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Material solutions for low carbon energy

General description of use case

The European Union has prioritized materials as a Key Enabling Technology (KET) to enable the transition to a knowledge-based, low carbon, resource-efficient economy and has proposed a materials roadmap to address the technology agenda of the SET-Plan. With the imperative to change the energy technology mix to respond to the challenges of decarbonization and security of energy supply, the need for new materials and processing routes is overriding. New efficient and cost-competitive energy technologies are urgently needed. In this respect, materials research and control over materials resources are becoming increasingly important in the current global competition for industrial leadership in low carbon technologies. Two EERA Joint Programs (Nuclear Materials and AMPEA) are directly involved in materials research for energy applications and several other Joint Programs are interested in new materials to improve the efficiency of energy technologies. To speed-up the discovery of new materials for energy technologies, Innovation Challenge No. 6 of the Mission Innovation Initiative is devoted to the discovery of new materials. This Innovation Challenge aims at accelerating the innovation process for high performance, low-cost clean energy materials and automating the processes needed to integrate these materials into new technologies. The challenge is to combine advanced theoretical and applied physical chemistry/materials science data, as well as data on the life cycle of materials and material compounds with next-generation computing infrastructures, artificial intelligence, and robotics tools. The goal is to create a fully integrated approach.

Materials research is characterized by strong multidisciplinary research in which both, converging technologies and cooperation, should be exploited to speed up application-oriented research activities. This is not always the case due to the extremely different technological fields where materials are employed (in the energy sector and beyond). Indeed, each technological field has often developed its own terminology, experimental set-ups, research procedures, and, consequently, its own standards in data management. Therefore, it can be argued that in the field of materials for energy data the state of the art is the following: Openness is low to medium, re-usability is low to medium, and barriers are high. Finally, actions put in place are rare (low to medium). The availability of an open data infrastructure covering as many research fields as possible could increase opportunities to develop new research programs, defragment the materials for energy communities, avoid the duplication of research activities, speed-up the discovery of materials, and increase the understanding of how energy systems could better benefit from existing and new materials. Many databases are already available but a large amount of data is currently produced in laboratories, not organized to be shared. Moreover, databases do not follow common formats preventing inter-operability and re-usability. In view of the intended automatization, it is important that access to databases is machine-actionable. Finally, due to the strong connection with industries, questions of open data access need to be explored and new business models need to be developed.

List of selected databases

During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:

Name of database Short description Reasoning of choice Current state of FAIR/O principles Target of FAIR/O to achieve within EERAdata
Database 1 Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx." Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of WS1UC3. What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page of WS1UC3. What FAIR/O target was decided?
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Metadata assessments

Databases above were assessed with respect to their current meta practices. The table below summarizes the current state and issues identified during WS 1:

Name of database Type of metadata provided Extend of metadata provided Level of implementation of FAIR/O principles Frameworks for metadata used Technical implementation of metadata
Database 1 Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? Summarize: Is it rich or basic metadata provided for each of the types? Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of WS1UC3. What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? How are metadata implemented? As xml, plain text, RDF, etc.
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