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Open-Access Data and Computational Resources on Coronavirus disease 2019 (COVID-19)

COVID-19, Open Science and Open Data

We are witnessing a massive ongoing production of thousands of scientific papers on COVID-19. Rapidly evolving scientific opinions in these papers that are based on studies and emerging data and evidence, as a part of the standard scientific process. Because of the scale of the effort and high interest of the public and impact on actions and policies that affect everyone, this production results in ambiguity and often confusion in the wider public. These findings and conclusions may be even weaponised in the public debate, which is nowadays quite common in climate science, but not in epidemiology and virology. The attractiveness and popularity of the subject make it more prone to opportunistic production od papers, while the availability of preprints that did not go through the standards peer-review process adds a layer on uncertainty due to greater chances for questionable work to be used and relied upon. On the other hand, preprints allow quick sharing of information and accelerate research, as studies become available months before they are published; this also facilitates external validation and pruning by other researchers outside of the formal peer-review process.

Unlike natural disasters that are easy to witness, the less visible nature of the epidemic makes it easier to negate its effects and related facts. Sharing of information increases the ability to understand and act rationally while reducing anxiety and uncertainty. The conflicting data and messages may result in the opposite and also lead to clustering of around conflicting views and conclusions. While these divisions are normally gradually resolved in through the scientific process, they may have a great immediate impact on behaviours, social trust and healthcare and public health interventions.

Inevitable difficulties related to the accuracy of measurements and related insufficient accuracy and timeliness of data complicate the interpretation of those data, something that is obvious in the discussion of the spread of the infection, mortality rate, reinfection or the percentage of asymptomatic carriers. The similar problems occur in the interpretation of the epidemiological models, which are often interpreted as predictions and not as the instruments to explore and quantify possibilities and effects of policymakers’ actions. This leads to the interpretation of warning as exaggerated and false predictions. Thus, preventive measures may be disregarded as their objective is to prevent something from actually happening, which exposes them to disputes and objection, pin particular upon prolonged or repetitive application.

The open science and open data may help in addressing these problems and concerns and become a part of the approach for addressing the current crisis of trust. This crisis affects the facts, validation process, experts and authorities, regardless of whether they are scientific, medical or societal. While the science operates with hypotheses, uncertainties and changing conclusions, others who are present in the public space may offer absolutes, overconfidence, inadequate simplifications or opportunistic scepticism. What is necessary is to develop new ways to communicate the facts and distinguish the valuable information, expertise and truth from everything else, at the same time providing the relevant, multi-disciplinary and integrative perspective. What COVID-19 emphasises is the need for the process that will ease dealing with uncertainties and accelerate the identification of important and valid messages and at the same time minimise the effects of uncertainties and changes in knowledge that diminishing trust and increase vulnerability to falsehoods and disinformation.

General data resources

Overall resource lists and national resources

Daily countries aggregate data

ECDC data

Daily country regional or city aggregate data

  • Country...
    • Resource...

Per case country data


Multitype registries

Publications registries

Computational resources

Offering to researches from NI4OS countries, but potentially also to other resources, for all who are working in COVID-19 related fields.


  • Contact XY... and express your need by briefly describing
    • Area of research
    • Estimated computational load,
    • Execution environment (programming language, libraries),
    • Data exchange, etc.
  • The needs will be matched against the available resources and you will be responded within xxx
  • Details will be...

Supporting resources

  • Something...

Data Coding

Procedures and protocols