Skip to main content
U.S. flag

An official website of the United States government

Tools for discovering and accessing Great Lakes scientific data

May 21, 2015

The Great Lakes Restoration Initiative (GLRI) is a multidisciplinary and interagency effort focused on the protection and restoration of the Great Lakes (GL) using the best available science and applying lessons learned from previous studies. The U.S. Geological Survey (USGS) contributes to the GLRI effort by providing resource managers with information and tools needed to meet restoration goals. This includes contributing scientific expertise and delivering findings to the GL community through meaningful information products.

One of the strengths of the GLRI is its interagency approach; however, this can create challenges when coordinating the large number of restoration activities being performed by GL governments, tribes, academics, nonprofits, and industry. There is a vast array of data being produced by both the USGS and its partners, and it is crucial that scientists, managers, policymakers, and the public can easily locate the biological, geological, geospatial, and water-resources data being generated.

The USGS strives to develop data products that are easy to find, easy to understand, and easy to use through Web-accessible tools that allow users to learn about the breadth and scope of GLRI activities being undertaken by the USGS and its partners. By creating tools that enable data to be shared and reused more easily, the USGS can encourage collaboration and assist the GL community in finding, interpreting, and understanding the information created during GLRI science activities.

Publication Year 2015
Title Tools for discovering and accessing Great Lakes scientific data
DOI 10.3133/fs20153040
Authors Jessica M. Lucido, Jennifer L. Bruce
Publication Type Report
Publication Subtype USGS Numbered Series
Series Title Fact Sheet
Series Number 2015-3040
Index ID fs20153040
Record Source USGS Publications Warehouse
USGS Organization Center for Integrated Data Analytics; Wisconsin Water Science Center