The promise of discrete global grid systems


Geoscientific data and mass-market location data have already broken through the petabyte-scale barrier and are rapidly heading toward the exabyte-scale barrier. Traditional approaches to the acquisition, management, distribution and application of this data have limitations that have made it difficult to realise its true potential. Converting these massive data stores and data feeds into timely information and decision-support products depends on the ability of the data analyst or scientist to rapidly analyse the data in a transparent and repeatable fashion. The cost involved in data preparation can be prohibitive and often results in the data being discarded because it is too noisy or too large to handle, so initiatives are scaled back to focus on smaller areas or smaller time periods; alternatively, data from just one sensor source is used because it too hard for a particular group to justify the technical work required to make data from different sensors comparable. â©

The challenges of handling multi-source, high velocity, high volume (more than a terabyte per day) data require those focused on combining and using these large data sources to rethink the way they store geospatial data. Data velocity and volume will only continue to grow even as demands increase for near-real-time decision support information derived from the data.â©

The increasing integration of geospatial and location data into our everyday lives is driving an increasing expectation of spatial information on demand and with minimal delay. A new generation of decision-makers is also expecting systems that are not constrained by middle data integrators who package products in anticipation of their users’ questions. Decision-makers have grown in sophistication and expect to be able to routinely navigate time and space, mine the web for interesting information, and share their insights with others. They are always connected. They are experts who demand choices and control over their own experience. They expect all the information now.â©

When it comes to geospatial data, there remains a gap between expectation and the present reality. Geospatial data integration on-demand is a grand challenge – a challenge we have yet to solve.â©

Discrete global grid systems are a solutionâ©

The gap can be bridged through the conversion of traditional data archives into standardised data architectures that support parallel processing in distributed and/or high performance compute environments. Critical to this will be the implementation of global interoperability standards that will enable data fusion to be achieved without the bulk movement and refactoring of data across different networks. A common framework is required that will link very large multi-resolution and multi-domain datasets together, enabling the next generation of analytic processes to be applied.â©

Success has been achieved using a framework called a discrete global grid system (DGGS). A DGGS is a form of reference system that represents the Earth using a tessellation of discrete nested cells. Generally, a DGGS exhaustively partitions the globe in closely packed hierarchical tessellations, each cell representing a homogenous value, with a unique identifier or indexing that allows for linear ordering, parent-child operations, and nearest-neighbour algebraic operations.â©

While conventional coordinate reference systems are designed to facilitate repeatable navigation, a DGGS is designed to ensure a repeatable representation of measurements – observations, interpretations and events. Every item of information in a DGGS is associated with an area, and spatial resolution is explicit. This is much preferable to tagging an attribute with a latitude and longitude that doesn’t show what area possesses the attribute, or how accurate the measurement of location is. Combining or integrating layers becomes trivial in a DGGS, because items of information automatically line up. This is much like overlaying information across congruent rasters, and far easier than having to perform overlay using points, lines and areas. DGGS transforms paper-age Earth coordinates to computer-age Earth coordinates, vastly reducing the computational burden and errors imposed by paper-age coordinate transformations. DGGS is a transformative technology because removing these obstacles enables real-time data integration and less human intervention and it enables geoprocessing performance to scale in step with rapid advances in hardware, software and business models.â©

A DGGS can be optimised to provide statistically valid sampling, rapid storage, processing, transmission, discovery, visualisation, integration, aggregation, processing, analysis, and modelling. There are many possible DGGSs, each with their own advantages and disadvantages, with variations in shape, alignment and granularity of cells. â©

Some working examples include:â©

a) The Snyder Equal Area Aperture 3 Hexagonal (ISEA3H) DGGS implemented in the PYXIS Innovation WorldView client application and used to successfully demonstrate multi-source on-demand data integration and analysis in several OGC open web services cross-community interoperability test-beds and International Group on Earth Observations GEOSS architectural pilot projects.â©

b) The SCENZ-Grid DGGS (see Figure 1), developed by Landcare Research New Zealand, a rectangular DGGS based on 3x3 tessellations of the six faces of a hierarchical equal area iso-latitude pixelated ellipsoidal cube (HEALPix) designed for use in high performance computing and cloud architectures for inter-disciplinary environmental modelling.â©

What will the DGGS SWG accomplish?â©

The DGGS SWG will not aim to specify one single DGGS, but to increase awareness of the advantages of DGGSs in general, to define the qualities of a DGGS, to make them interoperable – with conventional and other DGGS data sources – and to standardise operations on them.â©

The DGGS SWG will develop a version 1.0 implementation standard that includes:â©

• A concise definition of DGGS as a spatial reference system.â©
• The essential properties of a conformant DGGS.â©
• The variability within these properties that classify types of DGGS.â©
• Elements of a spatial reference system identifier suitable for registering specific implementations of a DGGS.â©

It will also specify interoperable protocols within the standard or through extension documents to develop sample implementations. â©

Why the OGC?â©

• The OGC has a non-competitive, non-adversarial consensus process that allows professionals with many kinds of experience and expertise to collaborate on the development of standards.â©
• The OGC’s proven consensus process takes research results into industry for social benefit.â©
• The OGC’s existing standards, such as NetCDF, CityGML, SensorML, WCS, WCPS, WMTS and KML, are technology enablers.â©
• Testbeds executed in the OGC’s interoperability programme provide the best and fastest way to develop and test interoperability solutions.â©

Join the SWGâ©

The DGGS standards working group (SWG) presents an excellent opportunity for individuals and organisations to become recognised players in an emerging technology. OGC working group members contribute to leading edge technology developments and position themselves early for participation in OGC testbeds, pilot projects and interoperability experiments. The SWG is likely to lead to testbed activity that will produce standards and best practices; working, interoperable and commercially available technologies and products; and solid evidence of the availability and practicality of operational systems based on open standards. The SWG serves as incubator, a network hub and a starting point for business development and strategic technology planning.â©

If you are interested in the design, development, implementation or use of discrete global grid systems, please consider participating in the OGC DGGS SWG. â©

DGGS is a transformative technology because it enables geoprocessing performance to scale in step with rapid advances in hardware, software and business modelsâ©

Matthew BJ Purss is senior advisor, geospatial standards at the National Earth and Marine Observations Group, Environmental Geoscience Division, Geoscience Australia (www.ga.gov.au)