CADRE is the Collaborative Archive & Data Research Environment
CADRE is a cloud-based text and data mining service for large datasets. Over 220 million scientific publications and 1.7 billion citations can be queried and analyzed. No programming experience is required, but programming tools are available for more advanced analyses and extractions.
The University of Toronto Libraries has purchased a membership to the CADRE platform starting in January 2021 but users can use the system immediately.
Web of Science XML Data
A key data source on the CADRE system is the Web of Science XML data (Wos). WoS XML data includes over 12,500 journals from around the world in over 250 Science, Social Science and Humanities disciplines. Conference proceedings and book data are also included. Data are available from 1900 and currently include over 63 million article records and 1 billion cited references.
Microsoft Academic Graph
Microsoft Academic Graph (MAG) is also available for use and linking to WoS results. MAG contains scientific publication records and citation relationships between publications, authors, institutions, etc.
Research on CADRE can be conducted using drop-down menus and search boxes, but Jupyter and other Notebooks are also available from within the system to allow for querying using R, Python and other programming languages.
Further resources are available for getting started with CADRE and understanding its potential through examples.
Videos - https://cadre.iu.edu/resources
- Documentation - https://cadre.iu.edu/resources/documentation
All UofT Students, Faculty and Staff are eligible for an account on CADRE. To get started, fill in the following trial user form.
Once your form has been completed and you have received confirmation from the CADRE system, sign into CADRE through the following CADRE Gateway Page.
Feedback and Further Information
The University of Toronto Libraries would appreciate feedback from users on their experiences in using CADRE. Please email email@example.com for further information and to provide feedback on this trial subscription.