FAIR data interoperability, Ontology & Knowledge Graph Development

We are carrying out a number of projects that aim at increasing FAIRness and specifically interoperability of metadata in specific use cases. Core aspects are for example our collaborations to develop ontologies and knowledge graphs that describe and link data across scientific use cases and domains. See some of the projects that we are carrying out at the moment:

FAIR Assessment: This project explores the use of the FAIR assessment tool F-UJI to evaluate metadata of resarch data repositories. The evaluation is carried out by using a set of APIs to extract the datasets from the repositories and applying F-UJI to them. As a result, a numeric “FAIR score” is obtained for each data set. These scores can then be combined and compared, resulting in valuable insight on how the repositories could improve their metadata to become more FAIR.

DISO – Dislocation Ontology: Dislocation Ontology (DISO) is an ontology that defines the linear defect concepts and relations in crystalline materials. DISO represents the domain knowledge of linear defects by a formal representation, i.e., use logical axioms that the machine/computer could understand and take action. Ultimately, it enables interoperability and data handling between related MSE domains. A human readable documentation of DISO can be accessed via here.
https://github.com/Materials-Data-Science-and-Informatics/dislocation-ontology

MatWerk Knowledge Graph: The Materials Science and Engineering Knowledge Graph (MSE KG) for FAIR linked (Open) Data will represent the scientific and infrastructural status of the Material Science and Engineering community. It will serve as an overarching knowledge base for the community and application-level ontologies will be aligned with it. The project is developed within the framework of the NDFI-MatWerk consortium and is in an early development phase at the moment – stay tuned for updates!