practices.
In many cases, however, we find that more powerful stakeholders wield
disproportionate power in driving the design, framing, and enforcement of data
sharing policies and practices; their values and interests dictate not only
the data sharing landscape, but also narratives around data access.

On the other hand, data sharing in the continent relies heavily on those in
the hidden part of the iceberg. Data is often extracted from these same
communities, and analyses of the data often have a direct impact on them.
Given the significant role of power asymmetries between these groups, data
sharing policies and practices that do not acknowledge such imbalances will
fail to capture all relevant perspectives. In this work, we examine this
dynamic data sharing landscape, its possible benefits and harms, and
challenges around data practices. Our work focuses on the following questions:
Who benefits from data sharing in Africa? What barriers exist in the data
sharing ecosystem, and for whom? How do entrenched legacies of power
disparity, colonialisms, ethno-centricisms, slavery, and Anglo- and Euro-
centrism present challenges in the data sharing ecosystem? If much of the data
sharing practice and initiative is shaped from the perspective of the Global
North, how then can we ensure that the narrative for Africa is controlled by
Africans? We tackle these questions guided by the experiences and perspectives
of African communities and initiatives, and especially those in the hidden
part of the iceberg.

Dominant narratives around data sharing in Africa often focus on a lack of
knowledge about the value of data and training, as well as insufficient
technological resources. This is often followed by _deficit narratives_
,222Deficit narratives reduce a group or culture to its “problems,” rather
than portraying it with the strengths, creativity, and agency of its people.
where discussions regarding data sharing in Africa revolve around issues of
hunger, illiteracy, unemployment, and poverty. In anchoring narratives around
these concerns — which are not unique to Africa and do not capture the full
scope of its people’s experiences — the strength, agency, and scientific and
cultural contributions of communities within the continent are minimized.
Community norms, values, and traditions are overlooked, and policies and
practice around improving data sharing focus on “fixing” the continent’s
problems. The perception of the dominant (often Western) narratives as the
standard comes at the expense of discarding local knowledge and expertise.
Furthermore, data sharing issues are discussed as a Global North/Global South
concern, ignoring plural norms, practices, and traditions that exist within
the continent, which themselves demand a thorough examination.

As we navigate this data sharing landscape, we counter these deficit
narratives and clichéd stereotypes with which the African continent is
frequently portrayed. In doing so, we hope to highlight overlooked imbalances,
inequalities, and injustices in the data sharing ecosystem, and to support the
development of policies and programs that will illuminate and mitigate them.
We counter these narratives through _storytelling_. We construct fictional
personas based on semi-structured interviews with data experts from the
continent, as well as our collective expertise in collecting, accessing, and
sharing data within the continent. Through these personas, we highlight
challenges faced by African communities in accessing and sharing data, as well
as the strategies they employ to insist on community-affirming data practices.

The stories also examine the power structures that affect if and how a
community benefits from transactions involving the use of their data. By using
these personas as touchpoints, we find that three overarching challenges —
power imbalances among stakeholders, disinvestment on building trust, and
disregard for context and local knowledge — drive inequalities and injustices
in the data sharing ecosystem. Through an analysis of these failures, we argue
that the policy and practice of data access and sharing must centre the needs
of those stakeholders in the hidden part of the iceberg. The values and
expertise of communities whose data is being collected and shared need to take
precedence in the development of data governance standards. Through our
discussions, we advocate for policies and practices that acknowledge and aim
to counter power asymmetries and structural obstacles. In presenting our
arguments, we also bring to the forefront rich research and scholarship on
this topic by African scholars.

##  2\. Background and Related Work

Data sharing and open data movements are gaining momentum globally (Knoppers
et al., 2011; Bezuidenhout and Chakauya, 2018; Chawinga and Zinn, 2019;
Onyancha, 2016), including in the context of the African continent
(Bezuidenhout, 2019; Anane-Sarpong et al., 2020; Chiware, 2020, 2020). Some of
this push within the continent comes from funding agencies and government
requests for researchers to archive and share data, including open data
portals from countries such as Kenya, Ghana, Nigeria, and South Africa (Dinah
et al., 2019; Iglesias, 2019; Bello et al., 2016; Abubakar, 2019). The call
for data sharing is found in various researching fields across the continent,
including in the environmental, geospatial, agriculture, health, and
biomedical sciences (Sebake and Coetzee, 2012; Denny et al., 2015; Bangani and
Moyo, 2019; Schaepman et al., 2007). The intergovernmental Group on Earth
Observations (GEO) (AfriGEOSS, [n.d.]), for example, runs initiatives focused
on Africa (AfriGEOSS) with the aim of enhancing earth observation data
production, management, and sharing. Similarly, the digitization and sharing
of soil data are believed to play a crucial role in a number of fields,
including food security, health, hydrological modelling, and climate change
(van Zijl, 2019; Janion-Scheepers et al., 2016; Tesfaye et al., 2019; Gebru et
al., 2021). Citing dialogues during a South African Soil Information Workshop,
scholars identify the expansion of soil databases and data sharing as
important developments for soil science and environmental fields (Paterson et
al., 2015; Belete et al., 2020). The biomedical sciences also echo the call
for data sharing (Adebamowo et al., 2018; Glennon et al., 2020; Bezuidenhout
et al., 2017; Denny et al., 2015; Mutuku and Mahihu, 2014). In a recent paper,
Martin et al. (2018) have called for global genomic data sharing and discussed
the urgent need for more genetic data studies, while also arguing that African
populations are not represented in global genomic databases. Although the
authors raise crucial concerns, including the unsuitability of the “European
method” to study heterogeneous African populations, they contend that data
sharing is vital for a fair representation.

