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A Research Data Infrastructure for Materials Science

Brandt, Nico ; Schoof, Ephraim ; Zschumme, Philipp ; Selzer, Michael

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Abstract

In materials science, the understanding of new materials is becoming increasingly complex. Without suitable analytical methods, the ever-increasing amounts of data from simulations and experiments will no longer be graspable. An important aspect to be able to perform corresponding data analyses smoothly is the structured retrieval of research data and corresponding metadata. In addition to uniform data storage, such systems can overcome inter-institutional hurdles, compare theoretical and experimental data and offer reproducible workflows for data analysis. Furthermore, linking data with persistent identifiers enables other researchers to reference them in their work. In order to support researchers in meeting the above-mentioned requirements, we conceptualize and develop the research data infrastructure Kadi4Mat, the Karlsruhe Data Infrastructure for Materials Science. This infrastructure is to be used in particular in the materials sciences and is being advanced within the framework of several research projects. The aim is to combine the possibility of structured data storage and exchange with documented and reproducible data analysis and visualization. These features can be split into the two components repository and electronic lab notebook (ELN). The focus on the repository component is on the handling of warm data, i.e. unpublished data that is yet to be analysed further. It can therefore be best described as a community repository. Sharing of data within the own working group or with cooperation partners is easily possible, while integrations are offered to directly publish data on an external repository focused on long term storage and on providing persistent identifiers, which make the data usable by the whole scientific community. A central part of the ELN component are the so called workflows, which describe a set of highly user- and application-specific tools that are executed in a well-defined order. Workflows offer a documented and reproducible way to automate different scientific steps, including running analysis tools or fetching data from an experimental device. Because the focus is in a different direction than classic ELNs, we refer to this component as an ELN 2.0. In general, the development of the research data infrastructure follows a bottom-up approach. Instead of developing concepts in advance, to cover as many use cases as possible, a basic technical infrastructure is established first. Due to the heterogeneous nature of materials science, most features are kept very generic. As a positive side effect, an extension of the research data infrastructure to other disciplines is possible in the future. The eventual goal includes covering the entire scientific workflow of daily research work, by allowing all kinds of different workflows to be represented and exchanged in our framework.

Document type: Conference Item
Place of Publication: Heidelberg
Date Deposited: 23 Apr 2021 10:21
Date: 2021
Number of Pages: 1
Event Dates: 04.03. - 05.03.2021
Event Location: Heidelberg
Event Title: E-Science-Tage 2021: Share Your Research Data
Faculties / Institutes: Service facilities > Computing Centre
Collection: E-Science Days 2021
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