Authors:
Andreas Schmidt
1
;
2
;
Mohamed Anis Koubaa
1
;
Nan Liu
1
;
Philipp Schmurr
1
;
Karl-Uwe Stucky
1
and
Wolfgang Süß
1
Affiliations:
1
Institute for Automation and Applied Computer Science, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
;
2
Department of Computer Science and Business Information Systems, Karlsruhe University of Applied Sciences, Karlsruhe, Germany
Keyword(s):
Code Generation, Metadata, Ontology Based Engineering, FAIR.
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 me
tadata. 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.
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