Making data on COVID-19 available to the scientific community

The team developed software to extract the color code for each municipality in the epidemiological reports.

During this corona crisis there is a high demand for statistics, graphs, and maps concerning the COVID-19 outbreak. The collects data and publishes statistics on COVID-19 infections in the Netherlands on a daily basis. Utrecht 木瓜福利影视鈥檚 Research Data Management Support spoke with research engineer Jonathan de Bruin about the data behind those graphs and his initiative, named . The aim of this project is to organize the reported data from the RIVM, and make it available to the scientific community and the public.

Time series

In the Netherlands, the RIVM is responsible for the national coordination for infectious diseases. 鈥淓very day around 2 p.m., RIVM reports the latest statistics on the COVID-19 outbreak in the Netherlands鈥 according to De Bruin. 鈥淭he numbers are made available in their news releases, an interactive chart, and a . When these data are collected and combined, these daily updates can result in a time series.鈥

Sound data management is more important than ever, to give researchers the chance to build upon the results of others

鈥淔or the scientific community as well as the public, it is important to have a time series of the COVID-19 cases and fatalities. Researchers and policymakers use them for modeling, discussion, and awareness. Making these data findable, accessible, interoperable, and reusable (FAIR) is more important than ever, to give researchers the chance to build upon the results of others.鈥

Worldwide 

Universities, developers and volunteers worldwide are taking the lead in collecting, organizing and structuring the outbreak numbers on the COVID-19 outbreak on a global and national level. 鈥淥ne of the most prominent projects is the鈥(JHU).鈥疛HU鈥痗ollects data on officially reported cases from around the world on a national level and provides an鈥痠nteractive鈥痙ashboard鈥痶o report and map the numbers. This is one of the most reliable sources of global outbreak numbers at this moment.鈥 

This project relies on the collaboration between our researchers and volunteers

COVID-19 infections by province during the past month

CoronaWatchNL 

Where the JHU stops, continues. With this project, De Bruin aims to compose a FAIR dataset on RIVM reported numbers. He started collecting all numbers, datasets, and mutations reported by RIVM directly after the first numbers were published. CoronaWatchNL is now backed by researchers from Utrecht 木瓜福利影视 and volunteers. 鈥淲e use the same methods as the JHU, but we collect data on a regional level as well. We do have several structured datasets available on positively tested patients, their municipality of residence, ages, and sex.鈥 

鈥淲e update the data on and make a persistent data publication on  on a daily basis. With date-based versioning, we provide a clear overview of our datasets. These persistent data publications are important for the research community such that their work is reproducible.鈥  The RIVM added the project to their on COVID-19.

Open Science

De Bruin, who also leads the work package Open Software in the Utrecht 木瓜福利影视鈥檚 Open Science program, praises the contributions of the researchers and volunteers on CoronaWatchNL. 鈥淣ew datasets have been added by volunteers, software was developed to extract statistics from PDF's, and visualizations were made available. Open Science, Citizen Science, and making datasets FAIR make research on COVID-19 more effective, reliable and fast. This project relies on the collaboration between our researchers and volunteers.鈥

Dutch Data Prize 2020

For this project, De Bruin has been awarded with the Dutch Dataprize 2020. The prize is awarded to someone from the research community who makes an extra contribution to science by making research data available for additional or new research. The prize consists of a sculpture and 鈧5,000 to make the dataset (even) more accessible. De Bruin emphasises that this project is the result of the hard work of many volunteers: "We could not have done this without the help of volunteers. I think CoronaWatchNL is a good example of citizen science. That is why the RDNL Data Prize 2020 is an award for them." Read the full newsitem here.