REFSQ 2024
Mon 8 - Thu 11 April 2024 Winterthur, Switzerland
Oliver Karras

Registered user since Thu 25 Jun 2020

Name:Oliver Karras

I am a post-doctoral researcher and data scientist working at the Data Science and Digital Libraries Research Group at TIB – Leibniz Information Centre for Science and Technology. I hold a Bachelor of Science and a Master of Science degree, as well as a PhD in Computer Science from Leibniz Universität Hannover. As part of this work, my research addresses the development of the Open Research Knowledge Graph (ORKG) for application to engineering science. The focus is on the formalization, discoverability, and accessibility of methodological knowledge and information on semantically rich and machine-interpretable concepts for engineering problems.

I am a member of the Gesellschaft für Informatik e.V. (GI), deputy spokesperson of the Fachgruppe Requirements Engineering (RE), and a regular reviewer and member of various program and organizing committees of conferences and journals.

Before joining TIB – Leibniz Information Centre for Science and Technology, I was a research assistant and PhD student at the Software Engineering Group at Leibniz Universität Hannover. I worked as project leader of the DFG research project ViViReq and researched the integration of videos as a complementary communication medium in requirements engineering. My research focused on supporting requirements communication between stakeholders and the development team to foster the development of a shared understanding of the project vision of the system under development among all project partners involved. I have published my research in over 50 national and international publications covering diverse topics such as requirements engineering, social and empirical software engineering, machine learning, natural language processing, research knowledge graphs, and FAIR scientific data.

Affiliation:TIB - Leibniz Information Centre for Science and Technology
Research interests:Software Engineering, Requirements Engineering, Data Science, Knowledge Graphs


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