Altmetrics for all

Cobaltmetrics monitors trusted sources to index citations, identifiers, and hyperlinks, helping you report on all types of content.

We track references to millions of documents and digital objects, including scientific publications, books, journals, patents, trademarks, clinical trials, financial statements, security vulnerabilities, tweets, videos, and raw URLs and URNs.

See our summary statistics to learn more about the data that Cobaltmetrics tracks.

Learn more about Cobaltmetrics

What does Cobaltmetrics do?

Cobaltmetrics helps you discover citations and backlinks to all types of documents and digital objects. We monitor trusted sources, in all domains and languages, to index and normalize citations, identifiers, and hyperlinks.

From academics to corporate R&D, reviewers to publishers, administrators to funders, different users of altmetrics data have different requirements, workflows, and tools. We are committed to delivering not only impact metrics that summarize all the attention around a digital object into a single number, but also raw data that can be integrated into existing dashboards and reporting systems.

This website is an early release of Cobaltmetrics, and some features are not yet public. We value feedback from the community, and we wanted to showcase the project at PIDapalooza 2018. More data and features will be released soon, including but not limited to support for shortened URLs, notifications, RSS feeds, RESTful APIs, and data dumps.

Design rationale

Our motto for Cobaltmetrics is altmetrics for all, and this implies more than merely extending the scope of altmetrics to documents other than scientific publications. Less than 1% of the world population speak English as their first language, but many altmetrics and scientometrics projects only track content in English. There are only two possible hypotheses behind projects focusing on English: all conversations around digital content happen in English, or English data is a perfectly balanced sample. Both are wrong. Cobaltmetrics extracts citations and backlinks from all sources, no matter the language.

Cobaltmetrics can only be queried by identifiers. Our team has a strong background in natural language processing and hands-on experience with bibliometrics. We know how ambiguous natural language can be, especially names. We decided early on to focus on speed and relevance, so searching by names will most likely never be supported. And if you are one of the 47,000 people in the US named John Smith, please register for an ORCID identifier.

How does it work?

All identifiers in Cobaltmetrics are stored as URIs, so every search term will consist of a scheme, a colon, and a value. For example, to search for RFC 3986, enter rfc:3986. Because all URLs are URIs, you can also enter full URLs into the search bar, and we'll do our best to extract identifiers from them, for example instead of rfc:3986. The summary statistics table lists all schemes (i.e. identifier types) that are currently supported.

Our search engine will automatically normalize identifiers depending on their type, for example if they are not sensitive to case like DOIs, or if their canonical form includes hyphens like ISSNs or ORCID iDs. Likewise, our search engine will reject syntactically incorrect identifiers.

The are two buttons next to the search bar, one with a magnifying glass and the other with a magic wand. Clicking on the magnifying glass will search for the identifiers you entered. Clicking on the magic wand will search for the identifiers you entered and, through a process known as query expansion, all other identifiers known to identify the same document or digital object. For example, we know from PubMed that pmid:23193287, pmcid:3531190, and doi:10.1093/NAR/GKS1195 refer to the same article. Query expansion allows you to find all citations and backlinks to a document with multiple identifiers, with a single query.

Coming Soon





Email us at [email protected] to inquire about upcoming features and data dumps, or just to say hello!