ABSTRACT
Of all the stumbling blocks in indicator research, it is clear that it is ‘data, data and data’ which makes it or breaks it. Data is both a requirement and a problem to indicator development. Without the basic ingredient of good-quality datasets, it is simply not possible to produce reliable and robust indicators, though in some cases innovative methodology and analytical techniques can help to ameliorate and overcome some of the problems. The rapid development of information technologies, notably the application of geographical information systems, the affordability of personal computers and the development of spreadsheets, database managers and various user-friendly statistical packages has largely enhanced our information-handling capacity in the last twenty years. The real concern is, however, how to capture reliable and good-quality information efficiently and effectively to provide the basic ingredient for analysis. Following the recommendations of the Better Information Report (SEU 2000), significant development work on neighbourhood and smallarea based statistics has been carried out by the ONS and other government departments. To start with, key statistics are now much more organised and centrally located in the neighbourhood statistics website of the ONS. With the advent of Internet technology and the World Wide Web browser, many government departments also publish their routinely collected statistics on their websites. While this progress in improving statistics is encouraging, there are still plenty of challenges ahead. This chapter, therefore, devotes attention to examine issues surrounding data availability and data quality, and to identify the inherent problems in current public data compilation practice. It also explores how methodological research interacts with the policy agenda to overcome some of these challenges. The discussion is augmented by the experience gained from compiling data for two indicators projects: local economic development indicators study (see Wong 2002a) and town and city indicators database research (see Wong et al. 2004).
