The current explosion in spatial data raises the need for efficient spatial analysis tools to extract useful information from such data. However, existing tools are neither generic nor scalable when dealing with big spatial data. This demo presents Flash; a framework for generic and scalable spatial data analysis, with a special focus on spatial probabilistic graphical modelling (SPGM). Flash exploits Markov Logic Networks (MLN) to express SPGM as a set of declarative logical rules. In addition, it provides spatial variations of the scalable RDBMS-based learning and inference techniques of MLN to efficiently perform SPGM predictions. To show Flash effectiveness, we demonstrate three applications that use Flash in their SPGM: (1) Bird monitoring, (2) Safety analysis, and (3) Land use change tracking.
|Original language||English (US)|
|Number of pages||4|
|Journal||Proceedings of the VLDB Endowment|
|State||Published - 2018|
|Event||45th International Conference on Very Large Data Bases, VLDB 2019 - Los Angeles, United States|
Duration: Aug 26 2017 → Aug 30 2017
Bibliographical notePublisher Copyright:
© 2019 VLDB Endowment.