EBRAINS Advances European Effort to Connect Scientific Research Through Knowledge Graphs

The EU-funded SciLake project has now concluded its three-year mission to make scientific knowledge easier to discover, connect and reuse. As part of this Europe-wide effort, EBRAINS contributed to the neuroscience pilot, helping demonstrate how advanced, domain-specific knowledge graphs can support better navigation of complex research fields.

EBRAINS’ role: enriching the neuroscience knowledge landscape 

Neuroscience is one of four thematic pilots chosen by the project to build field-specific knowledge graphs, along with cancer, transportation and energy. Together with neuroscience experts at the University of Oslo and Athena Research and Innovation Center, EBRAINS led the neuroscience pilot, building on the OpenAIRE Graph and integrating metadata from the EBRAINS Knowledge Graph. While SKGs are not new, SciLake brings two major contributions: domain-specific implementations and the aggregation of multiple types of metadata from various repositories.  

As scientific publishing accelerates, one challenge grows steadily more complex: how to navigate and connect the expanding body of research outputs. Neuroscience data is particularly challenging to aggregate and interpret as it is methodologically diverse. This makes it difficult for researchers to trace how datasets, tools and publications relate to one another – a challenge SciLake can significantly improve. 

Using AI to combat data fragmentation 

The multilayer structure of these graphs provides more metadata than previous knowledge graphs, and more specifically, it enables users to identify questions in a meta-analysis style by highlighting research outputs based on their impact. These new knowledge graphs use AI techniques like machine learning and natural language processing to automate the extraction, linking, and enrichment of information from vast and heterogeneous research outputs to identify relationships and trends, beyond what manual analysis can achieve alone. Essentially, SciLake tackles the fragmentation and disorganisation of scientific knowledge, which hinders the discovery of valuable insights, and facilitates informed decision-making in research. 

By contributing expertise in interoperability and neuroscience data standards, EBRAINS helped ensure that the resulting domain-specific knowledge graph reflects the realities of the field and can serve as a more powerful discovery tool for researchers. The pilot aimed to improve metadata completeness, highlight influential research outputs, and support meta-analysis–style queries that are difficult to perform with traditional search tools. 

Today’s research landscape is more “open” but still hard to use in practice because outputs are abundant yet scattered across many systems and formats. This makes it difficult to connect evidence and extract reliable insights. Knowledge graphs address this issue and provide reliable context for AI. They turn fragmented outputs into structured and interlinked representations with provenance, giving AI systems richer context than isolated documents can provide. This matters not only for performance but also for trust because knowledge graphs make relationships explicit, support traceability and updates, and create the conditions for human correction and feedback loops. 

SciLake is only one example of a clear vision for European long-term strategic priorities: to offer solutions to critical challenges in research, innovation, and societal development. Through collaborative European initiatives such as SciLake, the institutions involved contribute not only to scientific discoveries, but also to the evolving digital foundations that support them.  

Contact: Elisabet García González, PhD 

Networking & Communications Advisor 

University of Oslo | Neuroinformatics Norway | EBRAINS Norway 

e.g.gonzalez@medisin.uio.no