Due to limited structure, it is challenging for machines to access and process scientific knowledge. Scientific knowledge graphs have emerged as a potential solution for this issue. However, building such a knowledge graph demands significant manual effort and expertise in the respective domains, making the process time-consuming and cumbersome. Despite advancements in digital accessibility to scientific knowledge over recent decades, scholarly communication is still based on documents and managed by document repositories.

The Open Research Knowledge Graph [1] (ORKG, https://orkg.org/) as a FAIR Supporting Service, tackles the current challenge by offering research communities an easily accessible and sustainably managed infrastructure. It serves as a framework for creating, curating, publishing, and utilizing FAIR scientific knowledge and aims to shape a future scholarly publishing and communication where the contents of scholarly articles are FAIR research data. ORKG provides libraries for Python and R that enable loading or producing ORKG content in computational environments. Additionally, ORKG features various generic services that make use of FAIR scientific knowledge [2]. One of the prominent service is the ORKG comparison, which automatically compares research contributions of selected articles. Other services include knowledge visualization, thematic reviews, and observatories as virtual spaces for knowledge organization.

Topics to be covered in the tutorial:

• ORKG Introduction
• Methodology
• ORKG Services

1. Contributions
2. Comparisons
3. Visualization
4. Smart Review
5. Templates
6. Ask
7. Reborn Articles
8. Observatories

• Hands-on Practice with the ORKG

Speakers (tentative):

1. Sanju Tiwari, Professor, Sharda University & Researcher at TIB Hannover, Germany [Onsite]
2. Fidel Jiomekong Azanzi, Department of Computer Science, University of Yaounde 1, Cameroon [Online]
3. Anna-Lena Lorenz, TIB Hannover, Germany [Online]
4. Kheir Eddine Farfar, TIB Hannover, Germany [Online]
5. Stocker Markus, TIB Hannover, Germany [Online]
6. Jennifer D’souza, TIB Hannover, Germany [Online]

Duration: Half day

Target Audience: Students, Faculty, Researchers.

References:

1. Auer, S., & Mann, S. (2019). Towards an open research knowledge graph. The Serials Librarian, 76(1-4), 35-41.
2. Auer, S., Stocker, M., Karras, O., Oelen, A., D’Souza, J., & Lorenz, A. L. (2023, September). Organizing scholarly knowledge in the Open Research Knowledge Graph: an open-science platform for FAIR scholarly knowledge. In Proceedings of the Conference on Research Data Infrastructure (Vol. 1).