Dimensions is a new scholarly search database that focuses on the broader set of use cases that academics now face. By including awarded grants, patents, and clinical trials alongside publication and Altmetric attention data, Dimensions goes beyond the standard publication-citation ecosystem to give the user a much greater sense of context of a piece of research. All entities in the graph may be linked to all other entities. Thus, a patent may be linked to a grant, if an appropriate reference is made. Books, book chapters, and conference proceedings are included in the publication index. All entities are treated as first-class objects and are mapped to a database of research institutions and a standard set of research classifications via machine-learning techniques. This article gives an overview of the methodology of construction of the Dimensions dataset and user interface.

Until recently, comprehensive scientometrics data has been made available only in siloed, subscription-based tools that are inaccessible to researchers who lack institutional support and resources. As a result of limited data access, research evaluation practices have focused upon basic indicators that only take publications and their citation rates into account. This has blocked innovation on many fronts. Dimensions is a database that links and contextualizes different research information objects. It brings together data describing and linking awarded grants, clinical trials, patents, and policy documents, as well as altmetric information, alongside traditional publications and citations data. This article describes the approach that Digital Science is taking to support the scientometric community, together with the various Dimensions tools available to researchers who wish to use Dimensions data in their research at no cost.