In dieser Bachelorarbeit wird eine Beispiel-E-Learning-Lektion zum Import von GPS Daten in die Kartenherstellungssoftware OCAD erstellt. Dabei liegt im theoretischen Teil der Hauptschwerpunkt auf nutzergenerierten Daten (Volunteered Geographic Infor-mation; kurz: VGI). Nach einer kurzen, allgemeinen Einführung wird auf die Bedeutung der Kartographie im Zusammenhang mit VGI eingegangen. Der zweite Teil beinhaltet Didaktik mit Schwerpunkt E-Learning. Dazu werden das Goal Based Scenario Modell und das Cognitive Apprenticeship Modell kurz vorgestellt und anschließend das Projekt GITTA mit der enthaltenen ECLASS-Struktur näher erklärt. Den immer wichtiger werdenden Content Management Systemen (CMS) widmet sich der dritte Theorieteil. Für die Realisierung der zu erstellenden Lektion wird das Open-Source CMS Joomla! ausführlicher erläutert. Die Implementierung beschreibt die Umsetzung der E-Leraning-Lektion mittels Joomla! und die Nutzung des ECLASS-Modells. Bevor auf die Vorgehensweise eingegangen wird, enthält der Implementierungsteil die Erstellung eines groben Gesamtkonzeptes für eine komplette E-Leraning-Anwendung zu OCAD mit entsprechenden Erläuterungen. Anschließend folgen eine Zusammenfassung und ein Ausblick über die Weiterführung der E-Learning-Anwendung.

Submitted by Lucienne Costa (lucienneferreira@ufcg.edu.br) on 2018-08-30T17:53:33Z No. of bitstreams: 1 IGOR GOMES DE MENESES CRUZ – DISSERTAÇÃO (PPGCC) 2017.pdf: 3611712 bytes, checksum: 52e214b1e983514ff07991410708e671 (MD5) / Made available in DSpace on 2018-08-30T17:53:33Z (GMT). No. of bitstreams: 1 IGOR GOMES DE MENESES CRUZ – DISSERTAÇÃO (PPGCC) 2017.pdf: 3611712 bytes, checksum: 52e214b1e983514ff07991410708e671 (MD5) Previous issue date: 2017-07 / Indivíduos deficientes visuais, apesar de possuírem grande capacidade de adaptação por meio de outros sentidos, ainda apresentam algumas limitações, como, por exemplo, a locomoção segura. A navegação humana é um comportamento muito complexo, que depende principalmente da visão. Portanto, para uma pessoa com deficiência visual, a locomoção se torna uma tarefa muito difícil, especialmente em algumas situações, como em ambientes desconhecidos ou próximo ao tráfego urbano. Aplicativos de navegação, baseados em mapas, proporcionam uma ajuda significativa em questões de orientação, mobilidade e apoio à localização, bem como a estimativa das direções e distâncias. Porém, estes usuários ainda encontram grandes dificuldades no acesso à informação espacial, já que a interação com este tipo de aplicação é realizada, principalmente, por meio da visão. Assim, na presente pesquisa, foi realizado um estudo com deficientes visuais, visando desenvolver uma solução acessível colaborativa de mobilidade para entender as principais necessidades, em termos de locomoção, desses usuários. A solução proposta inclui uma aplicação móvel com mapas acessíveis e com efeitos sonoros, capaz de ajudar na mobilidade deste tipo de usuário, levando em consideração possíveis obstáculos em seus trajetos e descrevendo o ambiente, em termos de Pontos de Interesse (POI), ao seu redor e em torno de uma direção específica indicada pelo usuário. Para alcançar este objetivo, foi utilizada a técnica de Informação Geográfica Voluntária (Volunteered Geographic Information - VGI), que tem se mostrado eficaz e de baixo custo para obtenção de informação geográfica. Foi conduzida uma avaliação experimental para avaliar a qualidade dos dados obtidos de forma colaborativa, bem como experimentos envolvendo participantes voluntários, a fim de avaliar se a solução proposta é satisfatória para mitigar os problemas relacionados à navegação da população deficiente visual. Por fim, os resultados obtidos nos experimentos se mostraram encorajadores, demonstrando que a solução proposta pode ser satisfatória para usuários deficientes visuais. / Although visually impaired individuals have great ability to adapt to a variety of situations through other senses, they still face some limitations, such as safe locomotion. Human navigation is a complex behavior, which depends mainly on vision. Therefore, for a visually impaired person, locomotion is a difficult task, especially in some situations, such as in unfamiliar surroundings or close to urban traffic. Map-based navigation applications provide significant help with guidance, mobility and location support, as well as with estimation of directions and distances. However, this kind of users still find great difficulties in accessing spatial information, since the interaction with this type of application is performed, mainly, through the vision. Thus, a study was carried out with the visually impaired to understand their main mobility needs, aiming at developing an accessible and collaborative mobility solution. The proposed solution includes a mobile application with accessible maps and sound effects, able to help the mobility of this type of users, taking into account possible obstacles in their paths and describing the environment in terms of Points of Interest (POI) around them and around a specific direction indicated by the user. In order to reach this goal, the Volunteered Geographic Information (VGI) technique was used, since it has been shown to be efficient and low cost in obtaining geographic information. An experimental evaluation was conducted to evaluate the quality of the data obtained collaboratively, as well as experiments involving volunteer participants, in order to evaluate whether the proposed solution is satisfactory to mitigate the problems related to navigation of the visually impaired population. Finally, the results obtained in the experiments were encouraging, demonstrating that the proposed solution may be satisfactory for visually impaired users.

