Renat Shigapov, Forschungs­datenzentrum / BERD@NFDI: FAIR data und knowledge graphs (März 2023)

Dr. Renat Shigapov ist Data Science Consultant am Forschungs­datenzentrum der Universität Mannheim, Data Scientist für BERD@NFDI und Koordinator der NFDI-Arbeits­gruppe „Knowledge Graphs“. Renat wurde an der Fakultät für Physik des Karlsruher Instituts für Technologie promoviert. An der Universität Mannheim ist er Ansprech­partner für Forschende, die Unter­stützung bei der Automatisierung wissenschaft­licher Aufgaben, Data-Science-Anwendungen und FAIR-Forschungs­daten­management benötigen.


What is your current research topic?

I’m trying to make business, economic and related data in Germany FAIR (findable, accessible, interoperable and reusable) through the project BERD@NFDI. I work on structuring and semantically enriching the unstructured data and on releasing the structured (meta)data as knowledge graphs. I also support researchers of the University of Mannheim in automating scientific tasks, data science applications and FAIR research data management. For example, if a researcher has a printed book with valuable data, we can digitise, OCR, structure and release it as a knowledge graph with API and SPARQL endpoint.

For those who have not yet delved deeply into the topic of Data Science: How would you explain to children what you are working on?

I would ask children about their favourite books. Then I would say that they are very smart in comparison to computers because they understand what’s written in the books. Computers don’t understand texts and need help from humans to “understand” texts. I help computers to “understand” texts, and then computers help us to search through a lot of books and to answer our questions about the stories from the books.

Everyone talks about Data Science – how would you describe the importance of the topic for yourself in three words?

Automating every task

How can you support researchers of the University of Mannheim in Data Science applications?

Researchers can contact me with respect to automating their research tasks using data science algorithms in every phase of their research project (planning, executing and finishing). I can support with 1) getting data via API, SQL, SPARQL and web-scraping, 2) processing, cleaning, analysing, structuring and linking data, 3) publishing, archiving and sharing data & metadata in knowledge graphs as FAIR linked open data. Researchers can also contact me, if they have an idea for a new data science service at the University of Mannheim.

How high is the value of Data Science for your work? Would your research even be possible without Data Science?

Data Science plays crucial role in infrastructural projects aimed for Findable, Accessible, Interoperable and Reusable data. FAIR data implies FAIR metadata. To make metadata FAIR at large scales, data science algorithms and knowledge graphs are needed. Can we do it without data science algorithms? Not really.

What does the Research Data Center offer for researchers at the University of Mannheim with respect to Data Science?

We offer Data Science as a service, FAIR data as a service and courses for data literacy. We would like to improve these services in the next years. Feedback from researchers would be very welcomed.