Semantic representation, networking and curation of quality-assured material data



Prof. Dr. Sören Auer


Dr. Javad Chamanara, Tatyana Sheveleva


Federal Ministry of Education and Research (BMBF)


August 2019 – July 2022

This project addresses challenges regarding curating, quality assurance and interoperability of research data in materials science and materials engineering. The focus is on ensuring the completeness, coherence and consistency of material and context data and their cross-portal findability and usability. The establishment of a common understanding of the structure of material data is achieved by an agile MatVocontology modeling driven by all stakeholders, which leads to a coordinated representation scheme formaterial data from simulation and experiment and corresponding context information. The stakeholder driven definition of quality metrics and classification schemes results in a maturity model on the basis of which automated validation and classification of material data and context information is made possible. The quality of research data is thus continuously evaluated and can be gradually increased. Alternatively, the possibility of validation is explored by standardized tests and data analysis with methods of machine learning. By implementing a library of mappings of typical data formats to MatVoc ontology, commonalities and differences between different formats and data structures become clear and can be used for development, exploration and visualization. Despite the remaining heterogeneity, this promotes gradual harmonization and convergence in formats and structures. Established open-source software tools will be adapted for the demonstration and the support of processes for research data management will be shown in several semantically networked material data portals. As a result, material data with contextual information (metadata) can be connected, searched and explored across portals and effectively reused and shared.

Role of TIB: Ontology development for the semantic representation of material data. For this purpose, a collaborative, agile and iterative ontology development methodology will be established and validated with the project partners and representatives of the professional community. Further focal points are the development of a classification scheme for material data, the creation of mappings from the original data structures to the ontology, and the preparation for reuse and transfer to other expert communities


  • Fraunhofer-Institut für Werkstoffmechanik (IWM)
  • Fritz-Haber-Institut (FHI) der MPG
  • InfAI Institut für Angewandte Informatik an der Uni Leipzig e.V.
  • Institut für Funktionelle Grenzflächen am Karlsruher Institut für Technologie

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