Desastres naturais são fenômenos que causam grandes danos às pessoas em áreas urbanas e rurais, motivando medidas de prevenção e reação. Se múltiplas fontes de informação são consideradas, tais medidas podem ser mais assertivas e efetivas. Porém, a integração de dados heterogêneos ainda impõe desafios devido às diferenças em suas estruturas. Para preencher essa lacuna, esta pesquisa apresenta uma arquitetura orientada a serviços, como parte de uma plataforma geoespacial para gestão de risco de desastres, a qual visa apoiar a integração de dados de sensores e de voluntários relacionados a inundações. Como resultado, a composição dos serviços descritos pelos componentes arquiteturais possibilita a integração entre dados de sensores e voluntários usando algoritmos diferentes de forma flexível e automática. / Natural disasters are phenomena that can cause great damage to people in urban and rural areas, thus motivating preventive and reactive measures. If multiple sources of information are considered, such measures can be more assertive and effective. However, the integration of heterogeneous data still poses challenges due to the differences in their structures. To fill this gap, this paper presents a service-oriented architecture, as part of a geospatial platform for disaster risk management, which aims to support the integration of sensor data streams and Volunteered Geographic Information (VGI) related to floods. The architectural components are implemented as Web services, and their composition enables the integration between sensor data and VGI using several algorithms in a flexible and automated manner. As result, the composition of the services described by the architectural components allows the integration of sensor and volunteered data by using diverse algorithms in a flexible and automated way.

Context: Accurate decision-making requires updated and precise information to establish the reality of an overall situation. New data sources (e.g., wearable technologies) have been increasing the amount of available and useful data, which is now called big data. This has a great potential for transforming the entire business process and improving the accuracy of decisions. In this context, disaster management represents an interesting scenario that relies on big data to enhance decision-making. This is because it must cope with data provided not only by traditional sources (e.g., stationary sensors) but also by emerging sources - for instance, information shared by local volunteers, i.e., volunteered geographic information (VGI). When combined, these data sources can be regarded as large in volume, with different velocities, and a variety of formats. Furthermore, an analysis is required to confirm their veracity is required since these data sources are disconnected and prone to various errors. These are the 4Vs that characterize big data. Gap: However, although all these data open up further opportunities, their huge volume, together with an inappropriate data integration and unsuitable visualization, can result in information being overlooked by decision-makers. This problem arises because the integration of the available data is hampered by the intrinsic heterogeneity of their features (e.g., their occurrence in different formats). When integrated, this information also often fails to reach the decision-makers in a suitable way (e.g., in appropriate visualization formats). Moreover, there is not a clear understanding of the decision-makers needs or how the available data can meet these needs. Objective: In light of this, this thesis presents an approach for improving decision-making with heterogeneous geospatial big data based on spatial decision support systems and volunteered geographic information in disaster management. Methods: Systematic mapping studies were conducted to identify gaps in research studies with regard to the use of volunteered information and spatial decision support systems in disaster management. On the basis of these studies, two design science projects were carried out. The first of these aimed at defining the elements that are essential for ensuring the integration of heterogeneous data, whereas the second project aimed at obtaining a better understanding of decision-makers needs. A cross-organizational action research project was also conducted to define the design principles that should be observed for a spatial decision support system to effectively support decision-making with heterogeneous geospatial big data. A series of empirical case studies was undertaken to evaluate the outcomes of these projects. Results: The overall approach thus consists of the three significant outcomes that were derived from these projects. The first