The Open Geospatial Consortium (OGC) supports interoperable solutions that geo-enable data about the world we live in. Its standards empower technology developers to make spatial information and services accessible and useful with all kinds of applications.
Having invested billions in spatial data collection, and witnessing rapid growth in the ways that data can be captured and published, organizations face the challenge of how to best use the data.
"I didn't know it existed"; "I couldn't get access to it"; and "It's not compatible with my system" are barriers that are falling away as standards-based web catalogue, map, feature and coverage services become widely used. Another barrier, "I don't trust it", remains.
So what about trust? How does one know, with confidence, that the data to be shared and re-used in this interoperable world is fit for the intended purpose? Fit for my purpose?
To facilitate this understanding, it is essential those quality assertions are expressed in a comparable way and that there is common knowledge of the measures used. ISO 19113, 19114 and 19138 (which are soon to be superseded by the new ISO 19157) provide principles for describing the quality of geographic data and offer a consistent way to determine and report a dataset's quality information, with guidelines for evaluation procedures of quantitative quality information. Furthermore, the draft ISO 19158 aims to provide a quality assurance framework for the producer and customer in their supplier-consumer relationship, identifying methods of managing the quality of production more efficiently and effectively.
Focusing on these issues and these ISO standards, the OGC Data Quality Domain Working Group (DQ DWG) is a global forum for the collaboration of producers and users of spatial data. The DQ DWG members seek to understand the use cases and describe a practical interoperable web services framework that builds on the ISO standards.
In 2007/08 the DQ DWG initiated its formation with a survey to measure interest and understanding of DQ within the geospatial industry. The survey received almost 800 responses from 107 countries, ranging from small to very large organisations and from commercial to government enterprises. Nearly all identified DQ as important, but almost half had no clear approach to managing it. However, a majority of those responding were willing to pay more for higher quality data in their projects, if they could just be sure that the quality was there. Yet there was great variety in how data quality was measured. So for most organisations, DQ appears to be something that is important, but difficult to quantify.
The group provides an opportunity to share experiences on the importance of good quality data (and the impact of poor quality data) for business domains such as national and international mapping, oil and gas, aviation and earth observation. Members discuss best practices for monitoring and reporting on the levels of accuracy and uncertainty in relation to the new ISO 19157; collaborate with projects like GeoViQua, which seeks to develop concepts for visually informing data users on usability and overall quality; and investigate approaches to improving currency and data completeness. Devising successful interface and encoding standards requires such discussion among users and providers of data working in diverse domains. It is necessary to have a shared understanding of the role of DQ control in the information supply chain, from change notification through data update to product generation, publishing and consumption. The standards emerging from this effort will enable knowledge of DQ levels to inform business intelligence that enables organisations to assess and mitigate the risk to their operations and future strategies.
Principle Consultant, 1Spatial
President, Blue Marble Geographics
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