Proceedings of the GIS Research UK 18th Annual Conference GISRUK 2010

This volume holds the papers from the 18th annual GIS Research UK (GISRUK). This year the conference, hosted at University College London (UCL), from Wednesday 14 to Friday 16 April 2010. The conference covered the areas of core geographic information science research as well as applications domains such as crime and health and technological developments in LBS and the geoweb. UCL’s research mission as a global university is based around a series of Grand Challenges that affect us all, and these were accommodated in GISRUK 2010. The overarching theme this year was “Global Challenges”, with specific focus on the following themes: * Crime and Place * Environmental Change * Intelligent Transport * Public Health and Epidemiology * Simulation and Modelling * London as a global city * The geoweb and neo-geography * Open GIS and Volunteered Geographic Information * Human-Computer Interaction and GIS Traditionally, GISRUK has provided a platform for early career researchers as well as those with a significant track record of achievement in the area. As such, the conference provides a welcome blend of innovative thinking and mature reflection. GISRUK is the premier academic GIS conference in the UK and we are keen to maintain its outstanding record of achievement in developing GIS in the UK and beyond

Google Maps as cartographic infrastructure: from participatory mapmaking to database maintenance

Google Maps has popularized a model of cartography as platform, in which digital traces are collected through participation, crowdsourcing, or user’s data harvesting and used to constantly improve its mapping service. Based on this capacity, Google Maps has now attained a scale, reach, and social role similar to the existing infrastructures that typically organize cartographic knowledge in society. After describing Google Maps as a configuration relying on characteristics from both platforms and infrastructures, this article investigates what this hybrid configuration means for public participation to spatial knowledge in society. First, this turn to infrastructure for Google has consequences on the status of public participation to mapmaking, which switches from creating content to providing activities of maintenance of its database. Second, if Google Maps “opens up” cartography to participation, it simultaneously recentralizes this participatory knowledge to serve its corporate interests. In this hybrid configuration, cartographic knowledge is therefore simultaneously more participatory and more enclosed

National Web Studies: Mapping Iran Online

This work offers an approach to conceptualizing, demarcating and analyzing a national web. Instead of defining a priori the types of websites to be included in a national web, the approach put forward here makes use of web devices (platforms and engines) that purport to provide (ranked) lists of URLs relevant to a particular country. Once gathered in such a manner, the websites are studied for their properties, following certain of the common measures (such as responsiveness and page age), and repurposing them to speak in terms of the health of a national web: Are sites lively, or neglected? The case study in question is Iran, which is special for the degree of Internet censorship undertaken by the state. Despite the widespread censorship, we have found a highly responsive Iranian web. We also report on the relationship between blockage, responsiveness and freshness, i.e., whether blocked sites are still up, and also whether they have been recently updated. Blocked yet blogging portions of the Iranian web show strong indications of an active Internet censorship circumvention culture. In seeking to answer, additionally, whether censorship has killed content, a textual analysis shows continued use of language considered critical by the regime, thereby indicating a dearth of self-censorship, at least for websites that are recommended by the leading Iranian platform, Balatarin. The study concludes with the implications of the approach put forward for national web studies, including a description of the benefits of a national web health index

Co-producing spatial information with citizens: Understanding practices, preferences, and challenges within government

In today’s era of digital media, collecting and sharing location-based information has become easier and more accessible for many people. This exchange of spatial information, created and shared by the public, is beneficial to different government operations such as disaster management, monitoring of air pollution, and effective planning. With these advancements of technology, as well as practices of information exchange, opportunities are emerging for governments to co-produce spatial information with citizens and acquire current and detailed information following the concept of ‘citizens as sensors’. Though these practices of co-production are becoming more common, there is a gap in understanding how governments are adopting, implementing, and managing co-production practices. Understanding these aspects is crucial, especially to evaluate the benefits, trends, and motivations associated with these practices. This research aims to address this gap, discussed in two main chapters: first, understanding the existing approaches and motivating factors for government co-producing spatial information; second, identifying the existing and potential challenges to implement a project for co-producing spatial information between government and citizens. To meet these research objectives, 18 officials from both local and national levels in North America and Europe were interviewed. The officials are affiliated with projects that are currently co-producing spatial information with citizens, or have potential tools or plans to implement the process. These semi-structured interviews reveal that at the local level, co-production practices involve collecting new information or observations of citizens and are also used to observe citizen preferences and practices. These insights are augmenting the existing operations and service delivery of government organizations with the frequent and detailed contribution of citizens. Furthermore, the role of technology and different partners such as private or research organizations were found to support government to undertake co-production approaches. The results from these interviews also indicate that both organizational and technical challenges prevail for adopting co-production processes. Based on these challenges, a set of best practices are also recommended for government. The overall study outlines the current contexts of government, trends of co-production of spatial information with citizens, and possible best practices for implementation and management of the co-production process

