HTML as a natural way for linking. OWS Context encoded in JSON-LD in a

60 Copyright © 2015 Open Geospatial Consortium. url: ftp:ftp.remotesensing.orgpubgeotiffsamplesgdal_egcea.tif , price: 0.00 } } script Figure 6: OWS Context example encoded in schema.org JSON-LD and tested in the Google Structured Data Testing Tool Recommendation 22: Consider JSON-LD encodings for HTML structured data to create another encoding for OWS Context. Target: OWS Context 9 Coverage JSON GeoJSON covers the need for encoding features in JSON and makes it easier to deal with geospatial features in the browser. TopoJSON was created to easily encode and deal with specific case of 2D topological polygons in the browser. We could think if there is the same need for coverages. If we think just about referenced grids, a grid is just a sequence of values. In practice this could just be encoded in a JSON array. In fact, there is an initiative in Github to convert a netCDF file into JSON that just does a conversion of netCDF to JSON as an object that contains arrays of values: https:github.comjllodrancdump-json Copyright © 2015 Open Geospatial Consortium. 61 But a referenced grid is a bit more than an array. It requires some extra metadata to fully describe the meaning of the array of values. NetCDF also contains this description and the mentioned application is able also to extract it using this syntax: ncdump-json sresa1b_ncar_ccsm3-example.nc -h –j And the resulting data for a NetCDF example is: { dimensions: { lat: 128, lon: 256, bnds: 2, plev: 17, time: UNLIMITED ; 1 currently }, variables: { area: { type: float, dimensions: [ lat, lon ], attributes: { long_name: Surface area, units: meter2 } }, lat: { type: float, dimensions: [ lat ], attributes: { long_name: latitude, units: degrees_north, axis: Y, standard_name: latitude, bounds: lat_bnds } }, ... 62 Copyright © 2015 Open Geospatial Consortium. }, global_attributes: { CVS_Id: Id, creation_date: , prg_ID: Source file unknown Version unknown Date unknown, cmd_ln: bds -x 256 -y 128 -m 23 -o datazenderdatadst_T85.nc, contact: ccsmucar.edu, project_id: IPCC Fourth Assessment, Conventions: CF-1.0, references: Collins, W.D., et al., 2005: The Community Climate System Model, Version 3 Journal of Climate Main website: http:www.ccsm.ucar.edu, acknowledgment: Any use of CCSM data should acknowledge the contribution of the CCSM project and CCSM sponsor agencies ..., realization: 1, experiment_id: 720 ppm stabilization experiment SRESA1B, model_name_english: NCAR CCSM } } This coverage description is specific for netCDF. There is a need for a standard description of a coverage in JSON.

9.1 GMLCov in JSON

OGC already provides a mean for encoding the description of a coverage that is raster encoding neutral and it is called GMLCov OGC 09-146r2. This standard defines a coverage by providing metadata and data about the domainSet definition of the grid structure, the rangeType definition of the values meaning and the rangeSet the actual values. Figure 7: GMLCov main subclasses Copyright © 2015 Open Geospatial Consortium. 63 Here we are applying the XML to JSON general rules to convert the GMLCov into a