Encyclopedia of GIS

2017 Edition
| Editors: Shashi Shekhar, Hui Xiong, Xun Zhou

Data Stream Systems, Empowering with Spatiotemporal Capabilities

  • Mohamed Ali
Reference work entry
DOI: https://doi.org/10.1007/978-3-319-17885-1_1589


Spatiotemporal data streaming (or geostreaming) refers to the acquisition, processing, and analysis of stream data that has geographical locations and/or spatial extents such as point coordinates, lines, or polygons.

Real-time stream data acquisition through sensors and probes has been widely used in numerous applications. Hence, integrating spatial operators in commercial data-streaming engines has gained tremendous interest in recent years. In this entry, we consider the Microsoft StreamInsight (StreamInsight, for brevity) as our industrial case study. We highlight the background beyond its temporal model and discuss the various efforts that leverage its temporal model to the spatial domain.

Historical Background

Spatial queries and operations are common and essential for a variety of location-aware applications, e.g., find out the gas stations nearby a driver’s location. During the last...

This is a preview of subscription content, log in to check access.


  1. Abadi D et al (2005) The design of the Borealis stream processing engine. In: CIDR. Asilomar, CAGoogle Scholar
  2. Ali M et al (2009) Microsoft CEP server and online behavioral targeting. In: VLDB. Lyon, FranceGoogle Scholar
  3. Ali M, Chandramouli B, Sethu Raman B, Katibah E (2010) Spatio-temporal stream processing in microsoft streaminsight. IEEE Data Eng Bull 33(2): 69–74Google Scholar
  4. Ali M, Chandramouli B, Goldstein J, Schindlauer R (2011) The extensibility framework in microsoft streaminsight. In: ICDE. Hannover, GermanyCrossRefGoogle Scholar
  5. Barga R et al (2007) Consistent streaming through time: a vision for event stream processing. In: CIDR. Asilomar, CAGoogle Scholar
  6. Chandrasekaran S et al (2003) TelegraphCQ: continuous dataflow processing for an uncertain world. In: CIDR. Asilomar, CACrossRefGoogle Scholar
  7. Chandramouli B, Goldstein J, Maier D (2009) On-the-fly progress detection in iterative stream queries. In: VLDB. Lyon, FranceGoogle Scholar
  8. Cranor C et al (2003) Gigascope: a stream database for network applications. In: SIGMOD. San Diego, CACrossRefGoogle Scholar
  9. Daubal M, Fajinmi O, Jangaard L, Simonson N, Yasutake B, Newell J, Ali M (2013) Safe step: a real-time gps tracking and analysis system for criminal activities using ankle bracelets. In: The ACM SIGSPATIAL conference on advances in geographic information systems, GIS. Orlando, FLCrossRefGoogle Scholar
  10. Jensen C, Snodgrass R (1992) Temporal specialization. In: ICDE. Tempe, AZCrossRefGoogle Scholar
  11. Jeremiah M, Raymond M, Archer J, Adem S, Hansel L, Konda S, Luti M, Zhao Y, Teredesai A, Ali M (2011) An extensibility approach for spatio-temporal stream processing using microsoft streaminsight. In: The international symposium on spatial and temporal databases, SSTD. Minneapolis, MNGoogle Scholar
  12. Kazemitabar SJ, Demiryurek U, Ali MH, Akdogan A, Shahabi C (2010) Geospatial stream query processing using microsoft sql server streaminsight. In: VLDB. SingaporeGoogle Scholar
  13. Motwani R et al (2003) Query processing, approximation, and resource management in a DSMS. In: CIDR. Asilomar, CAGoogle Scholar
  14. Open Geospatial Consortium. http://www.opengeospatial.org/standards/sfa (Last Accessed March 2016)
  15. Ryvkina E et al (2006) Revision processing in a stream processing engine: a high-level design. In: ICDE. Atlanta, GAGoogle Scholar
  16. Shekhar S, Evans MR, Gunturi V, Yang K (2012) Spatial big-data challenges intersecting mobility and cloud computing. In: The NSF workshop on social networks and mobility in the cloud. Washington DCCrossRefGoogle Scholar
  17. SQL Server Spatial Libraries. http://www.microsoft.com/sqlserver/2008/en/us/spatial-data.aspx (Last Accessed March 2016)
  18. Srivastava U, Widom J (2004) Flexible time management in data stream systems. In: PODS. Paris, FranceCrossRefGoogle Scholar
  19. StreamBase Inc. http://www.streambase.com/ (Last Accessed March 2016)
  20. Tucker P et al (2003) Exploiting punctuation semantics in continuous data streams. In: IEEE TKDEGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Center for Data Science, Institute of TechnologyUniversity of WashingtonTacomaUSA