Scientific Knowledge Graph Foundation
(SKG Foundation)
Vision Leveraging an ecosystem of interoperating knowledge graphs enables both human and machine-driven utilization of scientific knowledge, fostering innovation, facilitating open science, valorisation of research findings, and addressing grand societal challenges |
Mission The Scientific Knowledge Graph Foundation aims to advance the sociotechnical scholarly communication infrastructure in its capacity to produce, curate, and use machine-actionable scientific knowledge. As such, the foundation aims to shape a future scholarly publishing and communication where the scientific knowledge published in scholarly articles is FAIR research data. |
A wide range of knowledge graphs exist in the academic and scholarly domain, each of it with a specific focus, ranging from domain specific scientific knowledge graphs to more generic graphs that gather meta-information. The Scientific Knowledge Graph Foundation facilitates the collaboration and coordination among scholarly knowledge graphs to further the federation towards an integrated, interoperable research infrastructure, fostering cross-disciplinary research, maschine-actionability of knowledge and research outputs (publications, software, data) to facilitate Open Science and the valorisation of scientific knowledge.
On the European level activities have been started to make knowledge graphs with meta-information interoperable. Another collaboration in the field of Knowledge Graphs is facilitated by the Nationale Forschungsdaten Infrastruktur (NFDI, National Research Data Infrastructure). The NFDI aims to make valuable data from science and research systematically accessible and interconnected. The goal of the NFDI is to provide access to these data in a sustainable and qualitative manner for the entire German science system [link]. An example is NFDI4DataScience, which addresses Knowledge Graphs in its Task Area 2, to improve the FAIRness of Data Science artifacts including research datasets, benchmarks, machine learning models and research software (code and executables).
The Scientific Knowledge Graph Foundation takes a complementary approach and addresses the interconnection of knowledge graphs across scientific domains to respond to the needs and requirements of inter-domain research.
The grand challenges of our time can only be addressed in a cross-domain approach and thus interconnectivity of domain specific knowledge is of utmost importance.
Concrete challenges:
- interconnectivity of SKGs across scientific domains
- Interoperability between existing SKGs
- Facilitate cross-domain access to and use of knowledge