Motivation

This Infrastructure Use Case expresses the demand to extract implicit process and theory knowledge from experts to represent their domain-specific expertise in a formalized manner. Although this procedure depends on exemplary material systems to conduct this process, its theory is detached from concrete data.
The IUC requires ways of formalizing such expert knowledge by applying schemas based on other model contexts, to develop didactic frameworks that allow the structured formalization of the needed information and to have a working infrastructure at one’s disposal to implement and query the formalized knowledge expression.
The IUC works with dedicated PPs that tackle the challenge of formalization from an interdisciplinary, exemplary and collaborative point of view. In doing so, it vastly supports NFDI-MatWerk’s targets in the context of the FAIR-principles, since structured expert knowledge leads to standards, which then leads to interoperability.

Overview

Main requirements:
- Basis ontology advisory
- Ontology development support
- Multi-scale bridging ontologies
- Software interfaces for accessing workflow data semantically
- Implementation of DME for applying the representation
Main Task Area: TA-OMS
Other related Task Areas: TA-WSD
Possible connections within NFDI:
Material/Data: This depends on the selected expert scenarios, currently including Mat-o-Lab’s use cases on steel, copper, and fiber composites
Main Success Scenario: MSE-domain experts and interdisciplinary contributors from informatics and information science can jointly work on digitizing scientific workflows and develop their semantic representations.
Added value for the MatWerk community: Known and teachable processes for transforming expert domain knowledge into formalized structures as well as the resulting formalized workflows themselves.

Goals

  • Extract and Formalize Expert Knowledge: Develop methods to formalize implicit process and theory knowledge from domain experts into structured schemas.
  • Create Didactic Frameworks: Design didactic frameworks to facilitate the structured formalization and teaching of expert knowledge.
  • Develop Bridging Ontologies: Implement multi-scale bridging ontologies to connect expert knowledge with different model contexts.
  • Establish Software Interfaces: Create software interfaces for semantic access to workflow data.
  • Implement DME Application: Utilize the Digital Materials Environment (DME) for applying and querying the formalized knowledge.

Related Participant Projects

All Infrastructure Use Cases

NFDI-MatWerk
Funded by the German Research Foundation (DFG) under the National Research Data Infrastructure – NFDI 38/1 – 460247524

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