4 research outputs found

    A new trajectory for spatial data infrastructure evolution in the developing world

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    Includes abstract.Includes bibliographical references (leaves 107-113).Spatial Data is a key resource in the development of cities. There is a lot of socio-economic potential that is locked away in spatial data holdings and this potential is unlocked by making the datasets widely available for use. Spatial Data Infrastructures (SDIs) have served this primary purpose; to make data accessible through the use of web based technologies. However, SDIs have not had their anticipated impact at local levels of governance. They have traditionally served as platforms that facilitate access to raw spatial datasets. They have not fully facilitated for the use of these datasets and therefore have attracted minimal attention from decision makers and users. This research suggests a new trajectory for SDI evolution; a trajectory that will allow them to evolve into more relevant platforms for confronting the urban crisis in developing nations and thereby ensuring that they have the societal impact that they are intended to. The research explores the characteristics of the mainstream efforts to counter urban crises in the developing world to determine how the new SDI should be re-conceptualised to more adequately assist in responding to the urban crisis. This leads to the incorporation of Evidence Based Practice (EBP) into SDI through the use of urban indicators and knowledge creation processes to reflect on the pressing societal issues. From the new SDI concept, an architectural design is implemented as a “proof of concept”. At the heart of this new concept is the SDIs ability to provide access to more than just raw spatial datasets but useful information products that are based on these data. This proves that EBP can be incorporated into SDI to make them more efficient in responding to the urban problems in developing nation and consequently more relevant Information Infrastructures for urban decision makers

    Making Sense of Document Collections with Map-Based Visualizations

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    As map-based visualizations of documents become more ubiquitous, there is a greater need for them to support intellectual and creative high-level cognitive activities with collections of non-cartographic materials -- documents. This dissertation concerns the conceptualization of map-based visualizations as tools for sensemaking and collection understanding. As such, map-based visualizations would help people use georeferenced documents to develop understanding, gain insight, discover knowledge, and construct meaning. This dissertation explores the role of graphical representations (such as maps, Kohonen maps, pie charts, and other) and interactions with them for developing map-based visualizations capable of facilitating sensemaking activities such as collection understanding. While graphical representations make document collections more perceptually and cognitively accessible, interactions allow users to adapt representations to users’ contextual needs. By interacting with representations of documents or collections and being able to construct representations of their own, people are better able to make sense of information, comprehend complex structures, and integrate new information into their existing mental models. In sum, representations and interactions may reduce cognitive load and consequently expedite the overall time necessary for completion of sensemaking activities, which typically take much time to accomplish. The dissertation proceeds in three phases. The first phase develops a conceptual framework for translating ontological properties of collections to representations and for supporting visual tasks by means of graphical representations. The second phase concerns the cognitive benefits of interaction. It conceptualizes how interactions can help people during complex sensemaking activities. Although the interactions are explained on the example of a prototype built with Google Maps, they are independent iv of Google Maps and can be applicable to various other technologies. The third phase evaluates the utility, analytical capabilities and usability of the additional representations when users interact with a visualization prototype – VIsual COLlection EXplorer. The findings suggest that additional representations can enhance understanding of map-based visualizations of library collections: specifically, they can allow users to see trends, gaps, and patterns in ontological properties of collections

    Localizing the media, locating ourselves: a critical comparative analysis of socio-spatial sorting in locative media platforms (Google AND Flickr 2009-2011)

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    In this thesis I explore media geocoding (i.e., geotagging or georeferencing), the process of inscribing the media with geographic information. A process that enables distinct forms of producing, storing, and distributing information based on location. Historically, geographic information technologies have served a biopolitical function producing knowledge of populations. In their current guise as locative media platforms, these systems build rich databases of places facilitated by user-generated geocoded media. These geoindexes render places, and users of these services, this thesis argues, subject to novel forms of computational modelling and economic capture. Thus, the possibility of tying information, people and objects to location sets the conditions to the emergence of new communicative practices as well as new forms of governmentality (management of populations). This project is an attempt to develop an understanding of the socio-economic forces and media regimes structuring contemporary forms of location-aware communication, by carrying out a comparative analysis of two of the main current location-enabled platforms: Google and Flickr. Drawing from the medium-specific approach to media analysis characteristic of the subfield of Software Studies, together with the methodological apparatus of Cultural Analytics (data mining and visualization methods), the thesis focuses on examining how social space is coded and computed in these systems. In particular, it looks at the databases’ underlying ontologies supporting the platforms' geocoding capabilities and their respective algorithmic logics. In the final analysis the thesis argues that the way social space is translated in the form of POIs (Points of Interest) and business-biased categorizations, as well as the geodemographical ordering underpinning the way it is computed, are pivotal if we were to understand what kind of socio-spatial relations are actualized in these systems, and what modalities of governing urban mobility are enabled

    Google's Geospatial Organizing Principle

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