The present study provides a simplified framework verifying the degree of coverage and completeness of settlement maps derived from the OpenStreetMap (OSM) database at the national scale, with a possible use in official statistics. Measuring the completeness of the objects (i.e., buildings) derived from OpenStreetMap database supports its potential use in building/population censuses and other diachronic surveys, as well as administrative sources such as the register of building permits and land-use cadasters. A series of measurements at different scales are proposed and tested for Italy, in line with earlier studies. While recognizing the potential of the OpenStreetMap database for official statistics, the present work underlines the urgent need of an additional (spatially explicit) analysis overcoming the data heterogeneity and sub-optimal coverage of the OSM information source.

Geographic data quality is a complex issue requiring continuous operational improvements. Considering this to be one of the most topical research and technical issues in official statistics and environmental monitoring, this study re-connects the operational dimension of ‘geographic data quality’ with the broader issue of monitoring the quality of official statistics. By estimating the accuracy of public (spatially explicit) data, this study illustrates an operational framework with an exploratory exercise in estimating the geographic data quality characteristic of a specific information source within the official statistical system (i.e., building registry) in a given European country, namely, Italy. The results of this exercise provide a paradigmatic example of profound innovation in the activities of statistical services in Europe and specifically the Italian National Statistical Institute (Istat), transitioning from independent (and poorly connected) field surveys to an integrated system of registries. Since several studies are based on spatially explicit survey units, it is essential to estimate the quality of geographical data, especially those derived from information sources where space is topical information, such as (local, regional, or national) building registers. Thanks to the results of an empirical exercise applied to Italian building registers, the present article will discuss the issue of data accuracy, considered the main issue related to monitoring geographic data quality, from an official statistics’ perspective. Statistical indicators will be proposed for the assessment of systematic and random errors of spatially explicit measures, possibly enabling a quali-quantitative improvement in the semantic content of building registers that address the inherent requirements of official statistics. Such indicators have some positive implications for the entire system of official statistics in Italy and, for generalization, within the European Statistical System.

‘Marginal’ urban settlements can be assumed as specific locations within a metropolitan area that are unable to attract (incoming) commuter flows. The official statistical system of Italy (headed by the National Statistical Institute, Istat) introduced a summary index of ‘urban marginality’ following the original definition proposed by a national, ad hoc Parliamentary Committee and assessing together social vulnerability and material deprivation at a sufficiently detailed spatial scale. More specifically, the index—intended as a composite indicator of territorial marginality with a normative meaning—was calculated as a specific elaboration of the commuting matrix derived from decadal population censuses considering a municipal-level resolution. In this perspective, the ability of a given municipality to attract bigger (or smaller) inflows than outflows, indicates a specific demand for services allowing the identification of (respectively) central places and peripheral locations. Starting from the index described above, our study generalizes this approach to a wider background context, investigating the roles of spatial scale and geographical coverage. By providing a novel (functional) approach to centrality and periphery, we analyzed commuting patterns at a submunicipal level, indirectly focusing on patterns and processes of local development. A spatial clustering of a standardized polarization index quantifying home-to-work daily travels delineated submunicipal (homogeneous) areas taken as sinks (centers) or sources (peripheries) of commuter flows. The empirical results also demonstrate that spatial neighborhoods (i.e., contiguity order) did not affect the functional classification of a given territory as derived from spatial clustering. Our approach provides a dynamic and innovative interpretation of metropolitan hierarchy using simplified data derived from population censuses.

Statistical information related to Climate Change and Sustainability ask for an integrated approach related to economic, social, environmental and institutional goals, from global to local and from local to global to leave no one behind. The statistical measures are useful to build a common language crucial for monitoring. The Register of places is a complex system with several components. The challenge is the production of spatial information able to respond to the heightened need of detail statistical data. The construction process is complex and faces several issues first of all the very high number of objects involved and the integration of components stemming from different sources independent from each other. The final integrated product allows the possibility of geo-referencing information for flexible outputs. This information has the potential to increase statistical measures and analyses related to Climate Change and sustainability.