Operating anew: Queering GIS with good enough software [pre-print]

In the last decade, conversations around queering of GIScience emerged. Drawing on literature from feminist and queer critical GIS, with special attention to the under‐examined political economy of GIS, I suggest that the critical project of queering all of GIS, both GIScience and GISystems, requires not just recognition of the labour and lives of queers and research in geographies of sexualities. Based upon a queer feminist political economic critique and evidenced in my teaching critical GIS at two elite liberal arts colleges, I argue that the “status quo” between ESRI and geography as a field must be interrupted. Extending a critical GIS focus beyond data structures and data ethics, I argue that geographic researchers and instructors have a responsibility in queering our choice and production of software, algorithms, and code alike. I call this production and choice of democratic, accessible, and useful software by, for, and about the needs of its users, good enough software

Social Space and Social Media: Analyzing Urban Space with Big Data

This dissertation focuses on the key role that big data can play in minimizing the perceived disconnect between social theory and quantitative methods in the discipline of geography. It takes as its starting point the geographic concept of space, which is conceptualized very differently in social theory versus quantitative methodology. Contrary to this disparity, an examination of the disciplinary history reveals a number of historic precedents and potential pathways for a rapprochement, especially when combined with some of the new possibilities of big data. This dissertation also proposes solutions to two common barriers to the adoption of big data in the social sciences: accessing and collecting such data and, subsequently, meaningful analysis. These methods and the theoretical foundation are combined in three case studies that show the successful integration of a quantitative research methodology with social theories on space. The case studies demonstrate how such an approach can create new and alternative understandings of urban space. In doing so it answers three specific research questions: (1) How can big data facilitate the integration of social theory on space with quantitative research methodology? (2) What are the practical challenges and solutions to moving “beyond the geotag” when utilizing big data in geographical research? (3) How can the quantitative analysis of big data provide new and useful insight in the complex character of social space? More specifically, what insights does such an analysis of relational social space provide about urban mobility and cognitive neighborhoods

Evaluación del tiempo de respuesta de un geoservicio utilizando una base de datos híbrida y distribuida

Web mapping services provide information directly to users and other software programs that can consume and produce information. One of the main challenges this type of service presents is improving its performance. Therefore, in this research, a new geoservice integrated into GeoServer was developed, called GeoToroTur, with an OWS implementation of vector layers that consumes the information from a hybrid and distributed database that was implemented with PostgreSQL and MongoDB, making use of ToroDB for document replication. This geoservice was evaluated by executing geographic and descriptive attribute filter queries. Based on the results, we can conclude that the response time for GeoToroTur is shorter than that for Geoserver.Los servicios de cartografía Web proporcionan información directamente, no sólo a los usuarios, sino también a otros programas de software que pueden consumir y producir información. Uno de los principales retos que presentan este tipo de servicios es mejorar su rendimiento. Por ello, en esta investigación se desarrolló un nuevo geoservicio integrado a GeoServer, denominado GeoToroTur con una implementación OWS de capas vectoriales que consume la información de una base de datos híbrida y distribuida que fue implementada con PostgreSQL y MongoDB haciendo uso de ToroDB para la replicación de documentos. Este geoservicio fue evaluado mediante la ejecución de consultas geográficas y de filtro de atributos descriptivos. Los resultados obtenidos permiten concluir que el geoservicio GeoToroTur tiene un menor tiempo de respuesta que Geoserver

The Impact of Biases in the Crowdsourced Trajectories on the Output of Data Mining Processes

The emergence of the Geoweb has provided an unprecedented capacity for generating and sharing digital content by professional and non- professional participants in the form of crowdsourcing projects, such as OpenStreetMap (OSM) or Wikimapia. Despite the success of such projects, the impacts of the inherent biases within the ‘crowd’ and/or the ‘crowdsourced’ data it produces are not well explored. In this paper we examine the impact of biased trajectory data on the output of spatio-temporal data mining process. To do so, an experiment was conducted. The biases are intentionally added to the input data; i.e. the input trajectories were divided into two sets of training and control datasets but not randomly (as opposed to the data mining procedures). They are divided by time of day and week, weather conditions, contributors’ gender and spatial and temporal density of trajectory in 1km grids. The accuracy of the predictive models are then measured (both for training and control data) and biases gradually moderated to see how the accuracy of the very same model is changing with respect to the biased input data. We show that the same data mining technique yields different results in terms of the nature of the clusters and identified attributes