Semantic and syntactic interoperability in online processing of big Earth observation data

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Abstract

The challenge of enabling syntactic and semantic interoperability for comprehensive and reproducible online processing of big Earth observation (EO) data is still unsolved. Supporting both types of interoperability is one of the requirements to efficiently extract valuable information from the large amount of available multi-temporal gridded data sets. The proposed system wraps world models, (semantic interoperability) into OGC Web Processing Services (syntactic interoperability) for semantic online analyses. World models describe spatio-temporal entities and their relationships in a formal way. The proposed system serves as enabler for (1) technical interoperability using a standardised interface to be used by all types of clients and (2) allowing experts from different domains to develop complex analyses together as collaborative effort. Users are connecting the world models online to the data, which are maintained in a centralised storage as 3D spatio-temporal data cubes. It allows also non-experts to extract valuable information from EO data because data management, low-level interactions or specific software issues can be ignored. We discuss the concept of the proposed system, provide a technical implementation example and describe three use cases for extracting changes from EO images and demonstrate the usability also for non-EO, gridded, multi-temporal data sets (CORINE land cover). © 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Translated title of the contributionSemantic and syntactic interoperability in online processing of big Earth observation data
Original languageEnglish
Pages (from-to)95-112
JournalInternational Journal of Digital Earth
Volume11
Issue number1
DOIs
Publication statusPublished - 2018

Bibliographical note

Funding: Austrian Science Fund (DK W1237-N23), Research Promotion Foundation

Keywords

  • OGC WPS
  • big Earth data
  • large-scale processing
  • model-driven semantic analyses
  • time series

Fields of Science and Technology Classification 2012

  • 105 Geosciences
  • 207 Environmental Engineering, Applied Geosciences

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