Advertisement

A Model of Aggregate Operations for Data Analytics over Spatiotemporal Objects

  • Logan Maughan
  • Mark McKenney
  • Zachary Benchley
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8823)

Abstract

In this paper, we identify a conceptual framework to explore notions of spatiotemporal aggregate operations over moving objects, and use this framework to discover novel aggregate operators. Specifically, we provide constructs to discover temporal and spatial coverage of a query window that may itself be moving, and identify quantitative properties of entropy relating to the motion of objects.

Keywords

Spatial Object Space Coverage Temporal Coverage Moving Region Motion Window 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Güting, R.H., Böhlen, M.H., Erwig, M., Jensen, C.S., Lorentzos, N.A., Schneider, M., Vazirgiannis, M.: A Foundation for Representing and Querying Moving Objects. ACM Trans. Database Syst. 25(1), 1–42 (2000)CrossRefGoogle Scholar
  2. 2.
    Lazaridis, I., Mehrotra, S.: Progressive approximate aggregate queries with a multi-resolution tree structure. SIGMOD Rec. 30(2), 401–412 (2001)CrossRefGoogle Scholar
  3. 3.
    Lopez, I., Snodgrass, R., Moon, B.: Spatiotemporal aggregate computation: a survey. IEEE Transactions on Knowledge and Data Engineering 17(2), 271–286 (2005)CrossRefGoogle Scholar
  4. 4.
    McKenney, M., Olsen, B.: Algorithms for fundamental spatial aggregate operations over regions. In: Proceedings of the ACM SIGSPATIAL BigSpatial, pp. 55–64 (2013)Google Scholar
  5. 5.
    Papadias, D., Kalnis, P., Zhang, J., Tao, Y.: Efficient olap operations in spatial data warehouses. In: Proceedings of SSTD (2001)Google Scholar
  6. 6.
    Schneider, M., Behr, T.: Topological relationships between complex spatial objects. ACM Trans. Database Syst. 31(1), 39–81 (2006)CrossRefGoogle Scholar
  7. 7.
    Wolfson, O., Sistla, P., Xu, B., Xu, J., Chamberlain, S.: Domino: Databases for moving objects tracking. SIGMOD Rec. 28(2), 547–549 (1999)CrossRefGoogle Scholar
  8. 8.
    Worboys, M.F.: A unified model for spatial and temporal information. The Computer Journal 37(1), 26–34 (1994)CrossRefGoogle Scholar
  9. 9.
    Zhang, D., Tsotras, V.: Improving min/max aggregation over spatial objects. In: Proceedings of ACM GIS (2001)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Logan Maughan
    • 1
  • Mark McKenney
    • 1
  • Zachary Benchley
    • 1
  1. 1.Department of Computer ScienceSouthern Illinois University EdwardsvilleEdwardsvilleUSA

Personalised recommendations