Visual topic overviews
Enter a topic or keyword to get a topical overview of matching research outputs. The map groups similar resources so you can see main areas at a glance.
Open Knowledge Maps
RivendicaOpen Knowledge Maps turns research searches into visual knowledge maps, helping researchers, students, and institutions find relevant literature, concepts, and open access resources faster.
Overview
Open Knowledge Maps is a visual discovery tool for scientific literature. It takes a research question or keyword and turns matching publications into a knowledge map that shows the main areas of a topic, related resources, and key concepts.
The service is positioned as an open, charitable non-profit platform. It is designed to support literature search for researchers, students, and institutions that want a clearer starting point before they dig into individual papers.
Features
Similarity-based clustering
The AI pipeline clusters related publications together, which helps separate broad search results into subject areas and makes ambiguous queries easier to scan.
Concept labeling
Area labels are generated from subject keywords and related metadata so users can identify the concepts that define each cluster.
Open-content emphasis
Open access resources are highlighted, and many can be opened directly in the interface. When they are not available there, the full text is only a click away.
Live data-provider workflow
The FAQ explains that maps are built from live requests to selected data providers, currently including PubMed and BASE, using a controlled set of top results.
Custom services for institutions
Organisations can use Custom Services to embed Open Knowledge Maps components in their own discovery systems and workflows.
Use Cases
Starting a literature search
Start a literature review with a visual map that shows the main areas of a topic, so you can move from a broad question to the papers most likely to matter.
Refining broad or ambiguous topics
Use the clustered bubbles to break apart an ambiguous or multidisciplinary query and focus on the sub-areas that are actually relevant to your work.
Finding accessible research outputs
Identify open access papers quickly when you want content you can read immediately or share with others without leaving the interface.
Orienting newcomers to a field
Use the map as a teaching or orientation aid when introducing a research field, since it gives newcomers a visual way to learn the field’s concepts and structure.
Institutional discovery workflows
Embed Open Knowledge Maps components into an internal discovery system when an organisation wants AI-based literature discovery within its own workflows.
Pros and Cons
Pros
- Provides an immediate visual overview of a research topic.
- Clusters related resources so users can separate broad search results into themes.
- Highlights open access resources and often lets users open them directly in the interface.
- Uses trusted scholarly data providers such as PubMed, BASE, and OpenAIRE.
- Offers institutional Custom Services for embedding discovery components into other systems.
Cons
- Maps currently use only the top 100 resources from the selected data source, so some relevant items may be missed.
- The system relies on metadata such as titles, abstracts, authors, journals, and subject keywords, which can limit accuracy when metadata is thin or inconsistent.
- The FAQ notes that creating a map can take up to around 30 seconds because results are fetched live and then processed by the AI pipeline.
FAQ
How does Open Knowledge Maps create a knowledge map?
Open Knowledge Maps uses a live query workflow. A search is sent to a selected data source such as PubMed or BASE, and the system then builds a knowledge map from the returned results.
Why do some important resources not appear in a map?
The FAQ says the current maps use the top 100 resources from the selected data source. This keeps the map manageable, but it can also mean some relevant items are not shown.
Is the map based on full text or metadata?
The map is built from article metadata rather than full text. The FAQ says it uses titles, abstracts, authors, journals, and subject keywords to cluster related publications.
What is Open Knowledge Maps useful for?
The product is designed to work with common scholarly search tasks. It helps you get an overview of a topic, separate related areas, and identify concepts before you continue a literature search.
Can institutions integrate Open Knowledge Maps into their own systems?
The site states that organisations can use Custom Services to embed Open Knowledge Maps components into their own discovery systems and workflows.
Quick Facts
- Category
- Research discovery
- Platform
- Web
- Primary users
- Researchers, students, and research institutions
- Data sources
- PubMed, BASE, and OpenAIRE
- Business model
- Charitable non-profit; supporting membership for organisations
- Domain
- openknowledgemaps.org