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Explora : interactive querying of multidimensional data in the context of smart cities

Leandro Ordonez Ante (UGent) , Gregory Van Seghbroeck (UGent) , Tim Wauters (UGent) , Bruno Volckaert (UGent) and Filip De Turck (UGent)
(2020) SENSORS. 20(9).
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Abstract
Citizen engagement is one of the key factors for smart city initiatives to remain sustainable over time. This in turn entails providing citizens and other relevant stakeholders with the latest data and tools that enable them to derive insights that add value to their day-to-day life. The massive volume of data being constantly produced in these smart city environments makes satisfying this requirement particularly challenging. This paper introduces Explora, a generic framework for serving interactive low-latency requests, typical of visual exploratory applications on spatiotemporal data, which leverages the stream processing for deriving-on ingestion time-synopsis data structures that concisely capture the spatial and temporal trends and dynamics of the sensed variables and serve as compacted data sets to provide fast (approximate) answers to visual queries on smart city data. The experimental evaluation conducted on proof-of-concept implementations of Explora, based on traditional database and distributed data processing setups, accounts for a decrease of up to 2 orders of magnitude in query latency compared to queries running on the base raw data at the expense of less than 10% query accuracy and 30% data footprint. The implementation of the framework on real smart city data along with the obtained experimental results prove the feasibility of the proposed approach.
Keywords
ANOMALY DETECTION, FRAMEWORK, CITY, interactive querying, spatiotemporal data, smart city data, sensor data, synopsis data structures, continuous views, microservices

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Please use this url to cite or link to this publication:

MLA
Ordonez Ante, Leandro, et al. “Explora : Interactive Querying of Multidimensional Data in the Context of Smart Cities.” SENSORS, vol. 20, no. 9, 2020, doi:10.3390/s20092737.
APA
Ordonez Ante, L., Van Seghbroeck, G., Wauters, T., Volckaert, B., & De Turck, F. (2020). Explora : interactive querying of multidimensional data in the context of smart cities. SENSORS, 20(9). https://doi.org/10.3390/s20092737
Chicago author-date
Ordonez Ante, Leandro, Gregory Van Seghbroeck, Tim Wauters, Bruno Volckaert, and Filip De Turck. 2020. “Explora : Interactive Querying of Multidimensional Data in the Context of Smart Cities.” SENSORS 20 (9). https://doi.org/10.3390/s20092737.
Chicago author-date (all authors)
Ordonez Ante, Leandro, Gregory Van Seghbroeck, Tim Wauters, Bruno Volckaert, and Filip De Turck. 2020. “Explora : Interactive Querying of Multidimensional Data in the Context of Smart Cities.” SENSORS 20 (9). doi:10.3390/s20092737.
Vancouver
1.
Ordonez Ante L, Van Seghbroeck G, Wauters T, Volckaert B, De Turck F. Explora : interactive querying of multidimensional data in the context of smart cities. SENSORS. 2020;20(9).
IEEE
[1]
L. Ordonez Ante, G. Van Seghbroeck, T. Wauters, B. Volckaert, and F. De Turck, “Explora : interactive querying of multidimensional data in the context of smart cities,” SENSORS, vol. 20, no. 9, 2020.
@article{8665508,
  abstract     = {Citizen engagement is one of the key factors for smart city initiatives to remain sustainable over time. This in turn entails providing citizens and other relevant stakeholders with the latest data and tools that enable them to derive insights that add value to their day-to-day life. The massive volume of data being constantly produced in these smart city environments makes satisfying this requirement particularly challenging. This paper introduces Explora, a generic framework for serving interactive low-latency requests, typical of visual exploratory applications on spatiotemporal data, which leverages the stream processing for deriving-on ingestion time-synopsis data structures that concisely capture the spatial and temporal trends and dynamics of the sensed variables and serve as compacted data sets to provide fast (approximate) answers to visual queries on smart city data. The experimental evaluation conducted on proof-of-concept implementations of Explora, based on traditional database and distributed data processing setups, accounts for a decrease of up to 2 orders of magnitude in query latency compared to queries running on the base raw data at the expense of less than 10% query accuracy and 30% data footprint. The implementation of the framework on real smart city data along with the obtained experimental results prove the feasibility of the proposed approach.},
  author       = {Ordonez Ante, Leandro and Van Seghbroeck, Gregory and Wauters, Tim and Volckaert, Bruno and De Turck, Filip},
  issn         = {1424-8220},
  journal      = {SENSORS},
  keywords     = {ANOMALY DETECTION,FRAMEWORK,CITY,interactive querying,spatiotemporal data,smart city data,sensor data,synopsis data structures,continuous views,microservices},
  language     = {eng},
  number       = {9},
  pages        = {33},
  title        = {Explora : interactive querying of multidimensional data in the context of smart cities},
  url          = {http://dx.doi.org/10.3390/s20092737},
  volume       = {20},
  year         = {2020},
}

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