An Open Source Geodemographic Classification of Small Areas in the Republic of Ireland

Abstract

Geodemographic classifications have progressed from manual classifications of areas through to complex, highly marketable products used in both the public and private sectors. As their production became commercialized, input variables moved beyond census variables to include other, often not publicly available datasets, and hence the resultant black-box approach increased in sophistication, but was less open to scrutiny. In the UK this was somewhat reversed with the production of the Output Area Classification (OAC) from the 2001 census. As an alternative approach, in this paper we demonstrate the production of a geodemographic classification for the Republic of Ireland, using a different approach to OAC, and extending the ethos of transparency and reproducibility.

Gap analysis in decision support systems for real-estate in the era of the digital earth

“…In a qualitative element, behaviour, socioeconomic, historical, and geographical processes must be considered to identify effective factors and extract relevant spatial indices. (Brunsdon, Charlton, and Rigby 2018). Irish property websites do not use this type of data map, which is further evidence that the existing gap is not caused by data shortages.…”

“…Assuming (Brunsdon, Charlton, and Rigby 2018). Irish property websites do not use this type of data map, which is further evidence that the existing gap is not caused by data shortages.…”

Local and Application-Specific Geodemographics for Data-Led Urban Decision Making

“…From a public sector planning perspective, the proposed template also offers an opportunity for development of more 'on-the-fly' classifications, particularly in-house, potentially utilising more timely and locally bespoke Local Authority and open data. Moreover, more fluid classification development could also instigate a shift away from the convention of naming the classifications and deriving fixed pen portraits of areas, and the challenges and constraints present in such a practice, widely discussed across the academic literature [26,49].…”

“…Treating the public as consumers of public services [20], local government analysts have adopted methodology supported by geodemographic classifications, traditionally used to predict consumer behaviour, to instead highlight the composition of demand for public sector services and resources, and derive insights with which to inform local government policy development [4,25]. Such "social marketing initiatives" [26] have helped local policy-makers to gauge social attitudes, and more intelligently develop strategies for service delivery and target the allocation of public sector services and resources [24].…”

“…This could result in a loss of critical, locally relevant information, particularly in small-area geographies that diverge from the national picture, and impose restrictions on the ability to derive the level of local context which is required for successful targeted application in the public sector. Particularly, this is noted as being a potentially more acute problem in large cities with distinct make-up [14,26], such as Leeds, and as such, recommendations to explore the development of more local, place-specific classifications which are designed to more appropriately reflect locally specific phenomena are growing [14,18,22]. In addition, whilst place-specific alternatives have the potential to offer more nuanced local classifications, the more granular and focused extent simultaneously introduces the possibility of including more novel and bespoke local data into such classification development, particularly data that are only available at the local level and, as such, have been excluded from inclusion in the national-level classifications, which have necessitated consistent data across the extent.…”