Dear readers,
It is my privilege to compose this editorial for the inaugural issue of ing.grid. In ing.grid, we acknowledge the fundamental role of processing, accessibility, and usability of research data. These aspects serve as prerequisites not only for the traceability and trust in research but also as the foundation for knowledge and innovation processes. An exemplary case is the successful development of Covid-19 vaccines, where the application of FAIR data, facilitated by trust between academia and industry, significantly shortened the development timeline.
We are well aware that the effort that goes into research data management and data as well as research software quality has not received enough academic credit to date. We are committed to making research data management an integral component of good scientific practice. This encompasses not only economic processes and “exchange transactions” within the data cycle but also the evaluation of the value and costs of data, along with recognition as a “currency” in data publications. This issue contains first specimens of two types of ing.grid open peer reviewed publications: of a manuscript [1], and a software submission [2]. The detailed review discussion of each of these articles can be found on the ing.grid preprint server, and we are proud to see that many scientists were willing to contribute to ing.grid by conducting reviews.
We hope that this inaugural issue of ing.grid contributes to raising awareness about the importance of data quality in research and fosters fruitful dialogue within the scientific community.
Best regards,
Peter F. Pelz
Editor-in-Chief
References
[1] P. Diercks, D. Gläser, O. Lünsdorf, M. Selzer, B. Flemisch, and J. Unger, “Evaluation of tools for describing, reproducing and reusing scientific workflows,” ing.grid, vol. 1, no. 1, 2023, ISSN: 2941–1300. DOI: http://doi.org/10.48694/inggrid.3726. [Online]. Available: https://www.inggrid.org/article/id/3726/.
[2] Martin Hock, Hannes Mayr, Manuela Richter, Jan Lemmer, and Peter Pelz, “Plotid – a toolkit for connecting research data and visualization,” ing.grid, vol. 1, no. 1, 2023, ISSN: 2941–1300. DOI: http://doi.org/10.48694/inggrid.3632. [Online]. Available: https://www.inggrid.org/article/id/3632/.