CUGIR

About

CUGIR, the Cornell University Geospatial Information Repository, provides free and open access to geospatial data for New York State, as well as worldwide geospatial data created by researchers at Cornell. Our collections have traditionally focused on data relevant to agriculture, ecology, natural resources, and human-onvironment interactions. Subjects such as landforms and topography, soils, hydrology, environmental hazards, agricultural activities, wildlife and natural resource management are appropriate for inclusion in the CUGIR catalog. All data files are cataloged in accordance with FGDC standards and made available in widely used geospatial data formats.

PLEASE NOTE:The CUGIR website was first launched in the 1990s, back during a time when the Internet was young, computers had less memory, and download speeds were much slower. Consequently, many geospatial datasets were distributed as multiple quad- or county-based downloads. This required multiple downloads in order to access data for larger areas. When converting and migrating these datasets to the new CUGIR infrastructure, we decided that on the modern Internet, a merged statewide file of 8MB is no longer a "large" file. So in many cases, such as US Census data, we took 62 county- based files and merged them into a single statewide layer.

History

In 1996, staff at Cornell University’s Mann Library began work on a web-based system to distribute subsets of New York data from U.S. Census TIGER/Line files, and in 1998 became an official node of the National Spatial Data Infrastructure (NSDI) Federal Geospatial Clearinghouse. In 2006, the CUGIR website user interface was updated to improve the discovery and access to datasets.

After two decades in service, the aging CUGIR infrastructure has been retired and completely rebuilt using several open source components: PostGIS, GeoServer, Solr, and GeoBlacklight. Launched in 2017, the new CUGIR provides a powerful discovery interface that allows users to combine keyword- and map-based search. Search results can be filtered by facets such as topic category, year, author, collection, or data type. Individual datasets can be previewed on the website, allowing even non-GIS users to explore the data overlaid on a map and retrieve information for specific features. In addition to improved download packages, users of desktop GIS applications can also use WMS and WFS services to connect to CUGIR data without even downloading a zipfile.

Team

CUGIR has been supported over the years by many staff at Mann Library. Current team members include:

  • Darcy Branchini, Senior UX Designer
  • Keith Jenkins, GIS & Geospatial Applications Librarian
  • Huda Khan, Applications Programmer/Research Associate
  • Kevin Kidwell, UX Designer
  • Alan McCarty III, DevOps Engineer
  • Jeff Piestrak, Digital Collections Specialist

CUGIR Alumni:

  • Kathy Chiang
  • Michael Cook
  • Jon Corson-Rikert
  • Tom Gale
  • Philip Herold
  • Nan Hyland
  • Bill Kehoe
  • Lee LaFleur
  • Jesse Lessinger
  • Jaime Martindale
  • Tom Ottaviano
  • Gail Steinhart
  • Tom Turner
  • Bill Walter
  • Elaine Westbrooks