Narratives and Counternarratives on Data Sharing in Africa

Abebe, Rediet; Aruleba, Kehinde; Birhane, Abeba; Kingsley, Sara; Obaido, George; Remy, Sekou L.; Sadagopan, Swathi

doi:10.1145/3442188.3445897

Cited by 68 publications

(50 citation statements)

References 85 publications

(99 reference statements)

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“…Data sharing is helpful to achieve greater efficiency in the use and re(use) of data by the government [35,142,152]. It is a key to transparency and economic growth [174]. The fundamental idea of linked data is to use the World Wide Webs global architecture to share structured data worldwide [26].…”

Section: Storage Phase Key Functionsmentioning

confidence: 99%

“…• PAs should keep balance to allocate powers to a different group of stakeholders (Government bodies, NGOs, Regulators, Data Brokers versus data subjects, entrepreneurs, archivists, data, data collectors) in driving the design, framing, and implementation of data sharing policies and practices [174]. • Implement web standards in data formats, like HTML, XML, RDF, CSV, and web protocols, like HTTP, FTP, and SOAP to publish data on web [70,92,175].…”

Section: Storage Phase Key Functionsmentioning

confidence: 99%

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DaLiF: a data lifecycle framework for data-driven governments

2021

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The public sector, private firms, business community, and civil society are generating data that is high in volume, veracity, velocity and comes from a diversity of sources. This kind of data is known as big data. Public Administrations (PAs) pursue big data as “new oil” and implement data-centric policies to transform data into knowledge, to promote good governance, transparency, innovative digital services, and citizens’ engagement in public policy. From the above, the Government Big Data Ecosystem (GBDE) emerges. Managing big data throughout its lifecycle becomes a challenging task for governmental organizations. Despite the vast interest in this ecosystem, appropriate big data management is still a challenge. This study intends to fill the above-mentioned gap by proposing a data lifecycle framework for data-driven governments. Through a Systematic Literature Review, we identified and analysed 76 data lifecycles models to propose a data lifecycle framework for data-driven governments (DaliF). In this way, we contribute to the ongoing discussion around big data management, which attracts researchers’ and practitioners’ interest.

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Section: Storage Phase Key Functionsmentioning

confidence: 99%

Section: Storage Phase Key Functionsmentioning

confidence: 99%

DaLiF: a data lifecycle framework for data-driven governments

2021

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“…Additionally, as outlined by Abebe et al (2021), the reluctance to engage in data sharing initiatives may originate from insufficient trust. Data sharing can lead to risks for local communities, especially if data are taken out of context or not analyzed and interpreted with the appropriate local knowledge.…”

Section: Government Clearance and Regulationmentioning

confidence: 99%

Challenges and opportunities in accessing mobile phone data for COVID-19 response in developing countries

et al. 2021

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Anonymous and aggregated statistics derived from mobile phone data have proven efficacy as a proxy for human mobility in international development work and as inputs to epidemiological modeling of the spread of infectious diseases such as COVID-19. Despite the widely accepted promise of such data for better development outcomes, challenges persist in their systematic use across countries. This is not only the case for steady-state development use cases such as in the transport or urban development sectors, but also for sudden-onset emergencies such as epidemics in the health sector or natural disasters in the environment sector. This article documents an effort to gain systematized access to and use of anonymized, aggregated mobile phone data across 41 countries, leading to fruitful collaborations in nine developing countries over the course of one year. The research identifies recurring roadblocks and replicable successes, offers lessons learned, and calls for a bold vision for future successes. An emerging model for a future that enables steady-state access to insights derived from mobile big data - such that they are available over time for development use cases - will require investments in coalition building across multiple stakeholders, including local researchers and organizations, awareness raising of various key players, demand generation and capacity building, creation and adoption of standards to facilitate access to data and their ethical use, an enabling regulatory environment and long-term financing schemes to fund these activities.

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“…Attending to the unequal capacity to produce and analyse data, influential actors have argued that data sharing and open access can help solve existing asymmetries (Borgman, 2015, p. 39), not least in the case of astronomy (Peek et al, 2019). However, these frameworks have not been capable of capturing the full complexity encompassed by data collaborations, especially when it comes to accounting for the obstacles faced by data-poor actors and the asymmetrical distribution of benefits between the parties (Abebe et al, 2021).…”

Section: Data Collaborations In An Asymmetrical Planetary Ordermentioning

confidence: 99%

The coloniality of collaboration: sources of epistemic obedience in data-intensive astronomy in Chile

Lehuedé

2021

Information, Communication & Society

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Data collaborations have gained currency over the last decade as a means for data-and skills-poor actors to thrive as a fourth paradigm takes hold in the sciences. Against this backdrop, this article traces the emergence of a collaborative subject position that strives to establish reciprocal and technical-oriented collaborations so as to catch up with the ongoing changes in research. Combining insights from the modernity/coloniality group, political theory and science and technology studies, the article argues that this positionality engenders epistemic obedience by bracketing off critical questions regarding with whom and for whom knowledge is generated. In particular, a dis-embedding of the data producers, the erosion of local ties, and a data conformism are identified as fresh sources of obedience impinging upon the capacity to conduct research attuned to the needs and visions of the local context. A discursive-material analysis of interviews and field notes stemming from the case of astronomy data in Chile is conducted, examining the vision of local actors aiming to gain proximity to the mega observatories producing vast volumes of data in the Atacama Desert. Given that these observatories are predominantly under the control of organisations from the United States and Europe, the adoption of a collaborative stance is now seen as the best means to ensure skills and technology transfer to local research teams. Delving into the epistemological dimension of data colonialism, this article warns that an increased emphasis on collaboration runs the risk of reproducing planetary hierarchies in times of data-intensive research.

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Narratives and Counternarratives on Data Sharing in Africa

Cited by 68 publications

References 85 publications

DaLiF: a data lifecycle framework for data-driven governments

DaLiF: a data lifecycle framework for data-driven governments

Challenges and opportunities in accessing mobile phone data for COVID-19 response in developing countries

The coloniality of collaboration: sources of epistemic obedience in data-intensive astronomy in Chile

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