Geographic information. Data quality

2015 ◽  
Keyword(s):  
Data Quality ◽  
Geographic Information

scholarly journals Corporate Editors in the Evolving Landscape of OpenStreetMap

2019 ◽  
Vol 8 (5) ◽  
pp. 232 ◽  
Author(s):  
Jennings Anderson ◽  
Dipto Sarkar ◽  
Leysia Palen
Keyword(s):  
Data Quality ◽  
Road Networks ◽  
Volunteered Geographic Information ◽  
Geographic Information ◽  
Points Of Interest ◽  
The World ◽  
History Of ◽  
Multiple Uses ◽  
Map Data ◽  
Information Project

OpenStreetMap (OSM), the largest Volunteered Geographic Information project in the world, is characterized both by its map as well as the active community of the millions of mappers who produce it. The discourse about participation in the OSM community largely focuses on the motivations for why members contribute map data and the resulting data quality. Recently, large corporations including Apple, Microsoft, and Facebook have been hiring editors to contribute to the OSM database. In this article, we explore the influence these corporate editors are having on the map by first considering the history of corporate involvement in the community and then analyzing historical quarterly-snapshot OSM-QA-Tiles to show where and what these corporate editors are mapping. Cumulatively, millions of corporate edits have a global footprint, but corporations vary in geographic reach, edit types, and quantity. While corporations currently have a major impact on road networks, non-corporate mappers edit more buildings and points-of-interest: representing the majority of all edits, on average. Since corporate editing represents the latest stage in the evolution of corporate involvement, we raise questions about how the OSM community—and researchers—might proceed as corporate editing grows and evolves as a mechanism for expanding the map for multiple uses.

scholarly journals The Spatial-Comprehensiveness (S-COM) Index: Identifying Optimal Spatial Extents in Volunteered Geographic Information Point Datasets

2020 ◽  
Vol 9 (9) ◽  
pp. 497
Author(s):  
Haydn Lawrence ◽  
Colin Robertson ◽  
Rob Feick ◽  
Trisalyn Nelson
Keyword(s):  
Social Media ◽  
Data Quality ◽  
Spatial Scales ◽  
Volunteered Geographic Information ◽  
Geographic Information ◽  
Quality Metric ◽  
Fine Grained ◽  
Multi Scale ◽  
Feasible Study

Social media and other forms of volunteered geographic information (VGI) are used frequently as a source of fine-grained big data for research. While employing geographically referenced social media data for a wide array of purposes has become commonplace, the relevant scales over which these data apply to is typically unknown. For researchers to use VGI appropriately (e.g., aggregated to areal units (e.g., neighbourhoods) to elicit key trend or demographic information), general methods for assessing the quality are required, particularly, the explicit linkage of data quality and relevant spatial scales, as there are no accepted standards or sampling controls. We present a data quality metric, the Spatial-comprehensiveness Index (S-COM), which can delineate feasible study areas or spatial extents based on the quality of uneven and dynamic geographically referenced VGI. This scale-sensitive approach to analyzing VGI is demonstrated over different grains with data from two citizen science initiatives. The S-COM index can be used both to assess feasible study extents based on coverage, user-heterogeneity, and density and to find feasible sub-study areas from a larger, indefinite area. The results identified sub-study areas of VGI for focused analysis, allowing for a larger adoption of a similar methodology in multi-scale analyses of VGI.

scholarly journals Crowdsourcing the Cadastre: The Applicability of Crowdsourced Geospatial Information to the New Zealand Cadastre

2021 ◽  
Author(s):  
◽  
Andrew David Clouston
Keyword(s):  
New Zealand ◽  
Data Quality ◽  
Qualitative Methodology ◽  
Geographic Information ◽  
Geospatial Data ◽  
Multiple Use ◽  
Two Phase ◽  
Geospatial Information ◽  
Potential Applicability ◽  
Existing Data

<p>Crowdsourcing has transformed how geographic information is collected, stored, disseminated, analysed, visualised and used (Sui et al., 2013b). Yet, crowdsourcing has had little impact on core government geospatial data. This ‘authoritative data’ is often tightly controlled with a focus on data quality and security for protection from unauthorised change (Rice et al., 2012). Opportunities for consumers, users and existing data producers to contribute their skills and information to enhance authoritative government geospatial data has been limited. The adoption, or use, of crowdsourcing by Government has been slow (Haklay et al., 2014).  The New Zealand Cadastre, managed by Land Information New Zealand (LINZ) is an example of a core government geospatial system that has collated and managed data for over a century. Despite data meeting the contemporary acceptance standards when it was integrated into the cadastre, data quality is often questioned by users as inaccuracies or discrepancies are identified (Opus, 2013). Web 2.0 technologies and easy to use mobile devices enabled geospatial capability and a user skill base to an increased acceptance of crowdsourcing as a means to build and maintain geospatial datasets (Kostanski, 2012, McLaren, 2011, Rice et al., 2012). Accordingly, if cadastral data is to be maintained and enhanced to meet modern expectations for multiple use (LINZ, 2013a, Cadastre Ltd, 2003), one option is the use of crowdsourcing (Grant et al., 2014, LINZ, 2013a).  This thesis examines the potential applicability of Volunteered Geographic Information (VGI) as a specific form of crowdsourcing within an authoritative database - the New Zealand Cadastre. Using a two phase quantitative and qualitative methodology, the perspectives of users, data providers and administrators are explored to ascertain the applicability of VGI to the New Zealand Cadastre.  This thesis finds that crowdsourcing concepts could enable users to contribute data or information, re-conceptualise the role of the existing data providers (predominately licensed cadastral surveyors) and enable the reuse of cadastral related work. Cadastral VGI can provide advances in data collection and maintenance processes; if users, data producers and administrators change their perception of what crowdsourcing is, and what it can provide. However, the importance of user perception in the quality of the dataset will need to be strongly considered in any integration of VGI into the cadastre or other authoritative datasets.</p>

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