Geographic information of public interest is routinely produced by several public agencies. At the same time, the use of smartphones and other mobile devices generates an increasing amount of unofficial georeferenced data. Although official data have usually higher reliability, it takes longer for governmental organizations to put together relevant datasets and make them available, while the opposite occurs with unofficial data. This work explores the potential for integrating data from official and unofficial sources, as part of a project that aims to verify possible roles for unofficial or crowdsourced data, as replacements or to complement official sources. The article presents a case study with two traffic accident datasets in the city of Belo Horizonte, Brazil. We compare official traffic accident data to unofficial data collected from Waze, a mobile app dedicated to helping users fight traffic congestion. We found that seven percent of accidents reported by official sources have also been reported by users of Waze. Accidents reported only by official sources are concentrated in the central region, while those recorded by Waze are mostly on some major roads all over the city. An analysis on the possible influence of weather is also presented, as well as the identification of accident hotspots from the integrated dataset.
Over the past decade, the public awareness and availability as well as methods for the creation and use of spatial data on the Web have steadily increased. Besides the establishment of governmental Spatial Data Infrastructures (SDIs), numerous volunteered and commercial initiatives had a major impact on that development. Nevertheless, data isolation still poses a major challenge. Whereas the majority of approaches focuses on data provision, means to dynamically link and combine spatial data from distributed, often heterogeneous data sources in an ad hoc manner are still very limited. However, such capabilities are essential to support and enhance information retrieval for comprehensive spatial decision making. To facilitate spatial data fusion in current SDIs, this thesis has two main objectives. First, it focuses on the conceptualization of a service-based fusion process to functionally extend current SDI and to allow for the combination of spatial data from different spatial data services. It mainly addresses the decomposition of the fusion process into well-defined and reusable functional building blocks and their implementation as services, which can be used to dynamically compose meaningful application-specific processing workflows. Moreover, geoprocessing patterns, i.e. service chains that are commonly used to solve certain fusion subtasks, are designed to simplify and automate workflow composition. Second, the thesis deals with the determination, description and exploitation of spatial data relations, which play a decisive role for spatial data fusion. The approach adopted is based on the Linked Data paradigm and therefore bridges SDI and Semantic Web developments. Whereas the original spatial data remains within SDI structures, relations between those sources can be used to infer spatial information by means of Semantic Web standards and software tools. A number of use cases were developed, implemented and evaluated to underpin the proposed concepts. Particular emphasis was put on the use of established open standards to realize an interoperable, transparent and extensible spatial data fusion process and to support the formalized description of spatial data relations. The developed software, which is based on a modular architecture, is available online as open source. It allows for the development and seamless integration of new functionality as well as the use of external data and processing services during workflow composition on the Web. ; Die Entwicklung des Internet im Laufe des letzten Jahrzehnts hat die Verfügbarkeit und öffentliche Wahrnehmung von Geodaten, sowie Möglichkeiten zu deren Erfassung und Nutzung, wesentlich verbessert. Dies liegt sowohl an der Etablierung amtlicher Geodateninfrastrukturen (GDI), als auch an der steigenden Anzahl Communitybasierter und kommerzieller Angebote. Da der Fokus zumeist auf der Bereitstellung von Geodaten liegt, gibt es jedoch kaum Möglichkeiten die Menge an, über das Internet verteilten, Datensätzen ad hoc zu verlinken und zusammenzuführen, was mitunter zur Isolation von Geodatenbeständen führt. Möglichkeiten zu deren Fusion sind allerdings essentiell, um Informationen zur Entscheidungsunterstützung in Bezug auf raum-zeitliche Fragestellungen zu extrahieren. Um eine ad hoc Fusion von Geodaten im Internet zu ermöglichen, behandelt diese Arbeit zwei Themenschwerpunkte. Zunächst wird eine dienstebasierten Umsetzung des Fusionsprozesses konzipiert, um bestehende GDI funktional zu erweitern. Dafür werden wohldefinierte, wiederverwendbare Funktionsblöcke beschrieben und über standardisierte Diensteschnittstellen bereitgestellt. Dies ermöglicht eine dynamische Komposition anwendungsbezogener Fusionsprozesse über das Internet. Des weiteren werden Geoprozessierungspatterns definiert, um populäre und häufig eingesetzte Diensteketten zur Bewältigung bestimmter Teilaufgaben der Geodatenfusion zu beschreiben und die Komposition und Automatisierung von Fusionsprozessen zu vereinfachen. Als zweiten Schwerpunkt beschäftigt sich die Arbeit mit der Frage, wie Relationen zwischen Geodatenbeständen im Internet erstellt, beschrieben und genutzt werden können. Der gewählte Ansatz basiert auf Linked Data Prinzipien und schlägt eine Brücke zwischen diensteorientierten GDI und dem Semantic Web. Während somit Geodaten in bestehenden GDI verbleiben, können Werkzeuge und Standards des Semantic Web genutzt werden, um Informationen aus den ermittelten Geodatenrelationen abzuleiten. Zur Überprüfung der entwickelten Konzepte wurde eine Reihe von Anwendungsfällen konzipiert und mit Hilfe einer prototypischen Implementierung umgesetzt und anschließend evaluiert. Der Schwerpunkt lag dabei auf einer interoperablen, transparenten und erweiterbaren Umsetzung dienstebasierter Fusionsprozesse, sowie einer formalisierten Beschreibung von Datenrelationen, unter Nutzung offener und etablierter Standards. Die Software folgt einer modularen Struktur und ist als Open Source frei verfügbar. Sie erlaubt sowohl die Entwicklung neuer Funktionalität durch Entwickler als auch die Einbindung existierender Daten- und Prozessierungsdienste während der Komposition eines Fusionsprozesses.
