Natural Earth is a public domain map dataset available at 1:10m, 1:50m, and 1:110 million scales. Featuring tightly integrated vector and raster data, with Natural Earth you can make a variety of visually pleasing, well-crafted maps with cartography or GIS software.
Project Detail - Digital Preservation (Library of Congress). The GeoMAPP project is exploring ways to expand the capabilities of state governments to provide long-term access to geospatial data. The project is bringing together geospatial and archival staff in multiple states to identify, preserve, and make available temporal and superseded digital geospatial data with ongoing value. A key approach will include testing a geographically dispersed content-exchange network for the replication of state and local geospatial data among several states to promote preservation and access.
The Open Geospatial Consortium, Inc.® (OGC) is a non-profit, international, voluntary consensus standards organization that is leading the development of standards for geospatial and location based services.
OpenLayers is a pure JavaScript library for displaying map data in most modern web browsers, with no server-side dependencies. OpenLayers implements a (still-developing) JavaScript API for building rich web-based geographic applications, similar to the Go
A. Geronimus, J. Bound, and L. Neidert. Journal of the American Statistical Association, 91 (434):
529--537(June 1996)Investigators of social differentials in health outcomes commonly augment incomplete microdata by appending socioeconomic characteristics of residential areas (such as median income in a zip code) to proxy for individual characteristics. But little empirical attention has been paid to how well this aggregate information serves as a proxy for the individual characteristics of interest. We build on recent work addressing the biases inherent in proxies and consider two health-related examples within a statistical framework that illuminates the nature and sources of biases. Data from the Panel Study of Income Dynamics and the National Maternal and Infant Health Survey are linked to census data. We assess the validity of using the aggregate census information as a proxy for individual information when estimating main effects and when controlling for potential confounding between socioeconomic and sociodemographic factors in measures of general health status and infant mortality. We find a general, but not universal, tendency for aggregate proxies to exaggerate the effects of micro-level variables and to do more poorly than micro-level variables at controlling for confounding. The magnitude and direction of these biases vary across samples, however. Our statistical framework and empirical findings suggest the difficulties in and limits to interpreting proxies derived from aggregate census data as if they were micro-level variables. The statistical framework that we outline for our study of health outcomes should be generally applicable to other situations where researchers have merged aggregate data with microdata samples..
E. Valle, H. Qasim, and I. Celino. Proceedings of 1st International Workshop on Pervasive Web Mapping, Geoprocessing and Services (WebMGS 2010), (2010)
S. Ahern, M. Naaman, R. Nair, and J. Yang. JCDL '07: Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries, page 1-10. New York, NY, USA, ACM, (2007)
J. Owens, M. Yuan, M. Wachowicz, V. Kantabutra, E. Jr., D. Ames, and A. Gangemi. National Endowment for the Humanities Workshop Visualizing the Past: Tools and Techniques for Understanding Historical Processes, University of Richmond, Virginia, USA, volume 188 of Frontiers in Artificial Intelligence and Applications, IOS Press, (2009)
A. Soheili, V. Kalogeraki, and D. Gunopulos. GIS '05: Proceedings of the 13th annual ACM international workshop on Geographic information systems, page 61--70. New York, NY, USA, ACM Press, (2005)