Creation, Analysis, Sharing, and Visualization of Complex Spatiotemporal Data Using Free and Open Source Software at the National Renewable Energy Laboratory (NREL)
Dan Getman
Monday, April 6th, 5:00-6:00p.m. MDT
FAST Lab North Classroom 5033, University of Colorado — Denver
Join remotely: https://ucdenver.zoom.us/my/foss4g
Geospatial data science at the National Renewable Energy Laboratory incorporates a wide range of activities including the creation of large spatiotemporal resource datasets, modeling the technical potential of renewable energy at the national level, web based visualization of complex scenario based modeling, and sharing of both datasets and analysis methods with industry, academia, and the public through web services. In this presentation, we describe an integrated system in which all of the steps from data acquisition through analysis and collaborative research to sharing results with the public are accomplished using free and open source software and frameworks. Technologies used include R, Python, GDAL, OGR, Geoserver, Postgres, PostGIS, Mongo, Q GIS, NodeJS, Leaflet, OpenLayers, Ruby on Rails, CKAN, D3, and several other analysis and web based visualization libraries.