Optimizing the Response to the COVID-19 Pandemic with the Science of FAIR Data

1. THE SCIENCE OF FAIR DATA AND COVID-19 Francisca Oladipo, PhD, FNCS WAT, 11 July 2020 #NCSKogi

2. Focus Focus 1 Optimizing the Response to COVID Optimizing the Response to COVID- -19 with the Science 19 with the Science of FAIR of FAIR Data Data Responding to COVID Responding to COVID- -19 and Preparing for Future Outbreaks 19 and Preparing for Future Outbreaks Focus 2

3. Outline Introduction A new kind of science COVID 19 and the Different Roles COVID 19 and the Different Roles of Science of Science All about FAIR All about FAIR VODAN Africa VODAN Africa Concluding Remarks Concluding Remarks Data Stewardship and Africa Expertise

4. • Consequences • Fears • Disruptions… • Positives • eLearning • Collaborations and New Partnerships • Experiencing something new • Opportunities for knowledge sharing and convergence. • Realizations • Relevance of ML and AI in the scheme of things and why universities should invest in it • Need for science to play a role based on data that are trustworthy, etc The Crises of COVID-19

5. • The Response To COVID-19 • Learning from past Outbreaks through Data? • The 1918 flu pandemic • SARS • Ebola • … • Not much preparations for major outbreaks • Each major outbreak is different though, and experts have a hard time predicting how they will end • The fallout of each disease largely depends on other circumstances — when we catch it, how contagious and fatal it is, how hygienic people are, and how quickly a vaccine or cure becomes available. • Preparing For Future Outbreaks Consequences The unprepared World

6. • Natural (Bio) Sciences • Testing • Vaccines • Treatments • Communication Sciences • Informing • Combating Misinformation • Social Sciences • Supports • Counselling • … • Data Science • Realizations • Relevance of ML and AI in the scheme of things • Need for science to play a role based on data that are trustworthy, etc The Sciences of COVID-19

7. • The kind of Science that ask the questions of: • How do we provide access to critical data across locations • How do we ensure that the data is ’official’ • How do we ensure data governance • How do we protect data ownership • How do we ensure that all COVID-19 data remains: • Findable • Accessible • Interoperable • Reusable Even after the crisis of COVID-19 must have passed Natural (Bio) Sciences • How do we prepare the entire world for future outbreaks? • To answer these kind of questions is an emerging and exciting Computing Research Filed • The Science of FAIR FAIR Data A Different Kind of Science

8. The FAIR Principles

9. • Describe how research outputs should be organised so they can be more easily accessed, understood, exchanged and reused • FAIR data is the default for most funding bodies • Maximizes the integrity and impact of their research investment. • Below is the EC default framework to follow when designing a Data Management Plan The FAIR Principles

10. • Making data findable, including provisions for metadata • Ensuring that Data data produced and/or used in the project discoverable with metadata • identifiable and locatable by means of a standard identification mechanism (e.g. use of persistent DOI) • What naming conventions do you follow? • Will search keywords be provided that optimize possibilities for re-use? • Do you provide clear version numbers? • What metadata will be created? In case metadata standards do not exist in your • discipline, please outline what type of metadata will be created and how. • So generally and in the context of the COVID-19 • F1. (meta)data are assigned a globally unique and eternally persistent identifier. • F2. data are described with rich metadata. • F3. (meta)data are registered or indexed in a searchable resource. • F4. metadata specify the data identifier. Findable

11. • A specification for the data produced and/or used to be will be made openly available by default (State if certain datasets cannot be shared or need to be shared under restrictions) • A specification on how the data, metadata, documentation and code will be made assessible –deposited in a repository, stored in a VPS with URL provided, a premise server with public IP? • A repository that supports open access • Specification of the software or computing environment required to access the data and all associated metadata • A clear description of restrictions and corresponding access mechanisms • Generally and in the context of the COVID-19 • The WHO eCRF is anonymized and the accessibility provisions must conform to the privacy requirement of each country • A1 (meta)data are retrievable by their identifier using a standardized communications protocol. • A1.1 the protocol is open, free, and universally implementable. • A1.2 the protocol allows for an authentication and authorization procedure, where necessary. • A2 metadata are accessible, even when the data are no longer available Accessible

