Data Polygamy: The many-many relationships among urban spatio-temporal data sets

Fernando Chirigati, Harish Doraiswamy, Theodoros Damoulas, Juliana Freire

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The increasing ability to collect data from urban environments, coupled with a push towards openness by governments, has resulted in the availability of numerous spatio-temporal data sets covering diverse aspects of a city. Discovering relationships between these data sets can produce new insights by enabling domain experts to not only test but also generate hypotheses. However, discovering these relationships is difficult. First, a relationship between two data sets may occur only at certain locations and/or time periods. Second, the sheer number and size of the data sets, coupled with the diverse spatial and temporal scales at which the data is available, presents computational challenges on all fronts, from indexing and querying to analyzing them. Finally, it is nontrivial to differentiate between meaningful and spurious relationships. To address these challenges, we propose Data Polygamy, a scalable topology-based framework that allows users to query for statistically significant relationships between spatio-temporal data sets. We have performed an experimental evaluation using over 300 spatial-temporal urban data sets which shows that our approach is scalable and effective at identifying interesting relationships.

Original languageEnglish (US)
Title of host publicationSIGMOD 2016 - Proceedings of the 2016 International Conference on Management of Data
PublisherAssociation for Computing Machinery
Pages1011-1025
Number of pages15
ISBN (Electronic)9781450335317
DOIs
StatePublished - Jun 26 2016
Event2016 ACM SIGMOD International Conference on Management of Data, SIGMOD 2016 - San Francisco, United States
Duration: Jun 26 2016Jul 1 2016

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
Volume26-June-2016
ISSN (Print)0730-8078

Other

Other2016 ACM SIGMOD International Conference on Management of Data, SIGMOD 2016
CountryUnited States
CitySan Francisco
Period6/26/167/1/16

ASJC Scopus subject areas

  • Software
  • Information Systems

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    Chirigati, F., Doraiswamy, H., Damoulas, T., & Freire, J. (2016). Data Polygamy: The many-many relationships among urban spatio-temporal data sets. In SIGMOD 2016 - Proceedings of the 2016 International Conference on Management of Data (pp. 1011-1025). (Proceedings of the ACM SIGMOD International Conference on Management of Data; Vol. 26-June-2016). Association for Computing Machinery. https://doi.org/10.1145/2882903.2915245