TY - GEN
T1 - SURGE – Social Unrest Reconnaissance GazEteer (Demo Paper)
AU - Joshi, Deepti
AU - Soh, Leen Kiat
AU - Basnet, Sudeep
AU - Samal, Ashok
AU - Werum, Regina
AU - Arunachalam, Hariharan
AU - Ratcliff, Shawn
N1 - Publisher Copyright:
© 2017 Copyright is held by the owner/author(s).
PY - 2017/11/7
Y1 - 2017/11/7
N2 - Social Unrest Reconnaissance Gazetteer (or SURGE) is a Web-based application that provides an open system to visualize and integrate spatio-temporal data about social unrest events with related data layers in South Asia to facilitate data-driven as well as model-based investigations and analyses. Currently, the system displays eight categories of unrest, based primarily on the Global Database of Events, Language and Tone (GDELT) and the Global Terrorism Database (GTD). Users have the ability to select a single day or a range of dates along with the category of unrest they are interested to investigate. The users also have the option to normalize the raw event counts by population density. Additionally, the users can view infrastructure layers that facilitate or hinder the diffusion of unrest events (e.g., collated from an open GIS data-source: OpenStreetMap (www.openstreetmap.org)) and choropleth layers to display various socio-economic indicators (e.g., derived from global surveys and government census data such as the 2011 India census data (cenusindia.gov.in) and IPUMS Terra (data.terrapop.org)). Currently, SURGE displays unrest events for India, Pakistan and Bangladesh as heat map layers in multiple spatial resolutions. Challenges have involved geo-synchronization, data conversions, and displaying multiple layers of dense geospatial datasets. Future capabilities include automatic ingestion of raw data and standardizing levels of unrest using significant predictors.
AB - Social Unrest Reconnaissance Gazetteer (or SURGE) is a Web-based application that provides an open system to visualize and integrate spatio-temporal data about social unrest events with related data layers in South Asia to facilitate data-driven as well as model-based investigations and analyses. Currently, the system displays eight categories of unrest, based primarily on the Global Database of Events, Language and Tone (GDELT) and the Global Terrorism Database (GTD). Users have the ability to select a single day or a range of dates along with the category of unrest they are interested to investigate. The users also have the option to normalize the raw event counts by population density. Additionally, the users can view infrastructure layers that facilitate or hinder the diffusion of unrest events (e.g., collated from an open GIS data-source: OpenStreetMap (www.openstreetmap.org)) and choropleth layers to display various socio-economic indicators (e.g., derived from global surveys and government census data such as the 2011 India census data (cenusindia.gov.in) and IPUMS Terra (data.terrapop.org)). Currently, SURGE displays unrest events for India, Pakistan and Bangladesh as heat map layers in multiple spatial resolutions. Challenges have involved geo-synchronization, data conversions, and displaying multiple layers of dense geospatial datasets. Future capabilities include automatic ingestion of raw data and standardizing levels of unrest using significant predictors.
KW - Geographic Information System
KW - Social Unrest
KW - South-East Asia
KW - Spatio-Temporal Data Analytics
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U2 - 10.1145/3139958.3140052
DO - 10.1145/3139958.3140052
M3 - Conference contribution
AN - SCOPUS:85040966016
SN - 9781450354905
T3 - GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems
BT - GIS
A2 - Ravada, Siva
A2 - Hoel, Erik
A2 - Tamassia, Roberto
A2 - Newsam, Shawn
A2 - Trajcevski, Goce
A2 - Trajcevski, Goce
PB - Association for Computing Machinery
T2 - 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2017
Y2 - 7 November 2017 through 10 November 2017
ER -