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Managing Spatio-Temporal Big Data through Scalable OGC Web Services

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Managing Spatio-Temporal Big Data through Scalable OGC Web Services
FOSDEM 2016

In geosciences, and especially in the fields of remote sensing and geomatics, frequently large amounts of raster data need to be stored and processed efficiently. Rasdaman is tackling the big data deluge by providing a scalable array database that is capable of storing complex geographic data structures and exposing them through open and standard web services. Actually, the rasdaman team is actively shaping the OGC Big Geo Data standards.

Rasdaman is the OGC Web Coverage Service (WCS) Core Reference Implementation, but also supports WMS and WPS, for example. A particularly exciting extension of the WCS service is the Processing Extension. This links in the Web Coverage Processing Service (WCPS) which allows users to exploit the flexibility of a fully fledged query language for coverages to request ad-hoc parallel processing directly on the server, minimizing data transfer and response times.

In geosciences, and especially in the fields of remote sensing and geomatics, frequently large amounts of raster data need to be stored and processed efficiently. Rasdaman is tackling the big data deluge by providing a scalable array database that is capable of storing complex geographic data structures and exposing them through open and standard web services. Actually, the rasdaman team is actively shaping the OGC Big Geo Data standards.

Rasdaman is the OGC Web Coverage Service (WCS) Core Reference Implementation, but also supports WMS and WPS, for example. A particularly exciting extension of the WCS service is the Processing Extension. This links in the Web Coverage Processing Service (WCPS) which allows users to exploit the flexibility of a fully fledged query language for coverages to request ad-hoc parallel processing directly on the server, minimizing data transfer and response times. With that in mind, our proposed workshop will follow this structure:

Presenting the core concepts and technology:

  • The rasdaman array model and its query language
  • The GMLCOV model
  • The Web Coverage Service and its extensions
  • Hands-on exercises, experimenting with real data using the above mentioned services.

Workshop participants will:

  • Deploy rasdaman and its required components to create a local service
  • Learn how to ingest data into rasdaman and how to expose it as a coverage. Three types of coverages will be handled (2D rectified imag, 3D regular time series of satellite imagery,3D irregular time series of satellite imagery)
  • Learn how to use the WCS service to access coverages
  • Explore the extensions of the WCS service and the functionality that they provide
  • Ad-hoc process the coverages using WCPS queries

Speakers: Alex Dumitru