Paper Info
Title
Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets.
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 non-trivial 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.
Year
DOI
Venue
2016
10.1145/2882903.2915245
SIGMOD/PODS'16: International Conference on Management of Data San Francisco California USA June, 2016
DocType
Volume
ISSN
Journal
abs/1610.06978
Proceedings of the 2016 International Conference on Management of Data (SIGMOD '16), pp. 1011-1025
ISBN
Citations 
PageRank 
978-1-4503-3531-7
17
0.77
References 
Authors
17
4
Name
Order
Citations
PageRank
Fernando Seabra Chirigati120516.38
Harish Doraiswamy225218.95
Theodoros Damoulas321921.66
Juliana Freire43956270.89