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Database Fusion for the Comparative Study of Migration Data
DUKE-WILLIAMS, Oliver (email@example.com), University of Leeds, Centre for Computational Geography, Leeds LS2 9JT, U.K.; and BLAKE, M. (firstname.lastname@example.org), University of Adelaide, Key Centre for Social Applications in GIS, 10 Pulteney Street, Adelaide SA 5005, Australia
Key Words: migration, time-series, WWW, visualization, distributed databases, demographic modelling
Internal migration is one of the key processes influencing the population of small areas, together with the natural agents of birth and death. In most post-industrial countries it is both the most significant and the least predictable component of change. The study of migration is often made difficult by the particular characteristics of data collected-alternative datasets may not be directly comparable, data may be of limited extent, or where data does exist, it may do so in sufficiently large volumes so as to make analysis daunting. In addition, both the data themselves, and the results of analysis, can be complex, and require large amounts of metadata to support their explanation.
This paper describes a software system designed to facilitate the comparative study of two time series of migration data, respectively, detailing patterns of internal migration in Australia and the U.K. Both datasets stretch over a concurrent 20-year period (1976-1996), but they are different in conceptual structure: the Australian data describes migration transitions over four inter-Censal 5-year periods, whereas the U.K. data consists of 20 years of migration event data compiled from administrative registers. A database has been designed that contains both source data and data transformed through demographic models, which is intended to generate migration statistics, and measures which can be directly compared, in order to permit the study of features and patterns of change in migration in the two countries, with the primary aim being the elucidation of age-period-cohort relationships in the two sets of data.
The system is constructed from web servers coupled via server-side scripts to RDBMS servers in a manner that is intended to be flexible in terms of hardware and software used, and also to allow servers in the two countries to offer complementary services. The use of a hypertext system allows familiar interfaces to be offered to the user, and as much supporting explanatory text as is needed. The system is designed to support a wide variety of requirements ranging from the extraction of subsets of data to be imported into external analysis packages, and the generation of statistics describing the intensities and effects of migration for selected data to visualization of the data for speculative and exploratory analysis of the data. Migration data is multidimensional, thus, visualization through means such as VRML models allows a rich summary of the data to be presented to the user. This multidimensional nature of the data includes both demographic detail and derived information such as measures of change over time, and also geographic detail. The effects of geographic scale are of considerable importance when studying migration data, and it is presumed that causal factors have differing priorities for local and long distance moves. The system is designed to allow re-aggregation of the migration interaction matrices to suit the users requirements. In addition, many measures of migration intensity and impact rely on distance as a component, and studies have shown that alternative calculations of distance between origins and estimations can have very significant affects on the measures subsequently calculated; the system has been designed to accommodate a variety of methods for calculating distances between locations.
The system described in the paper uses data fusion and integration techniques, together with a variety of presentation approaches, to offer new analytic tools for researchers, allowing large volumes of data to be studied and compared in a manner that was not previously available.