One of the strongest arguments for rethinking how data is shared comes from
the Academy of Science of South Africa, which created the African Open Science
Platform, a project led by the South African Department of Science and
Technology (of South Africa, 2018). This project emphasizes the need to
increase awareness, accessibility, and visibility of African science and data.
It calls for data and science to be as open as possible, with the aim of
stimulating interdisciplinary use of data, identifying research areas for
further exploration, and averting the duplication of research.

The questions of data sharing and management are becoming ever more pertinent
to the continent. In one of the key gatherings in 2018, various stakeholders
and government officials from Botswana, Ethiopia, Kenya, Madagascar, South
Africa, and Uganda discussed and formulated national policies (Veldsman and
Smith, 2018). With increased demand for statistical data across many African
countries, many data organisations have been established to promote data
accessibility and open data (Zaba et al., 2013; Afful-Dadzie and Afful-Dadzie,
2017; Bezuidenhout, 2017; Chiware, 2020; Onyancha, 2016). For instance, the
African Development Bank Group developed a statistical open data portal known
as Africa Information Highway (AIH) portal (for Africa Portal, 2020). AIH
links all African countries with the aim of increasing public access to
statistics across the continent, while also helping these countries improve
data management, data quality, and sharing/dissemination. Similarly, Kenya
Open Data (Mutuku and Mahihu, 2014) is a portal that provides public access to
several governmental datasets curated in different categories at no cost. This
platform aims to support the government’s commitment to transparency and data
sharing between government offices and various stakeholders.

Despite extensive calls for data sharing and open data, backed by various
initiatives and organizations, data access remains relatively limited within
the continent (Staunton et al., 2019; Chiware, 2020; Dlodlo et al., 2012;
Tessema, 2019). Bangani and Moyo (2019), for example, compare data sharing
practices among researchers in South Africa to researchers in countries such
as France, the United Kingdom, and Turkey. The authors state that most
researchers in South Africa are not interested in sharing their data and
prefer to use data generated by others; only 19.4% of South African
researchers indicated that they currently share their research data with
others. As reasons for their reluctance, these South African researchers cited
worries ranging from unethical use or misuse to lack of resources. In extended
fieldwork with biochemistry laboratories in sub-Saharan Africa, Bezuidenhout
and Rappert (2016) find that scientists opt for closure over openness with
regard to their data. The reasons put forward include inequalities in research
environments which, if not examined critically, perpetuate disparities.
Furthermore, an overwhelming number of researchers in Africa lack the funding
necessary to make their data open to the wider community (Bezuidenhout and
Chakauya, 2018). Bezuidenhout and Chakauya (2018) reporte a lack of financial
investment in physical infrastructures could make a researcher’s data
unavailable, especially for critical clinical research. Barnes et al. (2019)
agree that funding is a panacea for doing quality research and promoting data
openness in low-resource settings. We note, however, that enthusiasm levels
for sharing data vary from field to field (Serwadda et al., 2018; Dlodlo et
al., 2012; Tessema, 2019; Anane-Sarpong et al., 2018).

Obstacles to data sharing are not only financial or infrastructural, but also
extend into the political sphere. Bezuidenhout and Rappert (2016) raise a
fundamental question regarding open data and open science. Their study shows
that data sharing and open data practices are informed by Western
perspectives, and are driven by the contextual issues of Western researchers.
Given that different circumstances will give rise to different issues, they go
on to ask whether the value attached to data sharing is a specifically Western
one. The question becomes: Should the African continent aspire to develop its
own data sharing policies and initiatives grounded in its distinct values,
context, and communal culture? This perspective takes data sharing challenges
beyond the financial and technological realms and suggests the need for a
fundamental rethinking. Yilma (2013), for example, has proposed the absence of
a strong political will as a major barrier to data sharing in Africa. Likening
data sharing practices to aid programs, Yilma states, “any type of aid program
that does not lead eventually to self-sufficiency is actually destructive,
just like welfare, and that is what has happened with many aid programs in
Africa” (Yilma, 2013).

##  3\. Storytelling as a Methodology

> _“Stories are just data with soul”_ – Brene (2010).

In this section, we illustrate the importance and relevance of storytelling to
our work. We first trace its historical significance to the African continent
before discussing our methodology for creating personas aimed at presenting
counternarratives.

###  3.1. Storytelling in Africa

Oral culture and the African continent are profoundly linked in most spheres,
from poetry and dance to philosophical traditions (N’Sougan Agblemagnon and
Pleasance, 1971; Olaoluwa, 2008; Soyinka, 2020; Tuwe, 2016). Many
philosophical ideas have deep roots in the African continent (Henshilwood et
al., 2002; McDougall et al., 2005; Rananga, 2008; Mojapelo, 2020). Ancient
Egypt, for example, marks the oldest known philosophical tradition
(Ohaegbulam, 1990; Kurewa, 2016; Ilahiane, 2017). Furthermore, in pre-colonial
Africa philosophical practices among indigenous peoples took the form of oral
traditions (Seroto, 2011; Imbo, 2002; Adeyemi and Adeyinka, 2003). Emphasizing
the distinctness of oral traditions to the African continent, Okot p’Bitek
(P’Bitek, 1975) contends that oral practices are much more immediate and
powerful. In Oral Traditions as Philosophy: Okot p’Bitek’s Legacy For African
Philosophy, Imbo (2002) further demonstrates the unique significance of oral
traditions in African philosophy.

