This blog post is from Lettie Conrad and Michelle Urberg, cross-posted from the The Scholarly Kitchen.
As sponsors of this project, we at Crossref are excited to see this work shared out.
The scholarly publishing community talks a LOT about metadata and the need for high-quality, interoperable, and machine-readable descriptors of the content we disseminate. However, as we’ve reflected on previously in the Kitchen, despite well-established information standards (e.g., persistent identifiers), our industry lacks a shared framework to measure the value and impact of the metadata we produce.
When Crossref began over 20 years ago, our members were primarily from the United States and Western Europe, but for several years our membership has been more global and diverse, growing to almost 18,000 organizations around the world, representing 148 countries.
As we continue to grow, finding ways to help organizations participate in Crossref is an important part of our mission and approach. Our goal of creating the Research Nexus—a rich and reusable open network of relationships connecting research organizations, people, things, and actions; a scholarly record that the global community can build on forever, for the benefit of society—can only be achieved by ensuring that participation in Crossref is accessible to all.
In August 2022, the United States Office of Science and Technology Policy (OSTP) issued a memo (PDF) on ensuring free, immediate, and equitable access to federally funded research (a.k.a. the “Nelson memo”). Crossref is particularly interested in and relevant for the areas of this guidance that cover metadata and persistent identifiers—and the infrastructure and services that make them useful.
Funding bodies worldwide are increasingly involved in research infrastructure for dissemination and discovery.
Preprints have become an important tool for rapidly communicating and iterating on research outputs. There is now a range of preprint servers, some subject-specific, some based on a particular geographical area, and others linked to publishers or individual journals in addition to generalist platforms. In 2016 the Crossref schema started to support preprints and since then the number of metadata records has grown to around 16,000 new preprint DOIs per month.
When someone links their data online, or mentions research on a social media site, we capture that event and make it available for anyone to use in their own way. We provide the unprocessed data—you decide how to use it.
Before the expansion of the Internet, most discussion about scholarly content stayed within scholarly content, with articles citing each other. With the growth of online platforms for discussion, publication and social media, we have seen discussions extend into new, non-traditional venues.
Crossref Event Data captures this activity and acts as a hub for the storage and distribution of this data. An event may be a citation in a dataset or patent, a mention in a news article, Wikipedia page or on a blog, or discussion and comment on social media.
How Event Data works
Event Data monitors a range of sources, chosen for their importance in scholarly discussion. We make events available via an API for users to access and interpret. Our aim is to provide context to published works and connect diverse parts of the dialogue around research. Learn more about the sources from which we capture events.
The Event Data API provides raw data about events alongside context: how and where each event was collected. Users can process this data to suit their requirements.
What is Event Data for?
Event Data can be used for a number of different purposes:
Authors can find out where their work has been reused and commented on.
Readers can access more context around published research, including links to supporting documents and commentary that aren’t in a journal article.
Publishers and funders can assess the impact of published research beyond citations.
Service providers can enrich, analyze, interpret and report via their own tools
Data intelligence and analysis organisations can access a broad range of sources with commentary relevant to research articles.
Anyone can contribute to Event Data by mentioning the DOI or URL of a Crossref-registered work in one of the monitored sources. We also welcome third parties who wish to send events or contribute to code that covers new sources. Learn more about contributing to or using Crossref Event Data.
Agreement and fees for Event Data
Event Data is a public API, giving access to raw data, and there are no fees. In the future we will introduce a service-based offering with additional features and benefits. Learn more about the Event Data terms.
What is an event?
In the broadest sense, an event is any time someone refers to a research article with a registered DOI anywhere online. Ideally we would capture all events, but there are limitations:
We can’t monitor the entire Internet, and instead check sites that are most likely to discuss academic content. There are still venues that could be relevant and that we do not cover yet.
Users online refer to academic content in different ways, sometimes using the DOI but more often using the URL or just the article name. We try to decode mentions of DOIs or a publisher website to get a match to an article but it isn’t always possible. This means we may miss mentions of an article even from sources we are tracking.
At present we are not able to track events where no link is included and only the title or other part of the metadata is mentioned.
For Crossref Event Data, an event consists of three parts:
A subject: where was the research mentioned? (such as Wikipedia)
An object: which research was mentioned? (a Crossref or DataCite DOI)
A relationship: how was the research mentioned? (such as cites or discusses)
We determine the relationship from the source of the event, it is an indication of how the subject and object are linked based on broad categories.
Software called agents collect events from various data sources. Most agents are written and operated by Crossref with some code written by our partners. Possible events are passed to the percolator software, which tries to match the event with an object DOI. This process is fully automated.
We perform periodic automated checks to the integrity of the data and update event types. Deduplication is also part of the process performed by the percolator.
To provide transparency, we keep an evidence record about how we matched the object to the subject. Learn more about transparency in Event Data, including links to the open source code and data.
The following agents currently collect data:
Relationships, references, and links to DataCite registered content
Links to Crossref registered content
Recommendations of research publications
Annotations in Hypothes.is
Discussed in blogs and media
Discussed on Reddit
Discussed on sites linked to in subreddits
Stack Exchange Network
Discussed on StackExchange sites
Mentions in tweets
References on Wikipedia pages
Discussed on Wordpress.com sites
We are planning to increase the number of agents and sources and welcome contact from anyone who can contribute. Patent Event Data was historically collected from The Lens.
What Event Data is not
By providing Event Data, Crossref provides an open, transparent information source for the scholarly community and beyond. It is important to understand, however, that it may not be suitable for all potential users. Here are some of the limitations:
It is not a service that provides metrics, collated reports, or offers data analysis.
Crossref does not build applications or website plugins for Event Data, for example for displaying results on publisher websites. We do, however, welcome third parties who wish to develop such platforms.
Event Data collection is fully automated and therefore may contain errors or be incomplete, we cannot provide any guarantees in this regard and users must assess the quality of the data required for their particular use case. There may also be delays between an event occurring and it appearing in Event Data.
Events might be missed due to the limitations of the collection algorithms we use. There is also a small possibility that we link an event to the wrong object.
Event Data does not cover every source of academic discussion. In some cases this is because there is no public access to the data; in others it is because we have not had the capacity to build an agent.
While we hope the data is useful for many purposes, we encourage users to be responsible and exercise caution when making use of Event Data.
Page owner: Martyn Rittman | Last updated 2020-October-06