FAIRlead: A Conceptual Framework for a Model Driven Software Development Approach in the Field of FAIR Data Management

Andreas Schmidt, Andreas Schmidt, Mohamed Anis Koubaa, Nan Liu, Philipp Schmurr, Karl-Uwe Stucky, Wolfgang Süß

2024

Abstract

The publication of scientific results together with the underlying experiments is an important source of further research. In 2016, the “FAIR Guiding Principles for scientific data management and stewardship” were published, in which the authors postulate a series of guidelines for improving the (F)indability, (A)ccessibility, (I)nteroperability and (R)eusability of digital information (FAIR). The point (I)nteroperability deals with the prerequisites for the reusability of digital objects. The central point here is the need to have a common understanding of the meaning of digital objects. This understanding is provided by formal languages of knowledge representation (ontologies), which describe the actual data. These descriptions of data are also known as metadata. As part of our current work at the Institute for Automation and Applied Computer Science (IAI) at KIT, we are implementing novel concepts and technologies for the sustainable handling of research data using high-quality metadata. As part of this work, we plan to develop a software tool that can be used to enrich data with suitable metadata and thus automate the process of making research results available. A key requirement is that the tool must be independent of the underlying domain. In order to be able to deal with data from any domain, we have opted for a model-driven approach in which an ontology, and possibly other platform-specific information, are input for a software generator, which then generates an (interactive) tool for specifying the metadata and linking it to the data itself. The generated tool includes the complete software stack, starting with a user interface, programmatic APIs for connecting additional application logic, and a persistence component. How these individual layers are realized is not specified, but defined by the mapping rules of the software generator, which also opens up the possibility of generating and evaluating different variants of the software.

Paper Citation

in Harvard Style

Schmidt A., Anis Koubaa M., Liu N., Schmurr P., Stucky K. and Süß W. (2024). FAIRlead: A Conceptual Framework for a Model Driven Software Development Approach in the Field of FAIR Data Management. In Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS; ISBN 978-989-758-716-0, SciTePress, pages 323-330. DOI: 10.5220/0013013700003838

in Bibtex Style

@conference{kmis24,
author={Andreas Schmidt and Mohamed Anis Koubaa and Nan Liu and Philipp Schmurr and Karl-Uwe Stucky and Wolfgang Süß},
title={FAIRlead: A Conceptual Framework for a Model Driven Software Development Approach in the Field of FAIR Data Management},
booktitle={Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS},
year={2024},
pages={323-330},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013013700003838},
isbn={978-989-758-716-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS
TI - FAIRlead: A Conceptual Framework for a Model Driven Software Development Approach in the Field of FAIR Data Management
SN - 978-989-758-716-0
AU - Schmidt A.
AU - Anis Koubaa M.
AU - Liu N.
AU - Schmurr P.
AU - Stucky K.
AU - Süß W.
PY - 2024
SP - 323
EP - 330
DO - 10.5220/0013013700003838
PB - SciTePress