Storytelling is one important method for indigenous research, and a tool to
legally claim the right to local voices through which narratives are validated
(Delgado, 1989; Gachago et al., 2014; Mataira, 2019; Inamara and Thomas,
2017). Making local communities the focal perspective of shared knowledge
through storytelling counters histories of colonialism, knowledge produced for
colonial regimes, and the power dynamics silencing indigenous expertise (Agan,
2006; Merolla, 2019; Shizha, 2014; Ayodele, 2020). In South Africa, for
example, the Truth and Reconciliation Commission (TRC) incorporated
storytelling – songs, poems, and oral literature – into the official legal
process of speaking aloud marginalized experiences of Apartheid (Oboe, 2007).
In Uganda, the National Education Ministry mandates storytelling as part of
the required national curriculum. The Ugandan Education Ministry’s curriculum
reform since independence has likewise re-introduced storytelling by law.
These reforms are focused on re-instituting local knowledge and teaching
methods, as well as countering the influences of former colonial powers
(Ssentanda and Andema, 2019; Anyeko and Hoffmann, 2020; Mudondo, 2020; Ngaka,
2020). The African StoryBook Project333https://www.africanstorybook.org/, a
repository of stories in local African languages, illustrates the value of
both storytelling as a method of knowledge creation and data sharing practices
driven by community needs. This open source repository of digital books
written in local African languages allows the re-purposing, scaling, and
sharing of content from the platform, helping the Ugandan Education system to
make the switch to teaching in local languages444Although the African
StoryBook Project can be seen as a powerful example, it is also important to
acknowledge that limitations and challenges remain for the Ugandan Education
system. For instance, the harms of colonial regimes are not extinguished
immediately upon instituting policy reforms. The dynamics of the global
political economy also continue to pressure national education systems to
emphasize teaching and establishing grading or progress standards for students
that are measured by English language competency, e.g. standardized tests.

African researchers and scientists have called for the international
scientific community to embrace indigenous research (Corntassel et al., 2009;
Baskin, 2005; Chilisa, 2019). The call acknowledges how research design (e.g.
how “validity” is determined) could reflect Western values, and thus, co-opt,
erase, and/or circumvent legitimate means of expressing knowledge.
Problematically, many Global North research methods characterize local ways of
creating and validating knowledge as scientifically invalid (Dyll-Myklebust,
2014; Wuni et al., 2019; Kiraka et al., 2020). Computational journal and
conference reviewers also insist on Global South authors contextualizing
research, including methods, in relation to the Global North. We argue this
demand erases and marginalizes local expertise.

###  3.2. Storytelling of African Data

Inspired by the role of storytelling in the African context, we illuminate
challenges faced when accessing and sharing data in the African continent from
African perspectives. We do so through personas created to portray recurring
challenges we encountered throughout our interviews, as well as our
experiences of collecting, accessing, sharing, and using data generated in the
continent.

We constructed the personas through an iterative process based on semi-
structured interviews with ten African data experts. Our interviewees included
individuals working in universities, governments, startups, and think tanks,
and we focused on data collected and shared for research or policy purposes.
We first developed open-ended questions, guided by our experiences observing
and actuating data sharing practices on the continent. The interviews were
recorded with permission from the interviewees, after which we manually
transcribed the audio recordings. Next, we identified and abstracted central
themes, challenges, and concerns expressed by the interviewees. Any
information that could be used to identify our interviewees, institutions,
government bodies, or communities was removed. In addition, we only took a
particular challenge as the inspiration for the creation of a persona if that
challenge appeared in at least three interviews. These decisions allowed us to
preserve the privacy of both the individuals we interviewed and the
communities of concern, while still creating space for discussing common data
sharing practices that are not affirming of the needs, values, and concerns of
those on the bottom of the iceberg. In response to these privacy concerns, we
did not incorporate any direct quotations from our interviews into the
personas, but we plan to include data of this kind in subsequent publications.

Each persona consists of two to three core challenges. Over the course of
multiple meetings, we discussed and debated the efficacy of each persona in
portraying the challenges we would like to elucidate. In our discussions, we
primarily focused on the following key questions:

  1. (1)

Do the personas elucidate the intended data sharing challenges, and if not,
why not? How can we better bring these challenges to the surface?

  2. (2)

Which data sharing challenges are more “familiar” to a diverse audience,
including many researchers from the Global North? In what ways should we amend
the personas to hone in on what challenges may be unique to the continent?

This process allowed the personas to evolve and solidify over time. We
rebalanced the emphasis on various themes in the personas at times by adding
details from more interviews or removing details from interviews that
obfuscated the key challenges we would like to highlight. In this paper, we
present a sample of three personas that illustrate the three key overarching
challenges we found in our work. Additional personas and details about this
project are shared on our project
page.555https://www.md4sg.com/workinggroups/GlobalSouthData.html.

##  4\. Personas

> “Proverbs are horses on which words ride, when words are lost [i.e. when the
> truth of a matter is elusive], it is proverbs we use to search for them
> [i.e. proverbs help us to solve an intractable problem]” – Agbájé (Agbájé,
> 2002).

The personas we present below present recurring themes we encountered in our
interviews and subsequent discussions. These stories are not meant to reflect
the experiences of any single individual, community, company, or country, but
rather to gather evidence and shed light on recurring barriers. Since these
stories are based on aggregate information, they call attention to common
social issues while respecting sensitive dynamics – such as concerns about
privacy and retaliation – that may make interviewees, and indeed many across
the continent, vulnerable when sharing these experiences. As such, these
stories convey and conceal truths at the same time.

On Good and Harm
Themes: power imbalance, data colonialism

Context:
DrinkUS West is a Europe-based non-government organization (NGO) working on
sustainable access to water and health. DrinkUS hopes to support people in
Buranda – home to the yetet’ebek’e community – by improving access to clean,
potable water. It also plans to deploy and test new water accessibility
technology and online monitoring of resources.

