Below is some info about today’s launch of Dimensons, a new research discovery platform (including citation data) from Digital Science. This new resource provides both free and fee-based services and tools.
From Digital Science:
Global technology company Digital Science is proud to announce the launch of Dimensions, a new platform that aims to democratiseand transform scholarly search.
A collaboration between six Digital Science portfolio companies (Altmetric, Digital Science Consultancy, Figshare, Readcube, Symplectic and ÜberResearch) and more than 100 research funders and universities,
Dimensions [provides access to] over 860 million academic citations freely available, and delivers one-click access to over 9 million Open Access articles.
Within Dimensions, 124 million formerly siloed documents, including $1.2 trillion in funding, 86 million articles and books, and 34 million patents, are linked through 3.7 billion connections and contextualised with metrics and altmetrics. Built using real-world use cases, it combines advanced concept extraction, natural language processing, categorization and complex machine learning
Whereas previous tools and datasets have focused mostly on publications and citations, Dimensions takes a different approach: by integrating funded grants, publications and citations, altmetric data, clinical trials and patents, a complete picture of the research landscape emerges; from resources entering the system, research outputs, recognition, patents reflecting the commercial trajectory and the translation of medical research into treatments.
[Our emphasis] Research organizations have the option to license additional data types and analytical functionality to benefit from a more comprehensive view of the research landscape.
An extension of the one-click access to include publisher content licensed by the institution is also available.
A new Dimensions API also provide access to the underlying data in the easiest and most flexible way possible, using a domain-specific language designed with non-technical users in mind. The API can be used not just for data retrieval but also to aggregate data or return different facets in one single API call, enabling direct integrations and machine-to-machine implementations.
Questions and Answers
What Can Be Accessed Free? What Services are Fee-Based?
From a Digital Science/Dimension FAQ:
The free version of Dimensions is designed to provide researchers with a more efficient and effective way to discover the most relevant research. It includes full text search of articles, basic metrics for all of those publications, and will display the bibliographic data of any grants or other document types found in Dimensions that are associated with each article. Any open access articles that appear in search results offer one-click access to the full text. Searching across datasets will also be added to the free version during the course of 2018.
The paid parts of Dimensions include data and tools more specifically designed to meet the needs of certain users:Dimensions Plus
Designed for institutions, Plus includes access to all of the other available content types (grants, clinical trials, policy documents, patents and more).Institutions who subscribe to the Plus version will also have the opportunity to provide users with one-click access to any full text content they have licensed from publishers via a shibboleth integration, and all Plus customers will benefit from access to the Dimensions API, enabling the data to be integrating into any internal systems.Dimensions Analytics
Currently available and already used by over 200 funders, Dimensions Analytics offers all of Plus and additional advanced reporting and visualisation functionality that are best suited to publisher and funder use cases.
The original version of Dimensions was launched by Digital Science portfolio company UberResearch in 2014. Designed primarily to meet the needs of funders, it brought together funded grant information from over 250 global funders, and publications from PubMed.
Direct to A Guide to the Dimensions Data Approach