Challenges in supporting extraction of knowledge about environmental objects and events from geosensor data

Peer-reviewed
Conference Proceedings
Technologies for capturing large amounts of real-time and high-detail data about the environment have advanced rapidly; our ability to use this data for understanding the monitored settings for decision-making has not. …
Author

Bleisch, S., Duckham, M., Kealy, A., Richter, K. F., Winter, S., Kininmonth, S., Klippel, A., Laube, P., Lyon, J., Medyckyj-Scott, D., and Wark, T.

Published

2012

[pdf]

Abstract

Technologies for capturing large amounts of real-time and high-detail data about the environment have advanced rapidly; our ability to use this data for understanding the monitored settings for decision-making has not. Visual analytics, creating suitable tools and interfaces that combine computational powers with the human’s capabilities for visual sense making, is a promising approach. Geosensor networks monitor a range of different complex environmental settings, collecting heterogeneous data at different spatial and temporal scales. Similarly domain experts with specific preferences and requirements use the collected data. Additionally, long-term monitoring networks may aim to increase sensor node longevity by minimizing storage and communication load. Based on these aspects, four key challenges for the extraction of knowledge about environmental objects and events from geosensor data are identified: dynamics and uncertainty of the continuous stream of recorded data; different scales in data collection but also data analysis at a range of aggregation levels; decentralized data processing and storage; and evaluation of the effectiveness, efficiency and completeness of implemented decentralized visual analytics approaches.

Figures

Sensor network nodes iButton (left) and iMotes (middle); part of the deployment map of site 2 showing approximate node locations (right)

left) Resnagging Murray River, Australia; right) Snag mass density in different river sections after resnagging

Logger tower schematic of the resnagging programm in Murray River; colored zones f, h, d and c mark priority resnagging sites (Lyon et al. 2010)

Part of a Google Maps® live traffic map: color-coded is the vehicle density (alternatively, depending on the environmental sensors, the average vehicle speed) along street segments.

BibTeX

@article{bleisch_challengesExtractingInfoFromGeosensorData_2012,
 abstract = {Technologies for capturing large amounts of real-time and high-detail data about the environment have advanced rapidly; our ability to use this data for understanding the monitored settings for decision-making has not. Visual analytics, creating suitable tools and interfaces that combine computational powers with the human’s capabilities for visual sense making, is a promising approach. Geosensor networks monitor a range of different complex environmental settings, collecting heterogeneous data at different spatial and temporal scales. Similarly domain experts with specific preferences and requirements use the collected data. Additionally, long-term monitoring networks may aim to increase sensor node longevity by minimizing storage and communication load. Based on these aspects, four key challenges for the extraction of knowledge about environmental objects and events from geosensor data are identified: dynamics and uncertainty of the continuous stream of recorded data; different scales in data collection but also data analysis at a range of aggregation levels; decentralized data processing and storage; and evaluation of the effectiveness, efficiency and completeness of implemented decentralized visual analytics approaches.},
 author = {Bleisch, Susanne and Duckham, Matt and Kealy, Allison and Richter, Kai-Florian and Winter, Stephan and Kininmonth, Stuart and Klippel, Alexander and Laube, Patrick and Lyon, Jarod and Medyckyj-Scott, David and Wark, Tim},
 file = {PDF:files/9562/Bleisch et al. - Challenges in supporting extraction of knowledge about environmental objects and events from geosens.pdf:application/pdf;PDF:files/9564/Bleisch et al. - 2012 - Challenges in supporting extraction of knowledge about environmental objects and events from geosens.pdf:application/pdf},
 language = {en},
 title = {Challenges in supporting extraction of knowledge about environmental objects and events from geosensor data},
 year = {2012}
}