outcome was the conceptual architecture that defines the integration of heterogeneous data sources. The second outcome was a model-based framework that describes the connection of decision-making with appropriate data sources. The third outcome is based on the framework and comprises a set of design principles for guiding the development of spatial decision support systems for decision-making with heterogeneous geospatial big data. Conclusion: This thesis has made a useful contribution to both practice and research. In short, it defines ways of integrating heterogeneous data sources, provides a better understanding of decision-makers needs, and supports the development of a spatial decision support system to effectively assist decision-making with heterogeneous geospatial big data. / Contexto: Uma tomada de decisão precisa exige informações mais precisas e atualizadas para estabelecer a realidade da situação geral. Novas fontes de dados (e.g, tecnologias vestíveis) tem aumentado a quantidade de dados úteis disponíveis, que agora é chamado de big data. Isso tem grande potencial para transformar todo o processo de negócio e melhorar a precisão na tomada de decisão. Neste contexto, a gestão de desastres representa um interessante cenário que depende de big data para aprimorar a tomada de decisão. Isso porque, ela tem que lidar com dados fornecidos não apenas por fontes tradicionais (e.g., sensores estáticos), mas também por fontes emergentes por exemplo, informações compartilhadas por voluntários locais, i.e., as informações geográficas de voluntários (VGI). Quando combinadas, estas fontes de dados podem ser consideradas grandes em volume, com diferentes velocidades e uma variedade de formatos. Além disso, uma análise com relação à sua veracidade é necessaria uma vez que estas fontes de dados são desconectadas e propensas à erros. Estes são os 4Vs que caracterizam big data. Problema: No entanto, embora todos estes dados abrem novas oportunidades, seu grande volume em conjunto com uma integração inapropriada e uma visualização inadequada, podem tornar as informações ignoradas por tomadores de decisão. Isso ocorre, pois, a integração dos dados disponíveis torna-se complicada devido a heterogeneidade intrínseca nas suas características (e.g., dados em formatos diferentes). Quando integradas, estas informações frequentemente também não chegam aos tomadores de decisão em uma condição apropriada (por exemplo, no formato de visualização adequado). Além disso, não existe uma clara compreensão sobre as necessidades dos tomadores de decisão ou sobre como os dados disponíveis podem ser usados para atender essas necessidades. Objetivo: Dessa forma, esta tese de doutorado apresenta uma abordagem para melhorar a tomada de decisões com grande volume de dados espaciais heterogêneos baseada em sistemas de suporte à decisão espacial e informações geográficas de voluntários na gestão de desastres. Métodos: Mapeamentos sistemáticos foram conduzidos para identificar lacunas de pesquisa no uso de dados voluntários e sistemas de suporte à decisão na gestão de desastres. Com base nestes estudos, dois projetos de design science foram conduzidos. O primeiro deles buscou definir elementos essências para entender a integração de dados heterogêneos, enquanto o segundo projeto buscou fornecer um melhor entendimento das necessidades dos tomadores de decisão. Também foi conduzido um projeto de pesquisa-ação interinstitucional para definir princípios de projeto que deveriam ser observados para um sistema de suporte à decisão espacial ser efetivo no apoio a tomada de decisão com grande volume de dados espaciais heterogêneos. Uma série de estudos de caso empíricos foram conduzidos para avaliar os resultados destes projetos. Resultados: A abordagem geral então é composta pelos três resultados significantes que foram derivados destes projetos. Em primeiro lugar, uma arquitetura conceitual que especifica a integração de fontes de dados heterogêneas. O segundo elemento é uma estrutura baseada em modelo que descreve a conexão entre a tomada de decisão com as fontes de dados mais adequadas. Com base nesta estrutura, o terceiro elemento consiste em um conjunto de princípios de design que guiam o desenvolvimento de um sistema de suporte à decisão espacial para tomada de decisão com grande volume de dados espaciais heterogêneos. Conclusão: Esta tese de doutorado realizou importantes contribuições para a prática e pesquisa. Em resumo, ela define formas para integrar fontes de dados heterogêneos, fornece uma melhor compreensão sobre as necessidades dos tomadores de decisão e ajuda no desenvolvimento de sistemas de suporte à decisão espacial para tomada de decisão com grande volume de dados espaciais heterogêneos.

