The University of Texas Libraries collects and preserves the finest achievements of human knowledge in support
of not only research and instruction needs, but also the exploration of ideas and intellectual innovation. We
are proud to provide access to geospatial data from our collections as well as the shared collections of other
universities for researchers, scholars, educators, and the general public through this portal.
You will find a wide variety of data types available for download including georeferenced scanned maps from the Perry-Castañeda Library Map Collection, vector datasets developed from collections in the Alexander Architectural Archives, geospatial data from the Benson Latin American Collection, and more. These datasets represent just some of the geospatial resources found in the UT Libraries’ collections. Additional datasets will continue to be added to this portal as they are processed.
The Texas GeoData portal has been developed with a mix of open source solutions and commercial off-the-shelf
technology, including GeoBlacklight 2.0.0 for the front
end framework, ArcGIS Server, PostgreSQL, and Apache Solr.
We provide access to the vector and raster datasets made available through this portal in a range of downloadable
formats and via web services to facilitate the use of the data in both GIS software and interactive web maps. All
University of Texas datasets that are available for download through this portal are georeferenced and use the
WGS 84 (EPSG: 4326) coordinate reference system by default to facilitate use in GIS software.
This portal has been configured to allow users to browse not only geospatial resources in the UT Libraries’ collections, but also raster and vector datasets shared by other universities that are utilizing GeoBlacklight and have shared the metadata for their resources through the OpenGeoMetadata collaboration. Since it is possible to find data from a variety of institutions through this portal you may notice some variations in the services and metadata that are available for particular datasets.