Welcome: GEOgraphical REFERencing resources for social scientists  

  This ESRC project involves the creation and deployment of a digital library of learning resources targeted at social scientists whose primary discipline is not geography, but whose research requires them to use and link geographically referenced data. Geographical location provides a key mechanism for linkage between sources, for example between individual-level survey responses or health records and existing secondary data such as that provided by the census of population. Further examples include sets of data for incompatible areal units and primary data collection using the global positioning system. More

Objectives

This web resource was the end-product of a project which was a continuation and development of the first Geo-Refer RDI award. The Geo-Refer projects addressed frequently-encountered challenges such as linking and mapping datasets with one or more geographical reference codes such as postcodes, census and administrative area codes. The aim of the second project was to further develop the Geo-Refer online training resources and in particular to customise the resources and offer them to researchers in specific areas by working with partner organizations such as the ESRC Census programme and SASPAC software consortium. Geographical referencing challenges particularly face those working with census datasets and in planning and local government settings, hence these were major foci of the project. Training was also provided to a range of young social science researchers who were not geographers and therefore did not have previous experience of geographical information systems. An initial aim had been to develop resources specifically in collaboration with a health research group but health researchers attended each of the other events. Two workshops were run for census audiences; for a local government/SASPAC user audience; to young researchers at the annual autumn school of the ESRC National Centre for Research Methods and to a general research audience at the ESRC Research Methods Festival in 2008. 

Authors

The original authors of the Geo-Refer resource were David Martin Samantha Cockings and Samuel Leung at the School of Geography, University of Southampton.

 

 

Original Project

The original work was undertaken as part of two awards funded under ESRC's Researcher Development Initiative. These were "Geo-Refer: Georeferencing Resources for Social Scientists" (PTA-035-25-0029, 1 Feb 2006-31 Jan 2008) and "Geo-Refer 2: Meeting Community-Speicific Research Needs in Geographical Referencing" (RES-035-25-0047, 1 Feb 2008-31 Dec 2008). The projects involved development of online learning materials designed to help social scientists understand geographical referencing issues such as geographical data linkage and mapping. The online materials were designed to be reusable, updatable, and conform to the main educational technology interoperability standards. In addition to authoring these online resources, the project team also delivered geographical referencing workshops in various locations to assist researchers from a range of disciplines with their georeferencing tasks. Workshop presentations are included within the online resource. For more details please see 

Quick Summary

A set of modular online learning resources covering geographical data linkage and mapping, mainly focused on the UK and dealing with census, postcode and administrative geographies, deprivation indicators and other major geographically-referenced datasets. The resources are highly modular and organized into four classes: concepts, methodology, data and exemplar applications. The materials demonstrate the use of common office software, ArcGIS and SASPAC. In addition to browsing through the detailed content, the site features a user profile form which assists users to profile their own learning needs and returns customised tutorial sequences through the four classes of resources relevant to their own work, accompanied by relevant examples. 

Classification

Use of Administrative Sources :: Observation :: Data Collection (general) :: Sampling :: Advanced Technologies ::

ReStoration date

This web resource has been restored on:2008-05-12

Last updated:

This web resource has been updated on:2012-06-01