In dieser Bachelorarbeit wird eine Beispiel-E-Learning-Lektion zum Import von GPS Daten in die Kartenherstellungssoftware OCAD erstellt. Dabei liegt im theoretischen Teil der Hauptschwerpunkt auf nutzergenerierten Daten (Volunteered Geographic Infor-mation; kurz: VGI). Nach einer kurzen, allgemeinen Einführung wird auf die Bedeutung der Kartographie im Zusammenhang mit VGI eingegangen. Der zweite Teil beinhaltet Didaktik mit Schwerpunkt E-Learning. Dazu werden das Goal Based Scenario Modell und das Cognitive Apprenticeship Modell kurz vorgestellt und anschließend das Projekt GITTA mit der enthaltenen ECLASS-Struktur näher erklärt. Den immer wichtiger werdenden Content Management Systemen (CMS) widmet sich der dritte Theorieteil. Für die Realisierung der zu erstellenden Lektion wird das Open-Source CMS Joomla! ausführlicher erläutert. Die Implementierung beschreibt die Umsetzung der E-Leraning-Lektion mittels Joomla! und die Nutzung des ECLASS-Modells. Bevor auf die Vorgehensweise eingegangen wird, enthält der Implementierungsteil die Erstellung eines groben Gesamtkonzeptes für eine komplette E-Leraning-Anwendung zu OCAD mit entsprechenden Erläuterungen. Anschließend folgen eine Zusammenfassung und ein Ausblick über die Weiterführung der E-Learning-Anwendung.:Zusammenfassung III Aufgabenstellung IV Abbildungsverzeichnis V Tabellenverzeichnis V Abkürzungsverzeichnis VI Inhaltsverzeichnis VII Selbständigkeitserklärung IX 1. Einführung 10 1.1 Ziele 11 1.2 Hintergrund 11 2. Nutzergenerierte Daten 13 2.1 Einführung 13 2.2 Nutzergenerierte Daten in der Kartographie 14 2.3 Nutzergenerierte Daten in OCAD 22 3. Didaktik 26 3.1 Allgemeine Bedeutung 26 3.2 Lernen 26 3.3 Lernprozess 27 3.4 Lernen mit digitalen Medien 28 3.5 E-Learning 28 3.5.1 Was ist E-Learning? 28 3.5.2 E-Learning Modelle 29 3.5.3 Vorteile und Nachteile von E-Learning 32 3.6 Das Projekt GITTA 32 3.6.1 Übersicht 32 3.6.2 Entwicklung von Lernmaterialien 33 3.6.3 ECLASS Modell 34 4. Content Management Systeme 35 4.1 Einführung 35 4.2 Definitionen 36 4.3 Eigenschaften von CMS 37 4.4 Ausblick 38 4.5 Joomla! 4.5.1 Einführung 39 4.5.2 Geschichte 39 4.5.3 Versionen 40 4.5.4 Funktionen 41 4.5.5 Aufbau 42 4.5.6 Auswahlkriterien für CMS 43 5. Implementierung 44 5.1 Motivation 44 5.2 Modellerstellung 46 5.3 Wahl der zur Umsetzung nutzbaren Systeme 48 5.3.1 ECLASS-Modell 48 5.3.2 Joomla! 49 5.4 Umsetzung der Lektion in Joomla! 49 5.4.1 Vorbereitungen 50 5.4.2 Konzeptübertragung 51 6. Zusammenfassung 54 6.1 Zusammenfassung der Praktischen Arbeit 54 6.2 Ausblick 55 Literaturverzeichnis LVI Literaturquellen LVI Internetquellen LXII Anhang LXIV Anhang 1 - Gegenüberstellung ausgewählter kartographischer Funktionalitäten in Adobe Illustrator und OCAD LXV Anhang 2 - Abdruck der Beispiel E-Learning Lektion LXVII

No description available.

