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This document summarises the results of an online community survey, which was conducted from 2nd June 2020 to 31st July 2020 within the framework of the project "Quality Assurance and Linking of Research Data in Plasma Technology - QPTDat" (funded 2019–2022 by the Federal Ministry of Education and Research (BMBF) in Germany, project numbers 16QK03A, 16QK03B and 16QK03C). The survey aimed at the evaluation of the status quo regarding research data management in the field of low-temperature plasma science as well as the identification of experimental and computational methods with great relevance to be used as a first reference for the design and testing of quality criteria and (meta)data models for research data management., The QPTDat project teams at Leibniz Institute for Plasma Science and Technology (INP), FIZ Karlsruhe – Leibniz-Institut für Informationsinfrastruktur GmbH and Hamburg University of Applied Sciences (HAW Hamburg) supported this work. The work was funded by the Federal Ministry of Education and Research (BMBF) under grant numbers 16QK01A, 16QK01B, 16QK01C. The authors are responsible for the content of this publication.

Additional file 1. Permission to use the devices on patients.

Additional file 4. Test controls of mechanical cleaning methods.

Additional file 3. Scanning electron micrograph of scratched titanium.

Additional file 2. Images of the water contact angle measurement.

The necessity and potential of systematic archiving and publication of digital research data is currently a hot topic in the scientific landscape, due to various benefits such as ensuring reproducibility of research results and providing the basis for data-driven science. This requires measures to ensure data quality and particularly a documentation of stored data by means of metadata, which is understandable to both humans and machines. Machine-actionable metadata is not only important for findability and interoperability of the data but also enables automated data processing. This contribution introduces a workflow for data and metadata, which uses programmatic data aggregation, electronic lab notebooks, ontology-based metadata, and blockchain protocols for partly automated processing and documentation of raw data as well as quality assured data publication, respectively. The practical relevance of the suggested (meta)data workflow is demonstrated at the example of highly resolved current measurements for pulsed dielectric barrier discharges in a nitrogen-oxygen gas mixture., This work was supported by the BMBF under grants 16QK03A, 16QK03B, 16QK03C and the DFG under grant 408777255.

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)., The Federal Ministry of Education and Research (BMBF) has supported this work under the grant marks 16QK03A, 16QK03B, and 16QK03C.

On October 28 to 29, 2020, the project QPTDat hosted the virtual workshop on FAIR Research Data in Plasma Medicine. This is a summary report of the workshop. The goal of the workshop was to bring together researchers in the field of plasma medicine with research data management experts to discuss requirements and possibilities for research data management in accordance with the FAIR principles. Research data management experts provided an overview over existing procedures and ideas for the provision and usage of quality assured research data, e.g. as a basis for data-driven science. On the other side, researchers in the field of plasma medicine and plasma technology introduced different use cases and pointed out specific demands and possible challenges. On this basis, approaches for the further development of an ontology, metadata standards, and quality criteria supporting a simplified publication and re-use of data in the field of plasma medicine were worked out in the course of the workshop., Funded by the German Federal Ministry of Education and Research (BMBF) under grants 16QK03A, 16QK03B, and 16QK03C.

The findability (F), accessibility (A), interoperability (I), and re-usability (R) of research data are essential and acknowledged factors for an efficient re-use of data, e.g. for data driven science. However, in the field of plasma technology there is currently a lack of common standards and tools to publish data according to these FAIR data principles. To address this issue, the present contribution reports on the development of a modular metadata model for the representation of subject- and method-specific metadata in the field of plasma technology, which is based on the core plasma metadata schema, Plasma-MDS (https://arxiv.org/abs/1907.07744). The linking and semantic description of the metadata modules are carried out via ontologies. The developed tools and services are made available via a plasma technology knowledge graph and the data platform https://www.inptdat.de/. They are intended to be reviewed and further developed by the low-temperature plasma community to provide a common basis for open science and research data management according to the FAIR principles., Funded by the German Federal Ministry of Education and Research (BMBF) under grants 16QK03A, 16QK03B, and 16QK03C.

The need to implement the FAIR data principles and structured research data management in our research workflows is growing. On the one hand, this is due to pressure, e.g. from research funders and publishers. But on the other hand, it is particularly because the advantages thus achieved in the use of data-driven research methods are becoming increasingly obvious. In my presentation I will introduce practical tools and workflows that aim to integrate research data management into the everyday work of scientists and to take the FAIR principles into account as early as possible in the life cycle of research data, avoiding additional work for the researcher as far as possible. While my examples are from practical implementation for plasma technology research, the approaches are generally applicable to any research area involving different research methods and domains., The work was supported by grants 16QK03A, 16QK03B, 16QK03C (BMBF).