What does the placement of the areas (bubbles) and the documents mean?

In general, the placement of areas (bubbles) can be interpreted as follows: Closeness of areas implies subject similarity. The closer two areas, the closer they are subject-wise.

What determines the size of the areas and the documents?

The calculation of the size of areas and documents differs between data integrations. In our PubMed integration, the size of a paper is determined by the citation count of the paper. In our BASE integration, the size of an area is determined by the number of documents it contains.

Why does the overview visualisation work better for some research topics than others?

The visualisation depends on the search results that we get for a given query. If there are for example not enough articles on the topic, or if the metadata quality is low, this will impact the visualisation.

How should I cite Open Knowledge Maps?

To cite an individual map, please use the citation provided for each map. To reference the website and the search, please use the following citation: Open Knowledge Maps (2019). Open Knowledge Maps: A Visual Interface to the World's Scientific Knowledge.

Where can I find more information on the background of Open Knowledge Maps?

Please see our Github page for a list of relevant research documents and project reports.

How can I include my repository / data source on Open Knowledge Maps?

Open Knowledge Maps uses BASE as its main data source. You can check if your data source is already indexed by BASE on their page.

How did Open Knowledge Maps come about?

Open Knowledge Maps was founded by Peter Kraker in 2015. Peter had worked on knowledge domain visualisations in his PhD and developed the first version of the open source visualisation framework Headstart.

Can I use Open Knowledge Maps to visualise my own collection(s)?

Using our Custom Services, you are able to embed Open Knowledge Maps services in your own discovery systems.

How is Open Knowledge Maps funded?

We are a charitable non-profit organization run by a group of dedicated team members and volunteers. We propose to fund Open Knowledge Maps in a collective effort.

How can I contribute?

You can contribute in a number of ways: we love to hear your feedback and ideas as this helps us to improve Open Knowledge Maps.

I would like to introduce Open Knowledge Maps to my peers. Do you have any materials available?

We do! Check out our training and promotional materials including presentations in English and Spanish.

How do I increase the visibility of my research online?

We have created a workshop for this topic entitled "Academic SEO". You can find a recording of this workshop on Youtube.

Are you available for collaborations and joint projects?

Yes! We partner with funders, research organizations and infrastructures that share our goals to develop innovative open science projects.

Last updated: July 27, 2026

Openknowledgemaps

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Introduction:

Visualize research topics and find relevant papers.

Launch Date:

November 5, 2014

Social links:

Monthly Visits:

131.4K

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Openknowledgemaps Overview

What is Open Knowledge Maps?

Open Knowledge Maps is an innovative AI-based search engine designed to enhance the visibility of scientific knowledge. It provides users with a visual overview of research topics, enabling them to discover relevant papers and identify key concepts within their field of interest. As the world's largest platform of its kind, Open Knowledge Maps aims to revolutionize the way individuals engage with scientific literature, making research more accessible and comprehensible for both academia and society.

How to use Open Knowledge Maps?

Visit the Open Knowledge Maps website at [openknowledgemaps.org](https://openknowledgemaps.org/index).
Use the search bar to enter your research topic or keywords.
Refine your search results by selecting document types and metadata quality preferences.
Browse the visual map generated, which clusters relevant papers and highlights important concepts.
Click on any paper to access its details, including abstracts and links to the full text.

What are the main features of Open Knowledge Maps?

Visual Mapping: Generates a visual representation of research topics, allowing users to see connections between papers and concepts.
Comprehensive Search: Access a wide range of document types including articles, theses, and reports from various disciplines.
Refinement Options: Users can filter results by document type and metadata quality to find the most relevant literature.
Open Science Commitment: Operates as a non-profit organization promoting open access to scientific knowledge.

Who is Open Knowledge Maps for?

Open Knowledge Maps is designed for researchers, students, and academics who seek to enhance their literature review process. It is particularly beneficial for those in the fields of science and academia who require efficient access to a wide array of scientific papers and concepts. Additionally, educators and institutions interested in promoting open science and improving knowledge accessibility can leverage this tool for their educational initiatives.

What are the use cases of Open Knowledge Maps?

Literature Reviews: Researchers can use Open Knowledge Maps to gather and visualize relevant literature on a specific topic, making it easier to identify key studies and gaps in research.
Academic Teaching: Educators can incorporate Open Knowledge Maps into their curriculum to teach students about literature search techniques and the importance of visualizing information.
Collaborative Research: Teams can utilize the platform to collectively explore and discuss relevant research papers, fostering collaboration and enhancing understanding of complex topics.