Almost 150 years ago a London doctor combined maps of cholera deaths and water pumps to discover the source of a deadly epidemic, and the case has since become an acclaimed use of spatial analysis taught to generations of geography students worldwide. Moving forward to the present day, data mining techniques are now radically changing the way supermarkets think about product placement within their stores, and telephone customers are moving away from their traditional "YellowPages" directories and turning instead to enhanced "YellowMap" products. While these are all very positive examples, on the other hand a recent UK government hearing into the establishment of an underground radioactive waste repository determined not to proceed with this major project after the results of groundwater hydrology modelling were rejected because they could not be validated.
A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information Systems ; The Agenda 2030 challenges the countries to use and produce new spatial data to support the path to Sustainable Development (SD). This requires development and adoption of Spatial Data Infrastructure (SDI), and the production of new relevant spatial data to support implementation, monitoring and reporting the progress on the targets on Sustainable Development Goals (SDGs). The importance of access to spatial data for development and resource management is widely acknowledged worldwide. Unrestricted, reliable and efficient access to accurate, timely, and upto- date spatial data may be achieved through a Spatial Data Infrastructure (SDI). Thus, most developed countries implemented and continue to develop their SDI. The Ecosystem Service (ES) is also crucially for SD and the concept needs to be expressed and communicated effectively to be successfully integrated into decision making. This study assessed the challenges and opportunities on SDI development and analyzed the documents relevant to LUP process and implementation. On the SDI, we identified and characterized through a survey the government institutions producing, sharing, and using spatial data in the country to estimate their potential contribution to the development of the Mozambican SDI. On the integration of ES into LUP, we conducted a review of relevant documents to Mozambique's spatial planning by performing a content analysis based on ES categories. Based on the possible contribution of the institutions producing and using spatial data, we proposed an SDI for Mozambique based on four pillars: i) organizational framework; ii) legal framework; iii) technical framework; and iv) accessibility. The periodical revision of tools and participatory approaches in LUP opens opportunities for integrating ES into LUP processes. This integration could be achieved by establishing a SEA legal framework based on LUP and Environment legal frameworks assisted by a set of common planning tools that consider ES as an additional indicator applied to spatial planning in Mozambique.
Many countries throughout the world believe they can benefit both economically and environmentally from better management of their spatial data assets, enabling them to access and retrieve complete and consistent datasets in an easy and secure way. This has resulted in the development of the Spatial Data Infrastructure (SDI) concept at various political and/or administrative levels. The SDI concept has been represented by different descriptions of its nature, however, currently these demonstrate an overly-simplistic understanding of the concept. The simplicity in existing definitions has been slow to incorporate the concept of an integrated, multilevelled SDI formed from a hierarchy of inter-connected SDIs at corporate, local, state/provincial, national, regional (multi-national) and global (GSDI) levels. Failure to incorporate this multidimensionality, and the dynamic mechanistic and functional roles of the SDI have rendered many descriptions of SDI inadequate to describe the complexity and the dynamics of SDI as it develops,and thus ultimately constrain SDI achieving developmental potential in the future. As a result, the objective of this paper is to demonstrate the fitness and applicability of Hierarchical Spatial Reasoning (HSR) as a theoretical framework to demonstrate the multi-dimensional nature of SDIs. It is argued that by better understanding and demonstrating the nature of an SDI hierarchy, any SDI development can gain support from a wider community of both government and nongovernment data users and providers. The findings presented in this paper build on the authors experiences in Regional SDI (multi-national) development and HSR.
AbstractPolitical units often spatially depend in their policy choices on other units. This also holds in dyadic settings where, as in much of international relations research, analysis focuses on the interaction or relation between a pair or dyad of two political units. Yet, with few exceptions, social scientists have analyzed contagion in monadic datasets only, consisting of individual political units. This article categorizes all possible forms of spatial effect modeling in both undirected and directed dyadic data, where it is possible to distinguish the source and the target of interaction (for example, exporter/importer, aggressor/victim, and so on). This approach enables scholars to formulate and test novel mechanisms of contagion, thus ideally paving the way for studies analyzing spatial dependence between dyads of political units. To illustrate the modeling flexibility gained from an understanding of the full set of specification options for spatial effects in dyadic data, we examine the diffusion of bilateral investment treaties between developed and developing countries, building and extending on Elkins, Guzman, and Simmons's 2006 study. However, we come to different conclusions about the channels through which bilateral investment treaties diffuse. Rather than a capital-importing country being influenced by the total number of BITs signed by other capital importers, as modeled in their original article, we find that a capital-importing country is more likely to sign a BIT with a capital exporter only if other competing capital importers have signed BITs with this very same capital exporter. Similarly, other capital exporters' BITs with a specific capital importer influence an exporter's incentive to agree on a BIT with the very same capital importer.