12. • Provision for Data Exchange between researchers, institutions, organisations, countries, etc. through: • standards formats that ensures re-combinations with different datasets from different origins • Following standard prescribed vocabularies, standards and methodologies What data and metadata vocabularies (for all data? Or some?) • When unavoidable to use uncommon or generate project specific ontologies or vocabularies, provision of mappings to common vocabularies and • Generally and in the context of the COVID-19 • I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation • I2. (meta)data use vocabularies that follow FAIR principles • I3. (meta)data include qualified references to other (meta)data Interoperable

13. • All considerations on their reusability of the Data during and after the project through: • Appropriate licensing that permits the widest re-use possible? • The time and terms of the reusability • The duration of the reusability • Generally and in the context of the COVID-19 • R1. meta(data) have a plurality of accurate and relevant attributes. • R1.1. (meta)data are released with a clear and accessible data usage license. • R1.2. (meta)data are associated with their provenance. • R1.3. (meta)data meet domain-relevant community standards. Reusable

15. Partnerships Institutional Supports • MoH and Health Regulatory Authorities in UG and ET VC, KIU and PVC, GZU and each of the partner universities Her Excellency, Julia Duncan Cassell Future Directions • Beyond COVID-19 More FDPs More country partnerships (Liberia, ZA, Rwanda) Technical Manpower Development Team Philips, GFF, FMO, CORDAID Ravel Works • Universities : Africa (UG, ZM, KY, ET, NG, TU) Europe: LIACS, Tilburg Core Team: MvR, FO, MB, FO, Country Cohorts: Coords, Data Stewards: Technical Team: ToT Support VIRUS OUTBREAK DATA AFRICA NETWORK (VODAN AFRICA) A project infusing Africa’s expertise into the fight against the COVID-19 pandemic using FAIR data

16. Virus Outbreak Data (Africa) Network: Key Messages • Africa will become a huge resource centre of verified data on the COVID -19 and future outbreaks through the network of FDPs • A solution by Africans for Africa will address part of the diversity concerns and put Africa in the spotlight • A partnership to further strengthen the Euro- African bond as a basis for global knowledge sharing: • The network of FDPs that will help in this outbreak and provide a decreased learning curve during future outbreaks • The FDPs will help identify potential outbreaks because there could be undetected outbreaks which will be pointed out by the Metadata

17. VODAN Africa Partnerships Uganda Ethiopia Univ de Sousse KIU, Case KIU, Case Hospital Hospital Mekelle, Addis Mekelle, Addis Ababa Ababa Tunisia Tunisia Kenya Kenya Zimbabwe Zimbabwe DSN, DSN, UniLorin UniLorin, IBB , IBB Westlands, Kamukunji, Pumwani Nigeria

18. Critical Point on the VODAN Africa Initiative: Ownership and Residence Question(?) Data is currently too much of western and less of an African initiative VODAN Africa will ensure data ownership and handling 18

19. In the Context of the COVID-19 Africa Data will be resident in Africa -avoid digital data removal to warehouses elsewhere Strengthen data-informed Health Systems for Africa Africa Data will ne the property of the country of jurisdiction -ensure data ownership and handling Capacity Building - strenghten digital data stewardship and tooling 19

20. VODAN THREE-POINT FAIRIFICATION FRAMEWORK

21. VODAN AFRICA

22. • Another opportunity to realize that the science of Data will help as much as the science of Medicine • While it is important to find vaccines, it is also important to provide healthcare workers with the right data to combat the present pandemic and prepare for future ones • …a set of principles for developing robust, extensible infrastructure which facilitates discovery, access and reuse of research data and software • Putting Computing right at the centre of the fight against the COVID-19 pandemic Conclusion Amid the fears and anxieties…

23. THANK YOU