Big data is playing a pivotal role in achieving a disruptive acceleration of the discovery of new technologies, including batteries, required by a sustainable future. No research group, centre, or institution can alone produce this quantity and variety of data, which involves multiple time and length domains. Withing the BATTERY 2030+ consortium and mainly driven by the BIG-MAP project, during the last 5 years, researchers have worked to establish a data infrastructure able to store and share curated data from multi-source and multi-fidelity simulations, experiments, and machine learning models. The first step of this process has been to establish a consensus on research data management and on the way we compile interoperable data management plans (DMP). The core component of the DMP is “data tables” which describes in detail which data is produced and what their flow is in the project.[1] By cross-linking the DMPs of the different projects, we have been able to identify collaborations between the projects based on data sharing, as shown in the figure below:
The DMP also includes information on where the data should be store. Most BATTERY 2030+projects have access to dedicated data repositories in the Materials Cloud Archive.[2] The archive has three level of openess. At the lowest level of openess, data are accessible only by the project. At a more open level, the data can be shared across the entire BATTERY 2030+ consortium. At the highest level of openess, the data are fully openly and accessible to the research community. This approach allows to create an open research community based on data sharing. Together with data, scripts can be collected in App Stores, such as the BIG-MAP App Store.[3] Part of the data infrastructure is also the definition of standards and protocols for simulations and experiments, that can be guidelines for the implementations of electronic laboratory notebooks [4] well as a battery ontology (e.g., BattINFO).[5] A BATTERY 2030+ memorandum on research data management and standards can be found here [6].
Jose Maria Castillo Robles and Ivano Eligio Castelli,
Danmarks Tekniske Universitet
Kongens Lyngby, Denmark
[1] Castelli, I. E.; Arismendi-Arrieta, D. J.; Bhowmik, A.; Cekic-Laskovic, I.; Clark, S.; Dominko, R.; Flores, E.; Flowers, J.; Frederiksen, K. U.; Friis, J.; Grimaud, A.; Hansen, K. V.; Hardwick, L. J.; Hermansson, K.; Königer, L.; Lauritzen, H.; Cras, F. Le; Li, H.; Lyonnard, S.; Lorrmann, H.; Marzari, N.; Niedzicki, L.; Pizzi, G.; Rahmanian, F.; Stein, H.; Uhrin, M.; Wenzel, W.; Winter, M.; Wölke, C.; Vegge, T. Data Management Plans: The Importance of Data Management in the BIG-MAP Project. 2021. Arxiv: 2106:01616
[2] https://archive.big-map.eu
[3] https://big-map.github.io/big-map-registry/
[4] http://big-map-notebook.eu
[5] https://github.com/BIG-MAP/BattINFO
[6] https://battery2030.eu/research/research-data-management-rdm-standards/