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FAIR Enough: Develop and Assess a FAIR-Compliant Dataset for Large Language Model Training?
The rapid evolution of Large Language Models (LLMs) highlights the necessity for ethical
considerations and data integrity in AI development, particularly emphasizing the role of …
considerations and data integrity in AI development, particularly emphasizing the role of …
[HTML][HTML] A FAIR catalog of ontology-driven conceptual models
Multi-domain model catalogs serve as empirical sources of knowledge and insights about
specific domains, about the use of a modeling language's constructs, as well as about the …
specific domains, about the use of a modeling language's constructs, as well as about the …
Building expertise on FAIR through evolving Bring Your Own Data (BYOD) workshops: describing the data, software, and management-focused approaches and their …
ABSTRACT Since 2014,“Bring Your Own Data” workshops (BYODs) have been organised to
inform people about the process and benefits of making resources Findable, Accessible …
inform people about the process and benefits of making resources Findable, Accessible …
The extended EA ModelSet—a FAIR dataset for researching and reasoning enterprise architecture modeling practices
Conceptual modeling research is increasingly investigating the application of artificial
intelligence (AI) and machine learning (ML) to automate tasks like model creation …
intelligence (AI) and machine learning (ML) to automate tasks like model creation …