Data needs:
To provide adequate services and assess its impact, DrinkUS seeks data about
people’s day-to-day water use habits and experiences through surveys. In the
survey, DrinkUS researchers ask individual respondents about their
demographics (age, gender, income, marital status, number of household members
and children), discretionary spending habits (ownership of computers, mobile
phones, leisurely activities), and water use habits (such as how water and
utilities are accessed, and the respondent’s knowledge of potable water
accessibility). Additionally, DrinkUS seeks country-wide data on demographic
patterns as well as outcomes related to health, education, and poverty levels
over the past decade. It gains access to this data from the Buranda Health
Ministry.

By using these two data sources, DrinkUS aims to estimate demand for potable
water, determine prices, and predict the impact such a service may have on the
health and economic welfare of the community. Additionally, the NGO assesses
technologies that could be used to monitor and manage water access. As the NGO
is keen to engage survey participants in future opportunities, it collects
contact information such as the names, addresses, and phone numbers of
participants. DrinkUS incentivizes each respondent by paying the equivalent of
$5 U.S. dollars in Kwacha, the local currency, for completing the estimated
30-minute long survey to improve survey completion rate. From this data,
DrinkUS researchers compile and infer which members lack access to potable
water, what community members can afford to pay, and who is most at risk for
water-related health impacts and/or disease. They combine these results with
data obtained from the Buranda Health Ministry to gain deeper insights into
the impact of access to potable water. This work is later published as a
research paper at a top-tier international conference on data science for
social good.

Data sharing challenges:
While employees at DrinkUS meticulously checked their survey design, they did
not seek adequate feedback from the yetet’ebek’e community beyond a few
initial meetings. The yetet’ebek’e community is not treated as a mutual
partner in the broader project design. In fact, there is an implicit
assumption that improving water access for the community is an adequate
benefit, and that DrinkUS is therefore justified in collecting and owning the
survey data. Further, since DrinkUS is a world-renowned NGO working in
partnership with the Burandan government, it wields significant power over
members of the yetet’ebek’e community. Even the pay incentives, which may be
negligible for the NGO, are significant due to currency exchange rates,
further highlighting a power imbalance.

Given that the NGO proceeded without consulting the community, it likely
failed to grasp all of the central issues and potential harms from the
perspective of the community. Sharing their research findings publicly,
including their predictions about which geographic locations in the
yetet’ebek’e community were at risk for water-related disease, put the
community at risk, as many belong to marginalized ethnic groups. Such
findings, even shared in aggregate, can reveal information on the community as
a whole. While notions of privacy often focus on the individual (Horvitz and
Mulligan, 2015; Kostkova et al., 2016), there is growing awareness that
collective identity is also important within many African communities, and
that sharing aggregate information about communities can also be regarded as a
privacy violation (Enyew, 2016; Namara et al., 2018).

In addition, given the partnership with the Burandan government and poorly
defined protocols around data sharing and use, survey participant data was
shared with government officials, including data about household composition
and reported or predicted health challenges linked to potable water access.
While the researchers vetted their questions for survey design validity, they
did not seek active involvement from the yetet’ebek’e community to discuss
whom the data can be shared with and for what purposes. DrinkUS also failed to
solicit feedback on the broader project design, data ownership and its use
beyond original scope of work, and research procedures. This disempowerment of
local communities in the decision-making process introduced trust issues both
with the NGO as well as with the Burandan government, which has been known to
engage in open data sharing practices with large NGOs and institutions. Local
communities, on the other hand, cannot access their own data with the same
ease.

The Journey of African Scholars
Themes: trust, awareness

Context:
A doctoral candidate from Bozatta researching in Nova Africa wants to collect
soil samples from several Nova Africa provinces for her research. Her study
aims to investigate the fertility of soil samples, which will inform key
stakeholders, such as the Government and NGOs, to find the best approaches to
assisting farmers.

In another case study, a doctoral candidate is researching the prevalence of
gender-based violence in Nova Africa. The study is targeted towards raising
awareness of gender-based violence prevalence, which remains a profound and
widespread problem in Nova Africa.

Data needs:

Case 1: Soil and apartheid

The researcher has outlined critical steps to conducting the soil fertility
test, using techniques such as sampling, analysis, interpretation, and
recommendation. All of these methods are essential for estimating soil
fertility. Enthusiastic about undertaking her research, the researcher aims to
collect these samples to determine soil fertility, nutrient deficiencies, and
recommendations, such as selecting the most favourable fertilizer plan to
increase farmers’ productivity. The information gathered from the study will
be used to create an effective fertility management program and provide
findings to the public through her dissertation and institutional public
databases.

Case 2: Gender-based violence
The researcher aims to collect this data and create a data platform to present
gender-based violence cases within provinces in Nova Africa. The tool will aid
data visualisation of these cases and will be available to the broader public.
The researcher understands that her work is focused on a pressing issue:
Gender-based violence remains a persistent problem, requiring attention from
multi-faceted responses and commitments from the government, civil society,
and other citizens. In particular, the government does not keep track of data
on the prevalence of gender-based violence, despite desire to work towards
protections for the vulnerable. The researcher’s work aims to narrow this data
gap.

Data sharing challenges:
In Case 1, in an attempt to collect soil samples, the researcher learns that
farmers are not enthusiastic about sharing this information, but she is unable
to understand why. After months of attempts, she eventually learns from her
colleagues that farmers have collected such data for their own internal
purposes, and use it to organize within their communities. The researcher
attempts to instead obtain this data, assuming that the farmers’ reluctance
may be partially due to replication of efforts. She eventually learns that the
farmers are reluctant to share any information due to fear that the government
might want to claim ownership of their lands. Collection of such data is a
challenge for local researchers as well. This issue is exacerbated by the
history of a former apartheid regime, under whose reign land grabs were
widespread, impacting Black Nova Africans primarily. Since sharing data can
lead to forfeiture of land rights, trust is a central issue for the farmers in
deciding how much information they share and with whom.

