Open Knowledge Maps for Web

Visual explorer for scholarly research

Open Knowledge Maps is a web-based platform that applies artificial intelligence to make scientific literature easier to find and understand. Instead of presenting long lists of search results, it generates visual maps that show how topics, papers, and key ideas connect, helping users quickly locate the most relevant publications and extract the main concepts from a body of research.

Core features and benefits

• Interactive topic maps that reveal relationships between research areas and important papers.
• Automated extraction of central concepts and summaries from groups of publications.
• Search functionality tailored to explore themes rather than just match keywords.
• Components available for integration into institutional systems to support custom workflows.
• A user-focused interface designed to lower barriers to discovery for newcomers and experts alike.

Who uses it and how it can be embedded

Open Knowledge Maps is useful for individual scholars performing literature reviews, students beginning research projects, and research support staff who need better ways to present subject overviews. Organizations can embed its modules into internal portals or combine them with existing discovery tools to create collaborative environments for teams and communities.

Philosophy, governance, and sustainability

Built on open-science values, the project operates as a non-profit initiative committed to creating an inclusive, long-term infrastructure for research discovery. Its development emphasizes co-creation with users, transparent practices, and accessibility for people from varied backgrounds and disciplines.

Alternatives and licensing

• Interactive Mathematics (paid) — a commercial product that can serve as an alternative for users or institutions seeking a proprietary solution with dedicated support.
• Other open and commercial discovery tools exist; evaluate each on integration options, cost, and the extent to which they emphasize visual mapping versus traditional search results.