data-as-service

Public data sources are often plagued with missng values. Naively you may think that you can ignore them, but think twice: in most cases, missing data in a table is not missing information, but rather malformatted information which will destroy your beautiful visualization or stop your application from working. In this example we show how we increase the usable subset of a public dataset by 66.7%, rendering useful what would otherwise have been a deal-breaker in panel regressions or machine learning applications.

Reprex joined the REshaping CCSI REsearch: Open data, policy analysis and methods for evidence-based decision-making consortium consortium, which will mainly develop new policy evidence in the field of innovation and inclusiveness for the creative and cultural sectors, industries.

Reprex’s co-founder, Daniel Antal and our Listen Local curator, Marie Zhorová participated in the MaMA Festival & Convention in Paris on 13-15 October within the JUMP Music Market Accelerator Program. We introduced our Digital Music Observatory to national music organizations and encouraged them to try out a cooperation with us.

The creative and cultural sectors and industries are mainly made of networks of freelancers and microenterprises, with very few medium-sized companies. Their economic performance, problems, and innovation capacities hidden. Our open collaboration to create this data observatory is committed to change this. Relying on modern data science, the re-use of open governmental data, open science data, and novel harmonized data collection we aim to fill in the gaps left in the official statistics of the European Union.

Sisyphus was punished by being forced to roll an immense boulder up a hill only for it to roll down every time it neared the top, repeating this action for eternity. When was a file downloaded from the internet? What happened with it sense? Are their updates? Did the bibliographical reference was made for quotations? Missing values imputed? Currency translated? Who knows about it – who created a dataset, who contributed to it? Which is the final, checked, approved by a senior manager?