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The geography of the cultural sector concerns the location of producers, consumers, and venues of the Cultural and Creative Industries (CCIs) to answer questions about their development and dynamics. Considering the case of the UK museums, we use national data from the Mapping Museums project to study their geodemographic context at the Local Authority District level. Across the UK, we observe the distribution of different types of museums according to their governance type and subject matter in areas belonging to different geodemographic categories. Both in terms of simple counts and divergence from expected values, different types of museums show vastly different distributions and trends, reflecting the variety of the sector.

The city of Leicester (UK) has seen large socio-demographic changes over the past century, gaining complex social, economic and multicultural geographies. Such changes are reflected in the data collected through the census and can be illustrated by developing a temporal geodemographic classification. This paper presents the results of a Master's dissertation project aimed at developing a temporal geodemographic classification for Leicester's urban area, including the Leicester Local Authority District, as well as the Oadby and Wigston Local Authority District, analysing its changing socio-economic structure over three censuses.

Films are deeply geographical. Externally, they are produced in places, across increasingly complex and shifting global networks that connect organisations, cities, professionals, and equipment. Internally, their imagined geographies are set in either real or fictional places, and refer to their social, political, and cultural facets. In this study, we adopt a cultural analytics approach to commence an investigation of the spatial dimension of films, focussing on toponyms in film plots. Using geoparsing, we extract toponyms from about 42,000 film plots from Wikipedia and we analyse their spatial distribution by country. We then consider the relationship between a film’s country of origin and the plot toponyms, charting the flows from places where films are produced to the geographies evoked in their stories.

This paper investigates the effects of the 2020 California wildfires on Volunteer Geographical Information (VGI). Previous research on VGI has frequently focused on its quality and spatial and temporal variability. This study implements a series of statistical analysis, including spatial autocorrelational and fuzzy clustering, to identify any spatial temporal changes in cases studies both involving and not involving wildfire to investigates to what extent changes might be a result of wildfires. The analysis shows similar spatial temporal changes of the VGI in both the wildfire and non-wildfire sites, concluding that wildfires do not directly impact VGI. &nbsp

This paper contributes to the working definition of natural points of interest (NPOI). We combine a theory-driven approach exploring existing definitions of points of interest and natural features and a data-driven approach in which we systematically assess datapoints from three separate data sources, proposing a set of criteria for the classification of natural points of interest.

Spatial autocorrelation statistics have a long-standing history being used by geographers to determine whether identifiable spatial patterns exist in data. However, existing research has identified that solely relying on p-values can be problematic when working with large datasets. This paper introduces a generalised model that can capture geographical data’s spatial patterns using a graph convolutional network (GCN). The preliminary analysis demonstrates that GCN can capture the localities among areas in local-scale datasets by processing the data features and the spatial information separately into the graph network.

Wikipedia is one of the largest platforms based on the concept of asynchronous, distributed, collaborative work. A systematic collaborative exploration and assessment of Wikipedia content and coverage is however still largely missing. On the one hand editors routinely perform quality and coverage control of individual articles, while on the other hand academic research on Wikipedia is mostly focused on global issues, and only sporadically on local assessment. In this paper, we argue that collaborative visualizations have the potential to fill this gap, affording editors to collaboratively explore and analyse patterns in Wikipedia content, at different scales. We illustrate how a collaborative visualization service can be an effective tool for editors to create, edit, and discuss public visualizations of Wikipedia data. Combined with the large Wikipedia user-base, and its diverse local knowledge, this could result in a large-scale collection of evidence for critique and activism, and the potential to enhance the quantity and quality of Wikipedia content.

The relevance of geographic information has become an emerging problem in geographic information science due to an enormous increase in volumes of data at high spatial, temporal, and semantic resolution, because of ever faster rates of new data capturing. At the same time, it is not clear whether the concept of relevance developed in information science and implemented for document-based information retrieval can be directly applied to this new, highly dynamic setting. In this study, we analyze the criteria users apply when judging the relevance of geographic entities in a given mobile usage context. Two different experiments have been set up in order to gather users' opinions on a set of possible criteria, and their relevance judgements in a given scenario. The importance ascribed to the criteria in both experiments clearly implies that a new concept of relevance is required when dealing with geographic entities instead of digital documents. This new concept of ‘Geographic Relevance’ is highly dependent on personal mobility and user's activity, whose understanding may in turn be refined by the assimilation of ‘Geographic Relevance’ itself.