Building a research ecosystem where knowledge is contextualized, interconnected, interoperable, and accessible
Supporting knowledge discovery and research assessment
Democratising scholarly content
About SciLake
Why SciLake?
SciLake tackles the fragmentation, diversity, and disorganization of scientific knowledge, which hinders discovery and the extraction of valuable insights needed for informed decision-making in research.
How?
By offering an environment to assist scientists transform domain knowledge into standardized and interoperable Scientific Knowledge Graphs (SKGs) and enable the creation and use of value-added services built upon them.
What makes this challenging?
Domain experts often lack the specialized technical expertise required to perform this work independently. On the other hand, knowledge management experts alone cannot organize the information properly without domain-specific insights.
So, what is SciLake doing?
SciLake brings together partners with technical expertise in knowledge management, and experts from four scientific disciplines for pilot activities, in the domains of neuroscience, cancer, transportation, and energy. From this teamwork, we introduce the concept of the open Scientific Lake: a set of components designed for easy data access, improved knowledge discovery, research reproducibility, and other research-related activities. Domain experts can choose and adjust components to fit their specific needs, thanks to a highly customizable environment.
Let’s take a closer look!
SciLake Ecosystem
SciLake turns technical advances in the field of Scientific Knowledge Graphs (SKGs) into the Scientific Lake: a modular, reusable ecosystem that helps research communities build, connect, and explore domain‑specific and cross‑domain SKGs.
Enabling:
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Faster discovery
of relevant research and knowledge
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More transparency and trust
through better connections and context
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Reuse at scale
across domains, communities, and infrastructures
What we built
The Scientific Lake foundation
A shared toolbox to:
- Extract knowledge from text
- Improve interoperability across SKGs
- Make knowledge easier to query and reuse (searchable, queryable, and connected)
The Applications tier
Services built on top of the foundation, including:
- Impact‑driven discovery — to navigate large knowledge spaces and find relevant research faster
- Reproducibility assistance — to highlight connections and gaps that support more transparent and replicable research
Research Community Pilots
The SciLake project actively involves domain experts in the design and development processes, seeking valuable feedback on initial service prototypes. These experts bring real-life use cases from four diverse scientific fields: Neuroscience, Cancer Research, Transport Research, and Energy Research. Their input ensures that the developed services are highly configurable and adaptable to the unique needs of various large scientific communities, including those involved in cross-disciplinary research and collaboration.
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