Open Knowledge Maps

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Open Knowledge Maps is a Research & Education tool that provides a visual overview of research topics. It helps users find relevant research outputs and identify important concepts through AI-based mapping.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is Open Knowledge Maps?

Open Knowledge Maps is the world's largest AI-based search engine for scientific knowledge, designed to transform research discovery. It offers a visual overview of research topics, helping users find relevant research outputs and identify key concepts. The platform is a charitable non-profit organization committed to open science principles, aiming to create an inclusive and sustainable infrastructure. It uses AI to analyze article metadata from trusted providers like PubMed and BASE, clustering resources and generating area titles to provide a comprehensive and interactive map of scientific literature. Users can explore topics, identify themes, and focus on pertinent papers, making it an invaluable tool for researchers and academics.

Best used for

Ideal for researchers, academics, and students who need to get an overview of a research topic, find relevant resources, and identify important concepts. Especially valuable for quickly understanding the landscape of scientific knowledge and discovering connections between different areas of study.

Common actions

visualize research topics

find scientific literature

identify research concepts

explore academic papers

Capabilities

Key features

AI-based research mapping
Visual topic overviews
Resource clustering
Concept identification
Custom integrations
Open source software

Target Audience

professorresearcherstudent

Integrations

Not yet documented

Pricing & Plans

Open Source

Not publicly disclosed. Check toolify.ai for current pricing.

FAQs

How does Open Knowledge Maps determine the 'most relevant' resources?

The tool uses relevance rankings provided by either the PubMed API or the BASE API, depending on the user's choice. These APIs primarily use text similarity between the search query and article metadata to determine relevance, ensuring that the most pertinent results are displayed.

Why does it take up to 30 seconds to create a knowledge map?

The process involves two main steps: sending the query to a data provider (PubMed or BASE) to retrieve results, which takes about 15 seconds, and then the AI pipeline analyzing this data to create the map, taking another 15 seconds. The team is working to reduce loading times.

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

The grouping of resources and map generation are based on article metadata, including titles, abstracts, authors, journals, and subject keywords. A word co-occurrence matrix is created, followed by clustering and ordination algorithms to visualize the relationships between articles.

How is Open Knowledge Maps funded as a non-profit organization?

Open Knowledge Maps is funded through a collective effort, inviting organizations to become supporting members and co-create the platform. They also seek third-party funding for their roadmap and accept individual donations to sustain their operations and development.

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Subcategories trending in Research & Education

Study Assistants Knowledge Management Course Creation Scientific Computing Summarization Language Learning

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