A Perspective on Digital Knowledge Representation inMaterials Science and Engineering

A Perspective on Digital Knowledge Representation inMaterials Science and Engineering

Bernd Bayerlein, Thomas Hanke, Thilo Muth, Jens Riedel, Markus Schilling,Christoph Schweizer, Birgit Skrotzki, Alexandru Todor, Benjami Moreno Torres,Jörg F. Unger, Christoph Völker, and Jürgen Olbricht

The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, predominantly in natural language in data silos. This problem can be equally applied to the heterogeneous research data from materials science and engineering. In this domain, ways and solutions are increasingly being generated to smartly link material data together with their contextual information in a uniform and well-structured manner on platforms, thus making them discoverable, retrievable, and reusable for research and industry. Ontologies play a key role in this context. They enable the sustainable representation of expert knowledge and the semantically structured filling of databases with computer-processable data triples.

Adv. Eng. Mater.2022, 2101176

Congratulations to all authors! :grinning:
@bernd.bayerlein @thomas.hanke @markus.schilling @birgit.skrotzki @alexandru @junger

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