Spatial Data on the Web notes from WWW conference 2017

From simple visualizations to sophisticated interactive tools, there is a growing reliance on data. Location information, or spatial data, is often a common thread running through such data; describing how things are positioned relative to the Earth in terms of coordinates and/or topology.- Spatial Data on the Web (WWW2017)

Spatial Data on the Web Best Practices

Armin Haller, ANU

Spatial Data on the Web Best Practices document:

What is the problem this working group is trying to solve:

What is the quality of the spatial data information?

Sample search: Google search for Beaches in the United Kingdom Does this search result bring the relevant spatial data?

Inspire Geoportal has the better information on the spatial data for UK coastline.

Unfamiliar protocols

Inspire and Google are two different protocols and resources. The results are different.

The geospatial industry has developed its own web services to publish location information.

Data is implicit and unstructured. Is data really “on the web” if you can’t find it via a search engine?

Most web content about places and location is unstructured. Harvesting requires sophisticated Natural Language Processing and inference. It does not scale.

Linked Open Data

Linked Geospatial Consortium and W3C combined to developer Linked Geospatial Data.

  • how should we encode geometry?
  • how and where should we implement topological functions
  • geometries express as WKT literals – large objects.
  • 2D or 3D

Spatial Web Data Working Group

The mission of the Spatial Data on the Web Working Group is to clarify and formalize the relevant standards landscape. In particular:

  • to determine how spatial information can best be integrated with other data on the Web;
  • to determine how machines and people can discover that different facts in different datasets relate to the same place, especially when ‘place’ is expressed in different ways and at different levels of granularity;
  • to identify and assess existing methods and tools and then create a set of best practices for their use; where desirable, to complete the standardization of informal technologies already in widespread use.

Spatial Data on the Web Use Cases & Requirements

Five stars of linked data: Tim Berners-Lee, the inventor of the Web and Linked Data initiator, suggested a 5-star deployment scheme for Open Data.

Data on the Web best practices

Best Practices Summary


Best practices for Open Spatial Data (some have been deleted)

Sensors, Satellites and Linking the Earth

Kerry Taylor (Australian National University, University of Surrey)

Semantic Sensor Networks (SSN)

SSN Ontology: This ontology describes sensors and observations, and related concepts. It does not describe domain concepts, time, locations, etc. these are intended to be included from other ontologies via OWL imports. This ontology is developed by the W3C Semantic Sensor Networks Incubator Group (SSN-XG).

Semantic sensor networks: Capabilities of sensors, measuring capability, sensors in systems, act and method of sensing, the results of sensing, and observations.

SOSA a.k.a. SSN Core
  • Actuator and actuation
  • Observation and its result
  • Samples an sampling
  • A little about sensors
  • No inference, just assertions
Extended SSN
  • Deployment
  • sensing and actuating capabilities
  • properties of measurements
  • systems of sensors and actuators
  • operating conditions, survival conditions
  • sensor behavior
  • typing constraints and class relations
  • supports inference to fill gaps

Publishing and Using Earth Observation Data with the RDF Data Cube and the Discrete Global Grid System

Giant size of satellite data has problems

  • granularity of tiles, not pixels
  • smallish metadata served through an ordinary triple store (linked data)
  • hugs raster data
  • specialized query processing
  • simple optimisations applied


Australia’s distributed national spatial dataset production systems and community

by Nicholas Car  (Geoscience Australia)

ANZLIC: the Spatial Information Council is the peak intergovernmental organisation providing leadership in the collection, management and use of spatial information in Australia and New Zealand.

Federal an state initiative to streamline the production of national spatial data products.

  • for the Dept. Prime Minister and Cabinet
  • coordinated by Geoscience Australia

FSDF is not:

  • an awesome tool. It is not “smart”, “machine learning”, etc.
  • It’s not a fast, non-permanent “initiative”. It is building a foundation
  • run by one agency or achieve success via one channel.

Introducing NZ to a new paradigm for spatial data

Byron Cochrane (Department of Internal Affairs, New Zealand Government)

What is special about New Zealand

  • New Zealand is rather isolated and tends to build there own solutions.
  • It is very unstable with earth quakes
  • aligning data sets is continually changing.

What is special about spatial data

  • the better you know it, the better you can use it
  • it’s popular

Old paradigm of spatial data

  • kicked off in the 90’s
  • centrally managed and tightly controlled
  • geoSpatial data engineers wanted a lot of access and data storage.
  • geo data was walled off by IT specialistws
  • Communication became easier between other geospatial data developers than the IT system that has isolated them.
  • spatial data was put into relational databases, but these were not very effective
  • a custom front end was created for the spatial data, but this fragile and exclusive.
  • IT systems began connecting to the web, but the geospatial data had to take their own path to exposing data
  • Spatial data was exposed via XML and SOAP

New paradigm

  • Move towards the Linked Data space.
  • To do this, it was necessary to reach out to the global community.
  • Use modern standards
  • integrate linked data best practices





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