® ® Big Geospatial Data: Open Approaches to Loosely-Coupled Ecosystems George Percivall CTO, Chief Engineer Open Geospatial Consortium

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Presentation transcript:

® ® Big Geospatial Data: Open Approaches to Loosely-Coupled Ecosystems George Percivall CTO, Chief Engineer Open Geospatial Consortium © 2016 Open Geospatial Consortium

OGC ® Big Geospatial Data © 2016 Open Geospatial Consortium 1PB in 1995 required a large building 1PB in 2016 requires a 1 car garage EROS Data Center, Sioux Falls, SDCyberGIS at NCSA Univ. of Illinois

OGC ® Commercial cloud hosting of large imagery archives with local processing DigitalGlobe –Entire DG archive in cloud in PB - largest EO archive –Harris/ENVI processing Google Earth Engine –5 PB storage (Landsat and others) Library Functions –Limiting factor is the ability to pull data from another cloud to support local processing. Hexagon Geospatial –Cloud hosted dynamic information service –AirBus archive in Amazon cloud with Hexagon services. © 2016 Open Geospatial Consortium Three presentations at ISPRS Congress, July 2016

OGC ® Open Approaches to Loosely-Coupled Geo-Imagery Clouds Approaches for Geo-Clouds to support loose-coupling while enabling competition –Identify open strategies Portability of data across cloud archives –Emphasis on information models, semantics, encodings –E.g., Discrete Global Grid Systems Algorithm and workflow abstractions –Processing and workflow control from web clients –Metadata for describing algorithms. Respond to the Proliferation of APIs and resulting degradation of interoperability © 2016 Open Geospatial Consortium

OGC ® Discrete Global Grid Systems “…a spatial reference system that uses a hierarchical tessellation of cells to partition and address the globe. DGGS are characterized by the properties of their cell structure, geo-encoding, quantization strategy and associated mathematical functions.” –OGC DGGS Candidate Standard Copyright © 2016 Open Geospatial Consortium

OGC ® Standardizing Discrete Global Grid Systems Copyright © 2016 Open Geospatial Consortium Different Cell Shapes Square = FamiliarTriangular = FastHexagonal = Fineness of Fit nD Spatial Analyses  1D Array Processes Unique Cell Indices Hierarchy-based, Space-filling Curve, Axes-based or Encoded Address

OGC ® Use Cases for Big Geo Data © 2016 Open Geospatial Consortium IoT Message Streaming Social Media Message Processing ETL Stream processing using RDF Observation Sources Users and consuming apps High Velocity Ingest Wide Area Motion Imagery Entity-oriented Spatial-temporal analytics Grid-oriented Spatial-temporal analytics Feature Fusion GeoAnalytics, Machine Learning Remote sensed data processing Machine Learning Array databases NoSQL databases Graph databases Geospatial Databases Built environment models Integrated environmental models Modeling and simulation Spatial Modeling SQL databases

OGC ® Location Powers: Big Data Tuesday 20th September Orlando, Florida © 2016 Open Geospatial Consortium #LPBigData

OGC ® The Open Geospatial Consortium © 2016 Open Geospatial Consortium Open Geospatial Consortium OGC Standards - freely available OGC on YouTube George Percivall