Improving Geospatial Integrity For Geoscience Software
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Improving Geospatial Integrity For Geoscience Software

An initiative by the International Association of Oil & Gas Producers (OGP, UK) is enabling geoscience software developers and users to rely on an industry best practice for evaluating the geospatial integrity of their software. Details of the Geospatial Integrity of Geoscience Software (GIGS) initiative came at the ECIM international data management conference in Haugesund, Norway in September 2011.  

 

The event attracted many of the industry's leading software vendors and developers. GIGS is a process developed in response to concerns arising from violations in the geospatial integrity of data when using geoscience software. This has led to inaccurate results and ambiguities for the user community. Integrity issues such as these are of concern to the oil & gas industry.

 

As a consequence, the OGP's Geomatics Committee, in its role as the industry provider of geomatics guidance, launched the GIGS review process as a way of mitigating such risks. GIGS can make a qualitative evaluation of any software's geospatial capability by means of a series of checklists, and perform a quantitative evaluation using approved test data sets. Software vendors, developers, clients, and users can all benefit from the results of a GIGS review.

 

The need for GIGS has become evident during the past decade, as over 95% of the industry's data is spatially referenced. In 2007 a Joint Industry Project (JIP), comprised of a significant number of major oil & gas E&P companies together with smaller regional operators, initiated a study to provide geoscience software developers with recommended guidance concerning industry best practise for ensuring geospatial integrity. This resulted in a number of international workshops.

 

The JIP delivered its findings to OGP in mid 2010. The Association's Geomatics committee refined this work into three documents: ‘Part 1 - Guidelines', ‘Part 2 - Software Review'  and ‘Part 3 - User guide for the GIGS Test Dataset'

 

 

 

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