Edited by Robert Stimson
Adequate and appropriate data lies at the heart of much social science and is especially important for spatially informed social science where the ability to generate models and draw inferences about complex phenomena is contingent upon adequate and reliable data. Both primary and secondary data sources are critical for the social sciences generally and spatially informed social science in particular. It is therefore essential to develop a full understanding of the advantages and disadvantages of each data source. Debates around the use and analysis of primary and secondary data sources have a long history, with the quantitative revolution that reshaped the discipline of geography in the 1960s and 1970s generating a new renewed focus on the nature and sources of data, the relative strengths and weaknesses of each data type, and the conventions for their use and presentation. Indeed, such issues were at the foreground of both teaching and research (see, e.g., Daugherty, 1974; McCullagh, 1974; Davis, 1974). Such issues continue to attract the attention of social scientists generally (Walter, 2010) with respect to both theoretically informed (Blaikie, 2010) and applied (Maher and Burke, 1991) social science research. Clearly this is a debate and set of concerns that has retained its centrality with the social sciences, even as the range of perspectives on the nature of data and ‘knowledge’ has broadened over time (Jacobs, 2010).
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