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dc.contributor.advisorMackaness, William
dc.contributor.authorMacCalman, Miles
dc.date.accessioned2015-05-06T13:57:18Z
dc.date.available2015-05-06T13:57:18Z
dc.date.issued27/11/2014
dc.identifier.urihttp://hdl.handle.net/1842/10359
dc.description.abstractSpatial data is becoming increasingly important to decision making in all areas of life, affecting all types of businesses and services, right down to individuals throughout our towns, cities and countryside. With the rise of Volunteered Geographic Information (VGI), government initiatives on making more data ‘open’ and the monopoly of formal spatial data providers, there are now many different choices about what source of spatial data is best suited to a particular task or activity. This paper explores the quality of a VGI data source, namely OpenStreetMap (OSM). It explores various aspects of quality by focusing on a range of Scottish school data, covering three local council areas. The data has been collected from a number of different sources - formal and informal; open and licenced. The aim is to ascertain how the datasets compare to each other, quantify their strengths and highlight any possible weaknesses. The results of this study show that to get a complete picture of schools in an area, no one dataset can be relied on alone. Each one has its positive and negative aspects. If VGI is to truly compete with established formal data providers, there needs to be more encouragement, help and guidance for contributors on adding metadata and attribution to the objects they draw, so that the data has the potential to be used for spatial analysis and research purposes.en_US
dc.language.isoenen_US
dc.publisherThe University of Edinburghen_US
dc.subjectVGIen_US
dc.subjectOpenStreetMapen_US
dc.subjectOrdnance Surveyen_US
dc.subjectopen dataen_US
dc.subjectcrowd sourced dataen_US
dc.subjectVGIen
dc.subjectOpenStreetMapen
dc.subjectOrdnance Surveyen
dc.subjectopen dataen
dc.subjectcrowd sourced dataen
dc.subjectMSc Geographical Information Scienceen
dc.subjectGISen
dc.titleExploring the quality of crowd sourced data: A comparison and analysis of formal and informal school datasets from open and licenced sourcesen_US
dc.typeThesis or Dissertationen_US
dc.type.qualificationlevelMastersen_US
dc.type.qualificationnameMSc Master of Scienceen_US
dcterms.accessRightsRestricted Accessen_US


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