This article explores the global implementation of the FAIR Guiding Principles for scientific management and data stewardship, which provide that data should be findable, accessible, interoperable and reusable. The implementation of these principles is designed to lead to the stewardship of data as FAIR digital objects and the establishment of the Internet of FAIR Data and Services (IFDS). If implementation reaches a tipping point, IFDS has the potential to revolutionize how data is managed by making machine and human readable data discoverable for reuse. Accordingly, this article examines the expansion of the implementation of FAIR Guiding Principles, especially how and in which geographies (locations) and areas (topic domains) implementation is taking place. A literature review of academic articles published between 2016 and 2019 on the use of FAIR Guiding Principles is presented. The investigation also includes an analysis of the domains in the IFDS Implementation Networks (INs). Its uptake has been mainly in the Western hemisphere. The investigation found that implementation of FAIR Guiding Principles has taken firm hold in the domain of bio and natural sciences. To achieve a tipping point for FAIR implementation, it is now time to ensure the inclusion of non-European ascendants and of other scientific domains. Apart from equal opportunity and genuine global partnership issues, a permanent European bias poses challenges with regard to the representativeness and validity of data and could limit the potential of IFDS to reach across continental boundaries. The article concludes that, despite efforts to be inclusive, acceptance of the FAIR Guiding Principles and IFDS in different scientific communities is limited and there is a need to act now to prevent dampening of the momentum in the development and implementation of the IFDS. It is further concluded that policy entrepreneurs and the GO FAIR INs may contribute to making the FAIR Guiding Principles more flexible in including different research epistemologies, especially through its GO CHANGE pillar.

The limited volume of COVID‐19 data from Africa raises concerns for global genome research, which requires a diversity of genotypes for accurate disease prediction, including on the provenance of the new SARS‐CoV‐2 mutations. The Virus Outbreak Data Network (VODAN)‐Africa studied the possibility of increasing the production of clinical data, finding concerns about data ownership, and the limited use of health data for quality treatment at point of care. To address this, VODAN Africa developed an architecture to record clinical health data and research data collected on the incidence of COVID‐19, producing these as human‐ and machine‐readable data objects in a distributed architecture of locally governed, linked, human‐ and machine‐readable data. This architecture supports analytics at the point of care and—through data visiting, across facilities—for generic analytics. An algorithm was run across FAIR Data Points to visit the distributed data and produce aggregate findings. The FAIR data architecture is deployed in Uganda, Ethiopia, Liberia, Nigeria, Kenya, Somalia, Tanzania, Zimbabwe, and Tunisia.

This article investigates expansion of the Internet of FAIR Data and Services (IFDS) to Africa, through the three GO FAIR pillars: GO CHANGE, GO BUILD and GO TRAIN. Introduction of the IFDS in Africa has a focus on digital health. Two examples of introducing FAIR are compared: a regional initiative for digital health by governments in the East Africa Community (EAC) and an initiative by a local health provider (Solidarmed) in collaboration with Great Zimbabwe University in Zimbabwe. The obstacles to introducing FAIR are identified as underrepresentation of data from Africa in IFDS at this moment, the lack of explicit recognition of situational context of research in FAIR at present and the lack of acceptability of FAIR as a foreign and European invention which affects acceptance. It is envisaged that FAIR has an important contribution to solve fragmentation in digital health in Africa, and that any obstacles concerning African participation, context relevance and acceptance of IFDS need to be removed. This will require involvement of African researchers and ICT-developers so that it is driven by local ownership. Assessment of ecological validity in FAIR principles would ensure that the context specificity of research is reflected in the FAIR principles. This will help enhance the acceptance of the FAIR Guidelines in Africa and will help strengthen digital health research and services.

This study explores the possibility of opening a policy window for the adoption of the FAIR Guidelines – that data be Findable, Accessible, Interoperable, and Reusable (FAIR) – in Uganda's eHealth sector. Although the FAIR Guidelines were not mentioned in any of the policy documents relevant to Uganda's eHealth sector, the study found that 83% of the documents mentioned FAIR Equivalent efforts, such as the adoption of the National Identification Number (NIN) as a unique identifier in Uganda's national Electronic Health Management Information System (eHMIS) (findability), the planned/ongoing integration of various information systems (interoperability), and the alignment of various projects with international best practices/standards (reusability). A FAIR Equivalency Score (FE-Score), devised in this study as an aggregate score of the mention of the equivalent of FAIR facets in the policy documents, showed that the documents at the core of Uganda's digital health/eHealth policy have the highest score of all the documents analysed, indicating that there is a degree of alignment between Uganda's National eHealth Vision and the FAIR Guidelines. Therefore, it can be concluded that favourable conditions exist for the adoption and implementation of the FAIR Guidelines in Uganda's eHealth sector. Hence, it is recommended that the FAIR community adopt a capacity building strategy through organisations with a worldwide mandate, such as the World Health Organization, to promote the adoption of the FAIR Guidelines as part of international best practices.

