Answers to the most frequently asked questions about Open Knowledge Maps.

Q1 How do you define "most relevant" when you are talking about most relevant papers?

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 (via Solr), which describe their ranking as well on this page.

Q2 Why are you only using the top 100 papers to create the map?

We want to keep the number of papers to a manageable amount. 100 papers are already 10 times more content than is presented on a standard search results page. Nevertheless, we are investigating on 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. One way to do this is to expand your query with the topic of a sub-area.

Q3 Why are there important papers missing in my map?

At the moment, we are using the top 100 papers 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 papers due to this restriction. In addition, we can only use papers that have an abstract - otherwise we do not have enough content for our automatic analysis.
In the future, we hope to overcome this problem by including more papers in a map and by enabling users to manually add papers to automatically created maps. In the meantime, please let us know of cases of major omissions via

Q4 Are the maps generated based on full text analysis or on metadata analysis?

The grouping of papers 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. The labels for the sub-areas (bubbles) are generated from the subject keywords of the articles in this area. In cases where they are missing from the metadata, we approximate them from abstract and title. More information can be found in this article.

Q5 What does the placement of the bubbles and the papers mean?

In general, the placement of bubbles can be interpreted as follows:

  • Closeness of bubbles implies subject similarity. The closer two bubbles, the closer they are subject-wise. The overlap of two bubbles implies strong subject similarity, but it does not mean that the two bubbles share common papers. Papers are always assigned to a single bubble only.
  • Centrality of bubbles implies subject similarity with the rest of the map, not importance. The closer a bubble is to the center, the closer it is subject-wise to all the other bubbles in the map.
Nevertheless, the placement of the bubbles should only be taken as an indication as the map is untangled in the beginning to improve readability. The placement of papers within a bubble has no specific meaning, as they are moved around significantly during the initial arrangement of the map to avoid overlap. More information can be found in this article.

Q6 Why does the overview visualization work better for some research topics than others?

The visualization 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 visualization. We have a number of routines in place to improve your chances of getting a useful map, but we do not always succeed. If you come across a map that needs improvement, we'd love to hear from you at

Q7 How should I cite Open Knowledge Maps?

  • To cite an individual map, please use the citation provided under each map.
  • To cite the open source software Head Start, please see the read-me on Github. It also includes relevant research papers.
  • 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.

Q8 Where can I find more information on the background of Open Knowledge Maps?

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

Q9 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 this page. If not, you can suggest it as a new source using this form.
To get included in PubMed, check if your journal is already included using information on this page. If not, you can suggest it as a new title for MEDLINE on this page.

Q10 How did Open Knowledge Maps come about?

Open Knowledge Maps was founded by Peter Kraker in 2015. Peter had worked on knowledge domain visualizations in his PhD and developed the first version of the open source visualization framework Headstart out of frustration with the existing discovery tools for scientific knowledge. In January 2016, Peter posted a Call for Collaborators on his blog, which brought a first team of volunteers together. Since 2016 Open Knowledge Maps is a registered non-profit organization.

Q11 Can I use Open Knowledge Maps to visualize my own collection(s)?

Absolutely! Open Knowledge Maps is based on the open source software Head Start, which is able to create knowledge maps from a wide variety of data, including text, metadata and references. If you have a collection that you would like to visualize with Open Knowledge Maps, check out our docs to get started. If you are interested in a collaboration project check out our present and past collaboration projects and learn more about how we can work together. Get in touch with your project proposal ideas at

Q12 How is Open Knowledge Maps funded?

We are a charitable non-profit organization run by a group of dedicated volunteers. Currently, we are looking for funding for our roadmap to realize the full potential of the idea. If you are interested in funding this effort, please contact us on

You can also help sustain Open Knowledge Maps by making a donation.

Q13 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. If you like the project, please spread the word as far as you can.

You can also help sustain Open Knowledge Maps by making a donation.

Q14 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 and a How-To for running an Open Knowledge Maps workshop.

Q15 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. We have also published the presentation including speaker notes and a short introduction in our training materials.

Q16 Are you available for collaborations and joint projects?

Absolutely! Check out our present and past collaboration projects and learn more about how we can work together.

You couldn't find an answer to your question? Get in touch and we will get back to you as soon as we can.

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