A Research Data Management Infrastructure for Plasma Medicine and Beyond

We propose a management infrastructure for research data specially designed for plasma medicine and adjacent fields (low temperature plasma science). Systematically archiving and publishing data has become an increasingly important part of research. This often follows the idea of FAIR (Findable, Accessible, Interoperable, and Reusable) data [1].

We currently build a system that accompanies the researcher from planning the experiment through its execution to saving, publishing, and reusing of the originating data with meaningful metadata. The goal is to use a knowledge graph that the community of plasma scientists continuously augments and maintains. This knowledge graph is used to help researchers in finding the metadata that is necessary for each individual experiment. It will also be linked to knowledge graphs of other fields to increase interoperability across different fields of research and therefore the visibility of plasma research. This gives credit to the multitude of research methods used in this field. The knowledge graph provides options to define quality criteria, which ensure the findability and reusability of published data.
As a first step towards this goal, we developed the data platform INPTDAT (https://www.inptdat.de/) to upload research data in a structure that is adapted to plasma research data. This structure follows the general plasma metadata schema, Plasma-MDS, which has been published recently [2] (see Fig. 1). Data published on INPTDAT and described by using Plasma-MDS can easily be found and cited by the owner as well as other researchers using its unique DOI (digital object identifier).
The use of blockchain technology is another part of the intended infrastructure to make the publishing and citing of data safer and traceable. In the future, this system can also allow reputation monitoring.
Together, these systems will support data exchange and thus enhance data-driven science in plasma medicine and beyond.

References
[1] M. D. Wilkinson, et al., Sci. Data, 3, 160018 (2016).
[2] S. Franke, L. Paulet, J. Schäfer, D. O'Connell, and M. M. Becker, Sci. Data, 7, 439 (2020).