CROWDSOURCED MAPPING – LETTING AMATEURS INTO THE TEMPLE?

Abstract. The rise of crowdsourced mapping data is well documented and attempts to integrate such information within existing or potential NSDIs [National Spatial Data Infrastructures] are increasingly being examined. The results of these experiments, however, have been mixed and have left many researchers uncertain and unclear of the benefits of integration and of solutions to problems of use for such combined and potentially synergistic mapping tools. This paper reviews the development of the crowdsource mapping movement and discusses the applications that have been developed and some of the successes achieved thus far. It also describes the problems of integration and ways of estimating success, based partly on a number of on-going studies at the University of Nottingham that look at different aspects of the integration problem: iterative improvement of crowdsource data quality, comparison between crowdsourced data and prior knowledge and models, development of trust in such data, and the alignment of variant ontologies. Questions of quality arise, particularly when crowdsource data are combined with pre-existing NSDI data. The latter is usually stable, meets international standards and often provides national coverage for use at a variety of scales. The former is often partial, without defined quality standards, patchy in coverage, but frequently addresses themes very important to some grass roots group and often to society as a whole. This group might be of regional, national, or international importance that needs a mapping facility to express its views, and therefore should combine with local NSDI initiatives to provide valid mapping. Will both groups use ISO (International Organisation for Standardisation) and OGC (Open Geospatial Consortium) standards? Or might some extension or relaxation be required to accommodate the mostly less rigorous crowdsourced data? So, can crowdsourced data ever be safely and successfully merged into an NSDI? Should it be simply a separate mapping layer? Is full integration possible providing quality standards are fully met, and methods of defining levels of quality agreed? Frequently crowdsourced data sets are anarchic in composition, and based on new and sometimes unproved technologies. Can an NSDI exhibit the necessary flexibility and speed to deal with such rapid technological and societal change?