In Case 2, during the process of conducting the research, the doctoral
candidate experiences a few unexpected encounters and shares them with some
colleagues from Nova Africa. She tells them that many participants became
emotional when sharing their experiences, and asked that the session be
discontinued. One participant even questioned why the interview was so
intrusive, and decided not to share further information. Her officemate tells
her that in Nova Africa, it is challenging to convince participants to release
information, especially as a foreigner. There is a perceived notion that
foreigners are here to steal from them, whether that be data or resources.
This, she learns, is in part reflective of and caused by divisions across
communities in Africa due to colonialism. Another colleague advises her that
some participants might seek secluded venues that are secure for sharing
experiences in most rural areas, but that building trust is crucial,
especially as an outsider of this community.

Young researchers working across different African countries may encounter
challenges when trying to collect, access, and share data. This challenge is
particularly stark when the researcher is not a local to the region or
community in which the data is being collected. Differences in languages and
cultures, as well as imbalances in trust and power, breed suspicion about
motives, impeding data access and sharing. With more than 1500 languages
spoken across the African continent, locals residing in rural areas are more
likely to communicate in their dialect, with potentially little or no
understanding of national languages. This concern may, at times, stand in
contrast to the fact that there is a pressing need on high-quality data to
understand the prevalence and impact of issues such as gender-based violence,
among numerous other forms of injustices and discrimination.

Discussions on data sharing in the African context often treat the continent
as a monolith and frame problems as a Global North/Global South issue.
However, the complex data sharing ecosystem can lead to challenges even for
those based in the continent. We further find that many issues with power
imbalances and trust can be traced back to the impact of entities based
outside of the continent. We see, for instance, that certain hesitations with
sharing data are rooted in colonial-era extracting practices whose impact can
be felt to this day. Numerous efforts to mitigate inequalities in data access
and sharing in the continent, and especially those driven by initiatives
outside of the continent, may not be attuned to the complex data landscape
resulting from a diversity of needs, priorities, and experiences of those in
the continent.

Livestocks and Livelihoods
Themes: data infrastructure, awareness

Context:

A researcher in Wolonda receives a two-year grant from a large foundation from
the Global North. The research project outlines an ambitious goal of ushering
in prosperity for the livestock farmers by making the mainstream markets work
for them.

Data needs:
The researcher outlined his intentions to collect various types of
data,including genomic data of crops and livestock and enterprise data for the
farm. The genomic dataset would help determine if the right crops were being
planted and the right animal breeds being reared to support the production
system. It would help provide the farmers vital intelligence on susceptibility
of their crops and animals to diseases and performance of their farm against
aggregate data. The project was structured as a donor-funded research
endeavor, with clear data collection and analysis objectives. Yet no protocols
for data storage and scope of use were defined, and there were no clear
guidelines on whether the data can be shared with third parties. Furthermore,
scant information was provided as to if and how the collected data would be
used beyond the time period of the donor-funded project.

As expected, the researcher and his team diligently collected the genomic data
as well as the farm data from a cluster of villages in several counties of
Southern Wolonda. The data collection process was, however, more challenging
than originally anticipated. Even with a local team well-versed in the norms
and practices of the region, farmers seemed skeptical to give up their data.
Slowly, as the end of the two-year grant period approached, the data
collection exercise also came to a close.

Data sharing challenges:
Encouraged by this newly collected and valuable dataset, a research team
established a for-profit company using the data collected as part of the
research project. In its mission statement, the company articulated the need
for precision agriculture in today’s data-rich environment as an enabler of
better agricultural practices. The source data on which the company was built
came from that dataset which was collected as part of the original research
project. In addition, due to infrastructure challenges, the data is now housed
in a data center at a University in the Eastern United Provinces, an
influential country in the Global North which is also home to the foundation
that originally funded this research.

The company has set its sights on expanding across Wolonda. Even though the
trust established with the farmers in Southern Wolonda has eroded due to the
actions of the researcher, he is confident that other farmers will see the
potential of his data engine and believe in the power of its predictive
analytics.

Foundations in the Global North may be eager to fund data collection projects
in an attempt to create an oasis in regions perceived to be data-starved – to
bridge data gaps and inequalities that appear to be merely inefficiencies.
Yet, as is the case in this scenario, the lack of forethought into the ethical
use of data – not only during the lifetime of the project, but also thereafter
– can create irreparable harms to communities’ well-being and make it
difficult to build partnerships based on respect and mutual trust. This above
case may alienate the farmers, precisely the people whom this project was
ostensibly seeking to support.

##  5\. Data Sharing Challenges

As the personas in the last section show, obstacles, issues, and challenges of
data sharing concerning the African continent are multifaceted. Questions such
as, ‘Is data sharing beneficial? Valuable?’ need to be contextualized by
subcommunity: We need to also ask ‘for whom?’ Throughout this work, we have
examined such questions in a manner that is informed by the perspective of the
stakeholders at the bottom of the data ecology chain – the hidden part of the
iceberg. There are numerous causes for challenges in this ecosystem. In this
section, we focus on three broad and interrelated challenges that surfaced
from our interviews and research. In particular, we explore: power
asymmetries, issues of trust, and the need for contextual knowledge.

