#  GIS Data Science/ Geospatial Big Data at CGA 

 



Big geospatial data includes datasets that are too large to be processed using traditional GIS tools. The objective of GIS Data Science/ Geospatial Big Data workstream at CGA is to:

- Apply Data Science, Machine Learning, AI techniques for complex geospatial analysis
- Design solutions for geospatial big data problems which cannot be handled by traditional GIS technologies
- Scale geospatial applications on cluster ([FASRC](https://www.rc.fas.harvard.edu/)) and cloud ([AWS](https://aws.amazon.com/)/[MOC](https://massopen.cloud/)) computing environments
- Use geospatial databases ([PostGIS](https://postgis.net/), [OmniSci](https://www.omnisci.com/)) to perform large scale complex analysis on big data
- Visualize large geospatial data at high speed using GPU based databases and other tools

More information on this workstream can be found in our detailed presentation [here](https://docs.google.com/presentation/d/1r2JdIu9JA-ZJ4QeQApdAbSci-YBNA8OQyNYg5mydP34/edit?usp=sharing).

CGA's key resources in this area:

- [Self- Service Tools](/geospatial-data-science-tools-and-data-harvards-high-performance-computing-infrastructure)
- [Tutorials](/self-led-tutorials)
- [Workshops](/workshops-0)
- [DataSets](/geotweet-archive-v20)
    - [CGA's Geotweet Archive](/geotweet-archive-v20)
    - [Twitter Seniment Geographic Index (TSGI)](/twitter-sentiment-geographical-index-tsgi-dataset-global-high-frequency-dataset-monitoring?admin_panel=1)
- [Github](https://github.com/cga-harvard/Data_Science_Big_Data_Projects)
- Key projects:
    - [Geospatial Infrastructure Enhancement](https://nerc.mghpcc.org/project/geospatial-infrastructure-enhancement/)
    - [Partisan Segregation Analysis](/nationwide-individual-partisan-clustering-analysis)
    - [Climate Data Analysis](/high-performance-computing-address-level-climate-data-extraction)
    - [Use of Social Media Data to study Climate Change](/use-social-media-data-study-climate-change)
    - [Weibo Mobility Index](https://projects.iq.harvard.edu/chinadatalab/event/introduction-weibo-mobility-index-data)
    - [Detroit Zoning Analysis](/detroit-ticket-polygonsparcel-zoning-analysis)
    - [Network Analysis of Geospatial Big Data for Brazil](/calculating-shortest-drive-distance-geospatial-big-data)
    - [Infogroup US Historical Business DataSet Analysis](/infogroup-us-historical-business-dataset-analysis)
    - [Billion Object Platform v1.0](/billion-object-platform-bop)
    - [Billion Object Platform v2.0 ](https://sc22.mghpcc.org/project/billion-object-platform/)
    - [Evaluating OmniSci](/mapd-explore-power-gpus-spatiotemporal-analytics)
    - [Travel Time Estimation on Big Data](https://isprs-archives.copernicus.org/articles/XLVIII-4-W7-2023/53/2023/)
    - [Building a robust infrastructure for Geospatial Big Data Analytics](/event/building-robust-infrastructure-geospatial-big-data-analytics)

Questions about GIS Data Science/Big Data? [Contact us](/contactus) or email [Devika Kakkar.](/people/devika-kakkar)

 ![big data](/sites/g/files/omnuum9996/files/gis/files/thumbnail_map_tweets_language.png)

 



 



 

 See also:- [ Services ](/page-type/services)