Assessment of Volunteered Geographic Information Data Quality in The National Map Corps Project of the U.S. Geological Survey (USGS)

2017 ◽  
pp. 135-151 ◽  
Author(s):  
Erin Korris ◽  
Lily Niknami ◽  
Elizabeth McCartney
Keyword(s):  
Data Quality ◽  
Volunteered Geographic Information ◽  
Geographic Information ◽  
Geological Survey ◽  
The U.S

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.

ACCURACY OF BOREHOLE GRAVITY DATA

Geophysics ◽  
1978 ◽  
Vol 43 (3) ◽  
pp. 538-542 ◽  
Author(s):  
James W. Schmoker
Keyword(s):  
Data Quality ◽  
Gravity Data ◽  
Geological Survey ◽  
Gravity Survey ◽  
Vertical Separation ◽  
Elapsed Time ◽  
Gravity Measurements ◽  
Period Data ◽  
The U.S

Repeated subsurface gravity measurements, obtained with the U.S. Geological Survey‐LaCoste and Romberg borehole gravity meter, were studied to determine the accuracy of the borehole gravity data, the dependence of accuracy upon elapsed time and vertical separation, and the precision of bulk densities calculated from borehole gravity measurements. The likelihood of poor interval gravity measurements increases sharply for vertical intervals greater than 150 ft, and increases approximately linearly with increasing time between readings. After a brief warmup period, data quality does not improve with the passage of time from the beginning of the survey. If the stations of a borehole gravity survey are separated by less than 70 ft, and the time between readings is less than 18 minutes, the gravity difference between two points in a borehole can be measured to ±10 μgals. For intervals greater than 20 ft, this is equivalent to a density error of [Formula: see text] or less.

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