
Semantic Scholar Releases New Recommendations API
Introducing a new public service that can recommend recently published papers or preprints to researchers based on a learned model of their topical interests.
Providing a reliable source of scholarly data for developers
Build projects that accelerate scientific progress with the Semantic Scholar Academic Graph API
The Semantic Scholar API is a way of representing the world’s scientific publications.
Scientific papers and their authors are connected by citations of one paper by another. Our API allows you to find and explore these relations, including data about authors, papers, citations, venues, and more.
Currently, Semantic Scholar API supports Paper and Author Lookup, Conflict of Interest detection, Conference Reviewer Match, SPECTER embeddings, and SUPP.AI annotations. We are actively developing new features based on user demand.
To learn more about our API service, read The Semantic Scholar Open Data Platform paper.
Semantic Scholar providing infrastructure for the research ecosystem is exciting as it enables partners like Litmaps to focus on creating great experiences for end users. We found the Semantic Scholar API and bulk data, clear and straightforward to use. The documentation, examples, and easy access to the raw data allowed us to move quickly on data integration, and get back to solving problems for our users.
Axton PittCo-founder and CTO, Litmaps
Eddie SmolyanskyCo-founder, Connected Papers
Since day 1 Connected Papers has been built on top of the Semantic Scholar Open Corpus and APIs, and heavily relies on them to provide paper discovery and search capabilities to our users. The APIs are well maintained, frequently updated, fast, and easy to use. The team is extremely responsive and has supported our growth every step of the way from open beta to a million users. This massive resource given to the public for free is a great driver for innovation in science and we are proud to be a part of the next layer of tools being built on top of it.
We are a startup that tracks the evolution and progress of AI research. Thanks to the Semantic Scholar API pulling in the latest references to papers from top AI conferences has been a really simple task. Otherwise, it would have taken much more time and effort.
Eduardo Antonio Espinosa GrimaldoFounder, Stateoftheart AI
Elman MansimovCo-Owner, Sourcely
We at Sourcely have migrated to the Semantic Scholar API to provide academic references to students writing their essays, and or experience working with academic references APIs has never been better. Not only is the Semantic Scholar API very easy to use, quick, and reliable, but it also incorporates a lot of additional metadata like PDF URLs, abstract, summarization, and more, that are not easily accessible with other academic reference providers like Google Scholar. Students love the references provided by Semantic Scholar API and their experience on Sourcely has improved since migration. On top of that, the Semantic Scholar team has been very helpful in answering our questions and considering our feedback.
You can use the API endpoint to test your application idea now! All unauthenticated users share a limit of 5,000 requests per 5 minutes. To access a higher rate limit, request authentication for your project. Authenticated partners with API keys have access to higher rate limits, personalized support, and co-marketing opportunities.
We provide the RESTful Semantic Scholar Academic Graph (S2AG) API as a service to the global research community. The API is a reliable on-demand source of data about authors, papers, citations, venues, and more that allows you to link directly to the corresponding page on semanticscholar.org for more information.
Documentation for paper and author lookup are available from our Academic Graph service, whose reference documentation is available here. Documentation for our Conference Peer Review service is available here. You can also download detailed information in JSON format about all the research papers in our corpus as described here.
We also provide the following datasets as free and open resources.