The incompleteness of patient health data is a threat to the management of COVID-19 in Africa and globally. This has become particularly clear with the recent emergence of new variants of concern. The Virus Outbreak Data Network (VODAN)-Africa has studied the curation of patient health data in selected African countries and identified that health information flows often do not involve the use of health data at the point of care, which renders data production largely meaningless to those producing it. This modus operandi leads to disfranchisement over the control of health data, which is extracted to be processed elsewhere. In response to this problem, VODAN-Africa studied whether or not a design that makes local ownership and repositing of data central to the data curation process would 2 have a greater chance of being adopted. The design team based their work on the legal requirements of the European Union's General Data Protection Regulation (GDPR); the FAIR Guidelines on curating data as Findable, Accessible (under well-defined conditions), Interoperable and Reusable (FAIR); and national regulations applying in the context where the data is produced. The study concluded that the visiting of data curated as machine actionable and reposited in the locale where the data is produced and renders services has great potential for access to a wider variety of data. A condition of such innovation is that the innovation team is intradisciplinary, involving stakeholders and experts from all of the places where the innovation is designed, and employs a methodology of co-creation and capacity-building.

Adopting the FAIR Guidelines – that data should be Findable, Accessible, Interoperable and Reusable (FAIR) – in the health data system in Nigeria will help protect data against use by unauthorised parties, while also making data more accessible to legitimate users. However, little is known about the FAIR Guidelines and their compatibility with data and health laws and policies in Nigeria. This study assesses the governance framework for digital and health/eHealth policies in Nigeria and explores the possibility of a policy window opening for the FAIR Guidelines to be adopted and implemented in Nigeria's eHealth sector. Ten Nigerian policy documents were examined for mention of the FAIR Guidelines (or FAIR Equivalent terminology) and the 15 sub-criteria or facets. The analysis found that although the FAIR Guidelines are not explicitly mentioned, 70% of the documents contain FAIR Equivalent terminology. The Nigeria Data Protection Regulation contained the most FAIR Equivalent principles (73%) and some of the remaining nine documents also contained some FAIR Equivalent principles (between 0–60%). Accordingly, it can be concluded that a policy window is open for the FAIR Guidelines to be adopted and implemented in Nigeria's eHealth sector.

With the prevailing COVID-19 pandemic, the lack of digitally-recorded and connected health data poses a challenge for analysing the situation. Virus outbreaks, such as the current pandemic, allow for the optimisation and reuse of data, which can be beneficial in managing future outbreaks. However, there is a general lack of knowledge about the actual flow of information in health facilities, which is also the case in Uganda. In Uganda, where this case study was conducted, there is no comprehensive knowledge about what type of data is collected or how it is collected along the journey of a patient through a health facility. This study investigates information flows of clinical patient data in health facilities in Uganda. The study found that almost all health facilities in Uganda store patient information in paper files on shelves. Hospitals in Uganda are provided with paper tools, such as reporting forms, registers and manuals, in which district data is collected as aggregate data and submitted in the form of digital reports to the Ministry of Health Resource Center. These reporting forms are not digitised and, thus, not machine- actionable. Hence, it is not easy for health facilities, researchers, and others to find and access patient and research data. It is also not easy to reuse and connect this data with other digital health data worldwide, leading to the incorrect conclusion that there is less health data in Uganda. The a FAIR architecture has the potential to solve such problems and facilitate the transition from paper to digital records in the Uganda health system.

The field of health data management poses unique challenges in relation to data ownership, the privacy of data subjects, and the reusability of data. The FAIR Guidelines have been developed to address these challenges. The Virus Outbreak Data Network (VODAN) architecture builds on these principles, using the European Union's General Data Protection Regulation (GDPR) framework to ensure compliance with local data regulations, while using information knowledge management concepts to further improve data provenance and interoperability. In this article we provide an overview of the terminology used in the field of FAIR data management, with a specific focus on FAIR compliant health information management, as implemented in the VODAN architecture.