Secondary Data from Insights from Publishing Open Data in Industry-Academia Collaboration

Secondary Data from Insights from Publishing Open Data in Industry-Academia Collaboration

Authors

Per Erik Strandberg [1], Philipp Peterseil [2], Julian Karoliny [3], Johanna Kallio [4], and Johannes Peltola [4].

[1] Westermo Network Technologies AB (Sweden).[2] Johannes Kepler University Linz (Austria)[3] Silicon Austria Labs GmbH (Austria).[4] VTT Technical Research Centre of Finland Ltd. (Finland).

Description

This data is to accompany a paper submitted to Elsevier's data in brief in 2024, with the title Insights from Publishing Open Data in Industry-Academia Collaboration.

Tentative Abstract: Effective data management and sharing are critical success factors in industry-academia collaboration. This paper explores the motivations and lessons learned from publishing open data sets in such collaborations. Through a survey of participants in a European research project that published 13 data sets, and an analysis of metadata from almost 281 thousand datasets in Zenodo, we collected qualitative and quantitative results on motivations, achievements, research questions, licences and file types. Through inductive reasoning and statistical analysis we found that planning the data collection is essential, and that only few datasets (2.4%) had accompanying scripts for improved reuse. We also found that authors are not well aware of the importance of licences or which licence to choose. Finally, we found that data with a synthetic origin, collected with simulations and potentially mixed with real measurements, can be very meaningful, as predicted by Gartner and illustrated by many datasets collected in our research project.

Secondary data from Survey

The file survey.txt contains secondary data from a survey of participants that published open data sets in the 3-year European research project InSecTT.

Secondary data from Zenodo

The file secondary_data_zenodo.json contains secondary data from an analysis of data sets published in Zenodo. It is accompanied with a py-file and a ipynb-file to serve as examples.

License

This data is licenced with the Creative Commons Attribution 4.0 International license. You are free to use the data if you attribute the authors. Read the license text for details.