Spatiotemporal database

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A spatiotemporal database is a database that manages both space and time information. Common examples include:

  • Tracking of moving objects, which typically can occupy only a single position at a given time.
  • A database of wireless communication networks, which may exist only for a short timespan within a geographic region.
  • An index of species in a given geographic region, where over time additional species may be introduced or existing species migrate or die out.
  • Historical tracking of plate tectonic activity.

Spatiotemporal databases are an extension of spatial databases and temporal databases. A spatiotemporal database embodies spatial, temporal, and spatiotemporal database concepts, and captures spatial and temporal aspects of data and deals with:

  • geometry changing over time and/or
  • location of objects moving over invariant geometry (known variously as moving objects databases[1] or real-time locating systems).

Implementations[]

Although there exist numerous relational databases with spatial extensions, spatiotemporal databases are not based on the relational model for practical reasons, chiefly among them that the data is multi-dimensional, capturing complex structures and behaviours.

As of 2008, there are no RDBMS products with spatiotemporal extensions. There are some products such as the open-source TerraLib which use a middleware approach storing their data in a relational database. Unlike in the pure spatial domain, there are however no official or de facto standards for spatio-temporal data models and their querying. In general, the theory of this area is also less well-developed.[2] Another approach is the constraint database system such as MLPQ (Management of Linear Programming Queries).[3][4]

GeoMesa is an open-source distributed spatiotemporal index built on top of Bigtable-style databases using an implementation of the Z-order_curve to create a multi-dimensional index combining space and time.

SpaceTime is a commercial spatiotemporal database built on top of the proprietary multidimensional index similar to the kd-tree family, but created using the bottom-up approach and adapted to particular space-time distribution of data.[5]

See also[]

References[]

  1. ^ Ralf Hartmut Güting; Markus Schneider (2005). Moving Objects Databases. Academic Press. ISBN 978-0-12-088799-6.
  2. ^ Brent Hall; Michael G. Leahy (2008). Open Source Approaches in Spatial Data Handling. Springer. pp. 126–128. ISBN 978-3-540-74830-4.
  3. ^ Peter Revesz (2010). Introduction to Databases: From Biological to Spatio-Temporal. Springer. p. 262. ISBN 978-1-84996-094-6.
  4. ^ "Instructions for MLPQ system".
  5. ^ "Mireo SpaceTime – an absurdly fast moving objects database".

External links[]

Organizations[]

Implementations[]


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