Openknowledgemaps Pros and Cons

Pros

Visual Overview of Research Topics: Open Knowledge Maps provides a visual representation of research topics, helping users to easily understand the relationships between different concepts and papers.
AI-Based Search Engine: As the world's largest AI-based search engine for scientific knowledge, it enhances the visibility of research findings for both science and society.
Open and Nonprofit Organization: Being a charitable nonprofit organization, Open Knowledge Maps promotes open science principles, making it accessible to everyone.

Cons

No cons data detected for this tool

Analytics of Openknowledgemaps

Openknowledgemaps Website Traffic Analysis

Visits Over Time

Nov 2025 - Jan 2026 All Traffic

#60

AI Tools Rank

131.37K

Monthly Visits

37.83%

Bounce Rate

3.32

Pages Per Visit

1:50

Visit Duration

267.71K

Global Rank

20.78K

Country Rank

Top Regions

Nov 2025 - Jan 2026 Desktop Only

Region	Percentage
🇮🇩 Indonesia	39.39%
🇩🇪 Germany	6.21%
🇧🇷 Brazil	3.26%
🇲🇽 Mexico	2.68%
🇺🇸 United States	2.23%

Top Keywords

Keyword	Volume	CPC	Estimated Value
maps	45.66M	$0.37	$2100.00
gmaps	1.02M	$2.54	$240.00
open knowledge maps	3.83K	$0.30	$3560.00
open knowledge	720	$0.79	$170.00
knowledge maps	430	$0.00	$390.00

Openknowledgemaps Reviews

We joined Open Knowledge Maps as a Supporting Member because it is an innovative tool for literature search and we are eager to support the further development of Open Knowledge Maps. Dr. David Johann, Head of Group Knowledge Management, ETH Library, ETH Zurich

I love how OKMaps breaks down the papers into clusters allowing me to identify themes in the literature and focus on papers that are most pertinent for my work. Girija Goyal, ReFigure Co-Founder, Staff Scientist at Wyss Institute for Biologically Inspired Engineering at Harvard University, USA

Open Knowledge Maps is a considerable reinforcement in the areas of open science & open access, which are central to our research services. Dr. Andrea Hacker, Open Access and Bern Open Publishing (BOP), University Library Bern

For more reviews, visit this link: https://openknowledgemaps.org/#what-users-and-supporters-say

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Openknowledgemaps Q&A

At the moment, we are using the relevance ranking provided by - depending on your choice - either the PubMed API or the BASE API. Both of them mainly use text similarity between your query and the article metadata to determine the relevance. PubMed has a detailed description of their relevance ranking. BASE uses Lucene, which describes their ranking as well.

We want to keep the number of documents to a manageable amount. 100 documents are already 10 times more content than is presented on a standard search results page. Nevertheless, we are investigating how to enable the exploration of larger amounts of content, while keeping cognitive load to a minimum. At the moment, you can drill deeper into a topic by providing a more specific search query.

At the moment, we are using the top 100 documents from the selected data source to create the map. While this is already 10 times more content than is presented on a standard search results page, we may still miss important documents due to this restriction. In the future, we hope to overcome this problem by including more documents in a map and by enabling users to manually add documents to automatically created maps.

While you wait, each query is processed live: first, it is sent to the selected data provider (either PubMed or BASE), which returns the most relevant results for it. This process takes around 15 seconds. Then, our AI pipeline analyses this data to create a knowledge map for it, which takes another 15 seconds.

We use only trusted data providers such as BASE, PubMed and OpenAIRE. These providers carefully review the data sources to make sure that they only include academic content. However, even with the most careful review, mistakes can occur.

The grouping of documents is based on article metadata. Currently, we use titles, abstracts, authors, journals, and subject keywords to create a word co-occurrence matrix between articles. On top of this matrix, we perform clustering and ordination algorithms.

Area titles are created from subject keywords of documents that have been assigned to the same area. We select those keywords and phrases that appear frequently in one area, and seldom in other areas.

In some cases, area titles can be multilingual, when there are documents in different languages in the knowledge map or when keywords are provided in more than one language.

For more FAQs, please visit this link: https://openknowledgemaps.org/faq