reproducible research

Credibility is Enhanced Through Cross Links Between Different Data from Different Domains

Credibility is enhanced through cross-links between different data from different domains that “does not disprove” one another or that is internally consistent. If, say, data on taxable income goes in one direction and taxes in another, it is the reasoned reconciliation of the - alleged or real - inconsistency that will validate the comprehensive data set. So I am a great believer in broad, real-time observatories where not only the data capture, but the data reconciliation is automated, sometimes by means of a simple comparative statics analysis, in other cases maybe through quite elaborate artificial intelligence.

We Need More Reliable Datasets on the Urban Heat Resilience and Disaster Risk Reduction

I would like to see more data on the consequences and impact of increasing drought and urban heat in our cities in the Green Deal Data Observatory. Because of the complexity of rapidly developing metropolitan regions and the uncertainty associated with climate change, we need to explore more climate change adaptation and mitigation activities, or disaster risk reduction, not only climate change itself.

Comparing Data to Oil is a Cliché: Crude Oil Has to Go Through a Number of Steps and Pipes Before it Becomes Useful

Many interesting phenomena are difficult to quantify in a meaningful way and writing a catchy song with international appeal is probably more an art than a science. Nevertheless that should not deter us from trying as music, too, is bound by certain rules and regularities that can be researched.

Join Copernicus Climate Data Store Data with Socio-Economic and Opinion Poll Data

In this series of blogposts we will show how to collect environmental data from the EU’s Copernicus Climate Data Store, and bring it to a data format that you can join with Eurostat’s socio-economic and environmental data.

Creating Algorithmic Tools to Interpret and Communicate Open Data Efficiently

Although there are a variety of open data sources available (and the numbers continue to increase), the availability of open algorithmic tools to interpret and communicate open data efficiently is lagging behind. One of the greatest challenges for open data in 2021 is to demonstrate how we can maximize the potential of open data by designing smart tools for open data analytics.

EU Datathon 2021

Reprex, a Dutch start-up enterprise formed to utilize open source software and open data, is looking for partners in an agile, open collaboration to win at least one of the three EU Datathon Prizes.