Data Collections These fields are in addition to Dublin Core fields to describe MDL's data collections, including microdata, statistical data, and GIS data. Links <a href="https://mdlutoronto.github.io/postgresql-databases-access/">Access Instructions</a> Terms of Use The Web of Science Raw Data (XML) and this PostgreSQL database are intended for academic study, research, teaching and administrative use at the University of Toronto. The data is restricted to University of Toronto faculty, students, researchers and staff. It is strictly forbidden to use this dataset or derivatives for commercial or Non-University of Toronto specific use. Further distribution of this data or derivatives, is prohibited. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Web of Science (WoS) Description An account of the resource The <a href="https://mdl.library.utoronto.ca/technology/text-data-mining-software/web-science-raw-data-xml">Web of Science (WoS) Raw Data Product</a> includes metadata from 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 (as of 2018). The raw XML is available. It has also been converted into an object-relational database (updated periodically) and is available to UofT faculty, staff, and students for querying in a high performance computing environment offered by <a href="https://www.scinethpc.ca/">SciNet</a>. Currently the database contains data up to and including Dec. 31, 2025. This is an excellent dataset for use in text and data mining research, particularly focusing on bibliometrics and citation analysis. It can be programmatically queried via SQL statements directly or through python scripts, with no limits on query results. <h3>Working with the Database</h3> You query the database using SQL statements, and then can either continue to work with the results within this computing environment, or download the results as a CSV file. For help with constructing your SQL queries: <ul> <li><a href="https://maps.library.utoronto.ca/docs/postgresql/WoS/db-structure.pdf">This document</a> describes the various tables and their contents.</li> <li>This <a href="http://maps.library.utoronto.ca/docs/postgresql/WoS/WoS_ERD.pdf">Entity Relationship Diagram (ERD)</a> provides a visual representation of all of the tables within the database and their relationships, including bridging tables. </li> </ul> <h3>Access</h3> In order to access the database, you must first gain access to the high performance computing environment through a <a href="https://mdlutoronto.github.io/postgresql-databases-access/">multi-step process</a> to create the appropriate account (may take a few days to create the account initially). <a href="https://mdlutoronto.github.io/wos-postgresql-database-mac-getting-started/">Tutorial for Mac Users</a> <a href="https://mdlutoronto.github.io/wos-postgresql-database-getting-started/">Tutorial for Windows Users</a>