Survey
Collection of Scientific Knowledge Graphs (SciKGs) resources
Understand SciKGs: The Backbone of Al for Science
SciKGs reshape research paradigms by converting multi-source scientific knowledge into semantic networks, enabling machine reasoning for tasks like drug discovery and material design.
Leverage Our Curated Resource Hub
Built on a definitive survey, our open GitHub-hosted navigation station provides access to key databases, tools, and applications with direct links and brief explanations.
Accelerate Discovery with SciKG-LLM Collaboration
We deconstruct the emerging ScikG-LLM synergy paradigm to automate scientific discovery, lowering entry barriers and empowering researchers to drive Al-powered progress.
SciKG Resource Hub
SciKG commonly used public databases
authoritative structured data sources covering the fields of biology, chemistry, and materials, which are the cornerstone of building high-quality SciKG.
ScIKG construction and maintenance tool
a software and platform used for tasks such as knowledge extraction, ontology alignment, graph fusion, dynamic updates, and inference completion.
SciKG core application scenario
Focusing on four major application scenarios: drug development and optimization, omics interpretation and analysis, chemical reactions and synthesis, and material design and synthesis.
SciKG-LLM collaborative resources
frameworks, models, and application cases that support bidirectional empowerment of both (such as knowledge grounding, semantic reasoning, hypothesis generation).