Open Data for Environment Sensing: Crowdsourcing Geolocation Data


  • Ngoan Thanh Trieu Can Tho University
  • Zachary E. S. Williams University of the West Indies image/svg+xml
  • Jean-François M. Dorville Caribbean Geophysical and Numerical Research Group
  • Hiep Xuan Huynh Can Tho University
  • Vincent Rodin Université de Bretagne Occidentale
  • Bernard Pottier Université de Bretagne Occidentale



Open Data, Web Semantic, Environment Sensing, Geolocation Data, Environmental Simulation


There are numerous situations where the digital representation of the environment appears critical for understanding and decision-making: threats on soils, water, seashores, risk of fires, pollutions are evident applications. If spatial cellular decomposition is evidence in the more common applications, there remains a large field for environment and activities modelling. The integration and composition of several information sources is perhaps the main difficulty with the need to deal with data interpretation and semantics inside concurrent simulators. Besides, the data on population, people's behaviours, people's perceptions are essential in environmental assessments, where the technical aspect is not counted as much as the common acceptance of impact technology. We provide a model for building environmental services with open data systems. A case study is given for getting information from the public about their relationship with freshwater and its scarcity in Jamaica.




How to Cite

Thanh Trieu N, Williams ZES, Dorville J-FM, Xuan Huynh H, Rodin V, Pottier B. Open Data for Environment Sensing: Crowdsourcing Geolocation Data. EAI Endorsed Trans Context Aware Syst App [Internet]. 2020 May 12 [cited 2024 Apr. 25];7(20):e4. Available from: