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.
Facilitating private-public partnerships is one step to encourage the data community to work with valuable open data. However, transparency and a high level quality assurance step must be given. In a joint collaboration with data curators, developers, technical specialists and academics, the datasets should be retrieved, cleaned and assessed in order to deliver efficient, relevant and credible information. The constant monitoring and regulation as well as compliance with data security guidelines are indispensable.
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.
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.
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.