###  5.1. Power asymmetries

Historically, traditional colonial powers sought unilateral domination over
colonized people through control of socio-economic affairs and the reinvention
of social orders for their own benefit (Okinedo Omovutotu and Mwiza, 2019). In
the current day-and-age, when data and digital technologies are powerful
instruments, colonial-era oppression has been reincarnated in various data
practices, including data collection, sharing, and analysis (Birhane, 2020;
Kimani, 2019). The search for data accumulation, especially with regard to
Western technology monopolies — both the scale as well as the manner in which
it is being collected — have raised questions regarding unprecedented wealth
accumulation and power struggles. Currently, a significant proportion of
Africa’s digital infrastructure is controlled by Western technology powers
such as Amazon, Google, Facebook, and Uber. Traditional colonial powers
pursued colonial invasion through justifications, such as “educating the
uneducated.” Data accumulation processes are accompanied by similar colonial
rhetoric, such as “liberating the bottom billion,” “helping the unbanked,”
“connecting the unconnected,” and using data to “leapfrog poverty.” However,
this rhetoric may not only preserves historical coloniality (Mohamed et al.,
2020) dressed in data, but also perpetuates deficit narratives. These
objections have been articulated by scholars and technologists within the
continent. For instance, Kimani (2019) writes:

> “I find it hard to reconcile a group of American corporations, far removed
> from the realities of Africans, machinating a grand plan on how to save the
> unbanked women of Africa. Especially when you consider their recent history
> of data privacy breaches (Facebook) and worker exploitation (Uber).”
> (Kimani, 2019)

Colonial legacies and power imbalances embedded in data practices may appear
less obvious and more nuanced within scientific research settings (Ashcroft et
al., 2013). Within the context of global health research, there has been
growing concern about power imbalances in authorship, which has negatively
affected how research undertaken by local researchers in low-income and
middle-income countries (especially in Africa) is perceived (Abimbola, 2019).
Academics in the Global North are bestowed with the power to define what
constitutes “legitimate knowledge,” “good research,” “standard method,” or a
relevant and worthwhile problem. As a result, African researchers are left
little room, if any at all, to compete at the global stage, even in matters
concerning the African continent. Following extensive analysis of interviews
with senior university research managers in Zimbabwe, and on a public
roundtable on Structural Inequalities in Global Academic Publishing, Jeater
(Jeater, 2018) finds that “When we ask who gets to represent the ‘African
perspective,’ we find it is decreasingly un-African.” Resource inequalities,
hegemonic academic standards that undervalue Southern research traditions, and
the unilateral power Northerners hold to validate research, all contribute to
structural obstacles that amount to systemic exclusion of African scholarship
from global health research. In a data ecosystem built on such firm yet
invisible power asymmetries, stakeholders already in a position of power not
only benefit the most, but also make data accessibility inequitable.

Imbalances in authorship and power asymmetries constitute a continuation of
the colonial project in global health research, creating fundamental trust
issues concerning data sharing. Underneath power asymmetries in global health
research partnerships between researchers from the North and South, lies what
Abimbola (Abimbola, 2019) calls “the foreign gaze.” In his analysis of this
concept, Abimbola asks questions such as “who we are as authors, who we
imagine we write for (i.e., gaze), and the position or standpoint from which
we write (i.e., pose).” Furthermore, power asymmetries which occupy an
important space around trust and data sharing often operate in invisible ways
and take many forms.

In a similar study that explores power imbalances between the global North and
South, using Zambia as a case study, Walsh et al. (2016) report that power
imbalances and inequalities manifest at all stages of research. This includes
everything from funding to agenda setting, data collection, analysis,
interpretation, and reporting of results. Looking at the underfunded Zambian
health research, where up to 90% of the funding for health research comes from
external funders (Walsh et al., 2016), the bargaining power rests with the
funders with little room for negotiations for Zambian scholars. Power
asymmetries are also observed in the personas above. In “On Good and Harm”, we
find the European NGO at the top of the power hierarchy making key decisions
regarding the data concerning yetet’ebek’e communities. Similarly, in the
“Livestocks and Livelihoods” persona, the foundation from the Global North
which provided grants dedicated to research in Wolonda holds much greater
authority and power compared to the villagers who are the source of the data.

Power asymmetries, historically inherited from the colonial era, often get
carried over into data practices and manifest themselves in various forms,
from imbalanced authorship to uneven bargaining powers that come with funding.
Having said that, power asymmetries are not limited to historical contexts
only. Within a given research project, for example, one can observe that power
asymmetries exist between project managers and data analysts; data analysts
and data collectors; data collectors and research participants. All these
factors are contingent on various caveats and implications for trust impacting
data processes from data quality to data sharing. Examining data production
and consumption process in the context of Malawian demographic survey, Biruk
(Biruk, 2018) makes these power asymmetries, hierarchies and structural
inequalities visible. Although obscured by partnership rhetoric, Malawian
demographics mapping in fact embodies structures with unequal division of
labor. Biruk explains:

:

“[B]eing on the ground in the field has the largest effect on data but—from
the perspective of researchers—the activities of fieldworkers are framed as
menial labor performed by easily replaceable and interchangeable individuals.
The local expertise they offer, then, is not in designing research or writing
proposals but comes as an additive to a project conceived in a distant office.
These hierarchies are embedded in political-economic structures that privilege
the knowledge work that is the purview of Western academic researchers over
the so-called unskilled labor performed by field workers. Meanwhile, Malawian
research collaborators occupy a middle space that is both constructed by and
fraught with power and economic inequalities.” (Biruk, 2018)

###  5.2. Trust

> “Data often move at the speed of trust.” – Hamilton and Hopkins (Rasmussen
> and Goodman, 2018)

Sharing data between different stakeholders hinges on trust. Trust is the
fundamental component of all relationships in a data sharing ecosystem. While
trust, or lack thereof, has been identified as a key challenge that hampers
data sharing (Colquitt et al., 2007; Jao et al., 2015; Adogame, 2014; Serwadda
et al., 2018), there remains much to be examined about the role of trust and
how it manifests in relationships between various stakeholders in the African
data sharing ecosystem. Data sharing practices which operate in the absence of
knowledge of local norms and contexts contribute – albeit indirectly – to the
erosion of trust among stakeholders in the data sharing ecosystem. Initiatives
coming from outside, with their own assumptions, interests, and objectives,
tend to be met with suspicion by local communities. The persona on “Soil and
Apartheid” captures this in a stark manner; due to the apartheid regime, the
doctoral researcher finds that Black farmers in Nova Africa suffered unjust
land grabs. Such historical injustice plays out in the farmers’ reluctance to
share soil data due to lack of trust.

