The VODAN IN Africa Training the Trainers

Fighting the COVID-19 with FAIR Data

Institutional Support for VODAN-Africa


About VODAN


About VODAN
What is the Virus Outbreak Data Network (VODAN)?
VODAN is a GO FAIR Implementation Network set up to help fight the COVID-19 Corona virus, that is causing a worldwide epidemic. The Implementation Network VODAN is a step to establish the Internet of FAIR Data and Services.
FAIR stands for human and machine-readable digital data objects that are Findable, Accessible, Interoperable and Reusable. Accessibility is fully compliant with regulatory and governance frameworks, including personal data protection and ethical considerations based on the principle to Do no Harm.
Making data and metadata FAIR ensures that these data are discoverable on the Internet of FAIR Data and Services. Central tot his approach is the establishment of FAIR Data Points (FDPs), for COVID-19 relevant digital data objects. Opening up FAIR (meta)data by publishing them on a FDP allows algorithms to search these (meta)data, looking for patterns. The Internet of FAIR Data and Services is a distributed data discovery network; data are NOT moved, but algorithms going over the internet can find the data.

About the VODAN ToT


This Training of Trainers (ToT) is set up to provide support to data stewards so that they can help combat the COVID-19 pandemic.

The first course will focus on awareness, and include subjects like: what does FAIR data stewardship entail? What are FAIR data? What is a Semantic Data model? What is a FAIR Data point?

This will be followed by a course how to set up a FAIR data point. Other courses will follow shortly.

The training sub objectives are to:

  • Help prepare ministries and institutions for publishing FAIR (meta)data regarding the pandemic;
  • Ensure that universities and institutions with medical data have capacities to assist the navigation of the crisis with quality data;
  • Ensure that data stewardship is carried out under strict adherence to the governance and regulatory framework of the country and institution where the data belong;
  • Enable data to be analysed in combination with data available globally;
  • Ensure quality data for AI solutions to help deal with the pandemic.
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The training is intended for data scientists and computer scientists, working in connection for medical and health service providers, the Ministry of Health, and other relevant institutions and companies.

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This training for trainers can be organized in all countries, but focusses for the moment particularly on Africa and Asia.

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The ToT is set up in such a way that participants can follow the training on-line, with maximum flexibility.

The Training is provided and set up by the experts of the GO FAIR International Support and Coordination Office (GFISCO)

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The Training of Trainers course is set up in such a way that participants can follow the training online, with maximum flexibility.

The course is provided and set up by the experts of the GO FAIR International Support and Coordination Office (GFISCO).

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Implementation Networks help build, train and also deploy the Internet of FAIR Data and Services.

  • Virus Outbreak Data Network (VODAN): Implementation Network on COVID-19
  • Implementation Network Ambassadors: Introduction and training of new participants
  • Implementation Network Africa: Introduction of participants in Africa-specific reality
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The participants of the ToT will be able to receive assistance from the Technical Support Team who are students in Computer Science/Data Science of Leiden Institute of Computer Science: Mariam Basajja Uganda (coordinator, PhD candidate), Kudakwashe Chindoza, Zimbabwe (PhD aspirant candidate), Aliya Aktau, Kazakhstan, (master student), Putu Hadi, Indonesia (master student) and QiQi Zhang, China (master student).

The Technical Support Team is backed by the Senior Supervision Team, faculty in Computer Science/Data Science.



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The participants of the training are invited to participate via different mediums (WhatsApp, ORCID, OSF and INs).

The training modules will be provided in accessible format for participants with low bandwidth.

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Vocabulary


Repositories


Presentation Slides

All the ToT Presentation slides are available here

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Training Documents

All training Documents are available here

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Training Videos

All training videos are available here

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Technical Instructions

All technical instructions can be accessed through here

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Communications

All Communications Documents on the VODAN Africa Project are available here

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VODAN-Africa In the News


COVID-19: Artificial Intelligence to Back Up Data-Driven Response in Africa

COVID-19: Artificial Intelligence to Back Up Data-Driven Response in Africa

IDN -indepthnews "The public research university in the Netherlands has joined universities in Uganda, Kenya, Tanzania, Ethiopia, Nigeria and Zimbabwe in the Virus Outbreak Data Africa Network (VODAN) FAIR Data initiative."

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Eurasia Review: COVID-19: Artificial Intelligence To Back Up Data-Driven Response In Africa

Eurasia Review: COVID-19: Artificial Intelligence To Back Up Data-Driven Response In Africa

Computer scientists across the continent collaborate to establish connected data to strengthen analytics to fight COVID-19

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Africa expertise included in global data network to combat the Corona pandemic

Africa expertise included in global data network to combat the Corona pandemic

The GO FAIR Foundation, Kampala International University and the Philips Foundation have teamed up in an effort to enable distributed access to the critical data needed from Africa to fight and contain the COVID-19 pandemic.

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euobserver -Coronavirus exposes lack of common data approach

euobserver -Coronavirus exposes lack of common data approach

Some experts believe that the EU's current approach to data collection may be missing an opportunity to fight the coronavirus outbreak

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Further Reading


  • Constituent article on the FAIR Guiding principles
Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18
https://www.nature.com/articles/sdata201618
  • FAIR Special Data Intelligence, MIT:
http://www.data-intelligence-journal.org/
  • Internet of FAIR Data and Services:
https://www.go-fair.org/resources/internet-fair-data-services/
  • Virus Outbreak Data Network (VODAN):
https://www.go-fair.org/implementation-networks/overview/vodan/
  • Implementation Networks:
https://www.go-fair.org/implementation-networks/
  • Response scenarios:
https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf
  • A FHIR RDF dataset for COVID-19 research: a dataset of 13202 journal articles.  This dataset extends the CORD-19 dataset (on which it is based) by adding several semantic annotations. 
https://github.com/fhircat/CORD-19-on-FHIR
  • WHO Data base articles on COVID-19
https://www.who.int/emergencies/diseases/novel-coronavirus-2019/global-research-on-novel-coronavirus-2019-ncov
  • Real-time detailed map
https://coronavirus.jhu.edu/map.html

Partners


Philips Foundation

About Philips Foundation

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Kampala International University

About Kampala International University

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GO FAIR Foundation

About GO FAIR Foundation

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