Parallel Processing over Spatial-Temporal Datasets from Geo, Bio, Climate and Social Science Communities: A Research Roadmap

• Published in: 2017 IEEE International Congress on Big Data (BigData Congress) pp. 232 - 250
• Main Authors: Prasad, Sushil K., Aghajarian, Danial, McDermott, Michael, Shah, Dhara, Mokbel, Mohamed, Puri, Satish, Rey, Sergio J., Shekhar, Shashi, Yiqun Xe, Vatsavai, Ranga Raju, Fusheng Wang, Yanhui Liang, Hoang Vo, Shaowen Wang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2017
• Subjects: Biological system modeling; CyberGIS; Data mining; Diseases; High performance computing; Map-reduce systems; Medical images; Meteorology; Parallel algorithms and data structures; Remote sensing; Remote sensing data; Sensors; Spatial data mining; Spatial databases; Spatial econometrics

This vision paper reviews the current state-ofart and lays out emerging research challenges in parallel processing of spatial-temporal large datasets relevant to a variety of scientific communities. The spatio-temporal data, whether captured through remote sensors (global earth observations), ground...