Resource inequalities and colonial oppressive histories instill deep mistrust
towards open data and data sharing initiatives. Although African researchers
are generally supportive of data sharing, they are considerably less
enthusiastic about open data expressing concerns that open data compromises
national ownership and reopens the gates for “parachute-research” (i.e.,
Global Northern researchers absconding with data to their home countries).
Such concerns are not unwarranted. In fact, the findings from a recent study
from Mbaye et al. (2019) affirm this fear. Mbaye et al. (2019) performed a
systematic review examining African author proportions in the biomedical
literature published between 1980 - 2016, in which research was originally
done in Africa. The authors found that African researchers are significantly
under-represented in the global health community, even when the data
originates from Africa. A common threat is parachute-research, in which non-
African researchers benefit from data sharing and open data, are afforded the
opportunity to narrate African stories (in some cases also contributing to
deficit narratives), and publish scientific work using African generated data
available through open access initiatives – all while ignoring the
contributions of African communities and scholars (Kraemer et al., 2020;
Yozwiak et al., 2016; Moroke, 2015; Mathebane, 2017). Recent work within the
medical sciences published on the Ebola outbreak in the Democratic Republic of
the Congo can be cited as a prime example in this regard.

Ideal data sharing initiatives, policies, and principles weigh the benefits
and potential risks, and strive to find a reasonable balance. Benefits and
risks also vary depending on the types of data being shared. For example, the
use of genomics data poses the potential for far more detrimental risk to the
individual providing the data, to the researcher, to the institution, and to
the community compared to soil data. The issues of trust as a challenge to
data sharing, likewise, vary in degree depending on the data in question.
Trust is a relatively significant challenge to sharing sensitive biomedical or
health data and less significant when it comes to, for example, environmental
sciences data. Noting this concern, Walport and Brest (2011) emphasize,
“people often agree to provide sensitive data because they trust the
researcher and believe the researcher would not use the data in a way that
would be harmful towards them. However, there is a concern that the trust may
not carry over when the data are shared”.

###  5.3. Contexts and local knowledge

Contexts are a crucial element to making sense of data and data sharing. Yet
data – within data science and machine learning, particularly – are often
stripped away of contexts (Magrin and Van Vliet, 2009; Cini, 2019; Misago,
2019). In the process of data cleaning, for example, information that provides
contexts about the specific background from which data are collected and how
datasets are structured can be lost (Adeola, 2020). The importance of context
for datasets has been explored by scholars, such as Loukissas (2019),
according to whom, we should shift into thinking in terms of data settings
instead of datasets. Contexts are crucial to understanding data fully; data
sharing practices that discard contexts risk becoming irrelevant and
potentially harmful to local communities, as we see in each of the above
personas.

Consequently, the context of the data itself – which provides a complete image
– and awareness of local norms, cultures, and histories constitute crucial
elements in a responsible data sharing practice. Thus, for data sharing
practices to benefit the underserved, such groups’ welfare and interests need
to be placed at the center stage. However, our interviewees nearly unanimously
agree that there remains a lot to be done to acknowledge and incorporate the
interest, norms, and context of these below the iceberg in Figure 1. In fact,
oftentimes, certain groups such as data subjects are hardly recognized as
stakeholders at all (Alaneme and Okotete, 2018; Gillwald, 2020; Keane et al.,
2017).

We see various levels of disregard for context and local norms displayed in
all the personas portrayed in the previous section. In ”On Good and Harm”, the
failure to ground data collection in communal understanding of privacy, for
example, resulted in the NGO exposing yetet’ebek’e community to various risks
in the process of data sharing. Lack of common language and understanding of
local norms creates a challenge for intra-continental data practice, as shown
in ”The Journey of African Scholars.” In both cases, the doctoral candidate
faced difficulties understanding the local norms, which played a role in the
community’s lack of trust towards her. Similarly, in the ”Livestocks and
Livelihoods” persona, we observe that the funding foundation (from the Global
North) failed to consider the context in which the data was collected. In
summary, data sharing calls that are not aware of local norms, contexts, and
culture, when imposed from the outside, constitutes a form of Western-centrism
and colonialism.

##  6\. Discussion

Returning to the question “is data sharing good/beneficial?” we argue that
responsible data sharing practices must, first and foremost, benefit local
communities and experts, with a focus on those at the bottom of the iceberg.
In recent years, the African continent as a whole has been considered a
frontier opportunity for building data collection infrastructures. The
enthusiasm around data sharing, and especially in machine learning or data
science for development/social good settings, has ranged from tempered
discussions around new research avenues to proclamations that “the AI invasion
is coming to Africa (and it’s a good thing)” (Novitske, 2018). In this work,
we echo previous discussions that this can lead to data colonialism and
significant, irreparable harm to communities. As we learned from the rich body
of previous works, our experiences, interviews and the personas, data sharing
practices are divergent, ad hoc, at times contradictory, and/or violate
community values for data use. As machine learning and data science move to
focus on the Global South and especially the African continent, the need to
understand what challenges exist in data sharing, and how we can improve data
practices become more pressing.

Despite significant variation among the different countries on the continent,
many countries are now producing high-quality data in a more reliable and
regular manner through statistical offices, national efforts, and involvement
of other public agencies. Likewise, non-public sectors actors — such as
private-sector companies, academic institutions, civil society organisations,
development agencies, and individuals or communities — are now encouraged and
incentivized to be involved in open data management. The future of open data
management and data sharing and their contribution to the advancement of
science and technology in Africa will continue to increase, despite the slow
pace caused by the lack of funding, redundant policy frameworks, and limited
infrastructures. The unique African landscape, and especially the existing
challenges and how they can be addressed, will continue to play a big part in
African participation in open science and open data global projects
(Bezuidenhout and Chakauya, 2018).

As explained by Bangani and Moyo (2019), to understand the sharing practices
of researchers, it is essential first to know where the data comes from and
the lives, cultures, and communities it represents. Bangani and Moyo (2019)
also conclude that most of the emerging researchers in South Africa would
prefer to use data from other sources and are not interested in sharing their
own data. Most of these emerging researchers indicated a lack of resources,
misuse of data, and trust issues as the significant challenges they face in
sharing their data. Some of them indicated that they would prefer to only
share their data with collaborators within their universities and not with
collaborators outside their universities. For many of the researchers in this
context, the labour, effort, and time it takes to collect data is unmatched by
the benefits (often little if any at all) they might receive from data
sharing. Subsequently, as well as encouraging researchers to share their data,
there also needs to be actionable benefits and rewards, as well as policies
that protect African researchers and communities from practices like parachute
research.

Open data imposes risks to African communities – in terms of both stripping
data away from contexts and reduced benefits to communities where data is
sourced. It may present a possibility for Global North researchers to publish
research using data from Global South with neither acknowledgements to data
collectors or data subjects nor an understanding of the data setting.
Consequently, there should be less pressure to open up data and more
incentives to share data with the necessary conditions and support for
infrastructures. The necessary conditions could include data sharing
guidelines that give adequate time to African researchers to make use of data
before wider sharing (Tenopir et al., 2015).

There are various ways towards equitable data sharing that benefit of local
communities. As we have seen in the data sharing challenges section (Section
5), responsible data sharing not only requires knowledge of the context of
data, it also needs to center the interests and norms of communities where
data comes from. Data sharing calls that are not aware of local norms,
contexts, and culture, when imposed from the outside, constitute a form of
Western-centrism and colonialism. For those coming from outside to participate
in data sharing activities, learning “the ways of the people” without
infiltrating their cultures need to be considered a vital part of the process.
Providing sufficient support to local researchers with the aim of facilitating
local-led data sharing practices can be one of the initial steps.

Trust is critical during data sharing. Trust is built if those involved know
each other. The reason for sharing is explicitly stated to all the
stakeholders involved. Each stakeholder performs their responsibility as
agreed, and all stakeholders’ expectations are defined, understood, and
respected. Supposing all stakeholders agree to these conditions, the
likelihood of further collaboration and the possibility of fair sharing
increases. It is recommended that the process of data sharing should be
transparent. Also, researchers based in the continent are encouraged to build
a trustworthy collaboration with funders and other stakeholders. Introducing
proper and adequate legal frameworks, documentation, and support for data
sharing will increase trust among stakeholders. Due to uncertainties and lack
of legal frameworks, several sectors in Africa are unsure of data sharing
norms and practices. They are allowed to share their data, what type of data
can be shared, who, and under what conditions. Such frameworks and
documentation can help clarify the benefits, expected norms, and equitable
data sharing practices. Such can help build trust and encourage researchers to
share their data in a manner that acknowledges their labour and protects their
ideas and innovations.

Equitable data sharing is also a matter of training the next generation of
data scientists. It is imperative to include African data challenges into the
data science curricula since these issues are very different from other parts
of the world. Aspiring data scientists must be aware of data sources, and
historical records about communities where data are collected and the harm
these collected data may pose.

Many of the challenges we have discussed here – such as data sharing in the
absence of awareness of local contexts and norms as well as the issue of trust
– are daunting, and lack simple answers. Nonetheless, as we have sketched in
the above sections, they are challenges that will need to be overcome to
reduce community harm. The much larger and nuanced issues of data sharing,
such as power asymmetry and underlying coloniality, Euro and Anglo-centrism,
white supremacy, are obstacles that need deeper structural and social changes.
They present challenges with no clear solutions. Understanding and
acknowledging their invisible operations is a vital part of the process, and
may point to how power asymmetries can be re-balanced. In this work, we have
brought to light these invisible forces. While our work focuses on data access
and data sharing, we note, also that many of the issues discussed may impact
processes across the data generation, collection, labeling, analyses,
implementation, and use pipeline. Each of these, we believe, warrants further
investigation.

Last, beyond shedding light on the complex data sharing and data practice
challenges in the continent, our work also uplifts research on this topic done
by Africans for Africans. This practice of centering African scholarship
itself challenges negative stereotypes of the continent as “uneducated
population.” There is a vast body of work examining the rapidly evolving data
practices of the African continent and its relationship with the global data
ecosystem.666We share a sampling of these papers, clustered by theme, on the
project page. In the same way that data sharing challenges cannot be overcome
without understanding local contexts, meaningful solutions will not be reached
without deep engagement with African scholarship.

##  7\. Acknowledgements

Abeba Birhane was supported, in part, by Science Foundation Ireland grant
13/RC/2094 and co-funded under the European Regional Development Fund through
the Southern & Eastern Regional Operational Programme to Lero, the Science
Foundation Ireland Research Centre for Software, Ireland (www.lero.ie). The
authors would like to thank our interviewees, members of the Data Science
Africa initiative, workshop and conference participants at the Machine
Learning for Development (ML4D) workshop, the Privacy Law Scholars Conference
(PLSC), the Contested Data Academic Workshop at Data and Society, the
Practical Machine learning for Developing Countries (PML4DC) workshop, as well
as members of the MD4SG Data Economies and Data Governance working group for
invaluable feedback throughout the development of this work. We would also
like to thank Maria Tatar, Thomas Laurent, and anonymous reviewers for the
same.

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