La production et la maintenance de contenus géographiques se fait souvent grâce à la mise en commun de contributions diverses. La mise à jour des données de l'IGN s'appuie ainsi sur l'intégration de données de partenaires ou la prise en compte d'alertes d'évolution du terrain. C'est également le cas des contenus libres produits par des projets communautaires comme OpenStreetMap. Un aspect problématique est la gestion de la qualité d'un contenu géographique collaboratif, particulièrement de leur cohérence afin de permettre que des prises de décision s'appuient dessus. Cette cohérence est liée à l'homogénéité de la représentation de l'espace, ainsi qu'à la préservation d'informations importantes non explicites mais qui peuvent être retrouvées sur les entités décrites grâce à leurs géométries. Ce travail de thèse propose un modèle baptisé Coalla pour l'édition collaborative d'un contenu géographique avec gestion de la cohérence. Ce modèle comporte trois contributions : 1) l'identification et la définition des éléments que doit comporter un vocabulaire formel visant à faciliter la construction d'un contenu géographique collaboratif ; 2) un processus d'aide à la construction à la volée d'un vocabulaire formel à partir de spécifications formelles des bases de données IGN et à des vocabulaires collaboratifs existants, et 3) une stratégie d'évaluation et de réconciliation des contributions afin de les intégrer d'une façon cohérente au contenu central. Notre modèle Coalla a été implémenté dans un prototype / Geographic content production and maintenance is often done through a combination of various contributions. Thus, updating IGN geographic data relies on integrating data from partners or by involving field change alerts. This is also the case of free content produced by community projects such as OpenStreetMap. An important problem is quality management of collaboratively produced geographic content, in particular consistency management. This allows for decision-making which is based on this content. Data consistency depends on how homogenous space representation is. Likewise, it depends on preserving important non-explicit information that can be found on the geometries of the entities described in the content. This Thesis proposes a model baptized Coalla for collaborative editing of geographic content with consistency management. The model has three contributions: 1) identifying and defining elements that should be included in a formal vocabulary to facilitate the construction of collaborative geographic content, 2) user assistance process to help users build on the fly a formal vocabulary extracted from formal IGN databases specifications and existing collaborative vocabularies, and 3) a strategy for evaluating and reconciling user contributions in order to coherently integrate them into the content. Our model Coalla has been implemented in a prototype

台灣擁有豐富而多樣的自然生態資源，而物種調查將有助於維護物種之多樣性與生態平衡。然而，台灣生物多樣性高且分布廣闊，調查工作往往需耗費龐大的人力、物力、經費與時間成本。故本研究採用自願性地理資訊 (volunteered geographic information, VGI) 的方式，鼓勵社區民眾參與社區之物種調查工作。藉由社區民眾對社區當地的瞭解與使命感，有效且快速地蒐集物種調查資料。望社區民眾可經由親身參與物種調查之工作，更加瞭解及關注社區生態環境之現況，體認生態保育及生物多樣性的重要性，提升環境保育意識。 而近年來隨著行動科技的快速發展，智慧型手機與平板電腦等行動裝置日益普及。為使物種調查之工作更加快速且便利，本研究利用多數智慧型行動裝置所擁有的即時定位、無線網路及照相等功能，建置社區物種調查系統App。該App可作為物種調查之工具，並提供適時適地之物種資訊查詢服務。此外，本研究亦透過物種空間資料庫與網際網路地理資訊系統 (WebGIS) 平台之建置，提供社區物種資料分享、管理與分析等服務。 / Taiwan is abundant in ecological resources, and species investigation will contribute to preserve species diversity and ecological balance. However, due to high biodiversity and wide distribution of species in Taiwan, the traditional investigation works cost a lot of money, time, human and material resources. Therefore, this study uses the concept of volunteered geographic information (VGI) to encourage the public to collect field data and to participate in species investigation for local communities. With local knowledge and enthusiasm about the community, residents are capable of collecting species data more effectively and efficiently. On the other hand, through volunteered participation in species investigation, residents will have better understanding about the current status of ecological environment in the community. Thereby the residents can realize the importance of ecological conservation and biodiversity, and promote their awareness of environmental conservation. With the rapid development of mobile technology in recent years, mobile devices such as smartphones and tablet computers are gaining popularity. In order to make the investigation of species for communities more quickly and conveniently, this study makes use of the functions of most smart mobile devices such as real-time positioning, wireless networking, and digital camera to build a mobile App system for community-based species investigation. The mobile App system can serve as a tool for species investigation, and it also provides with location-based inquiry services timely and efficiently. In addition, Geographic Information System (GIS) is applied to manage the geodatabase, and a WebGIS platform is built to facilitate data sharing and analysis.

This master’s thesis determines trail suitability in the context of environmental area sensitivity, closely focusing on a proposed Bästeträsk National Park, Gotland, Sweden. The current relative low usage of the area is expected to significantly increase its tourism flow once the proposed national park is established, as the demand for nature-based tourism and recreation is growing. However, due to its pristine landscapes, myriad endemic and red-listed species, and rare geomorphological phenomena, there is a need to closely review the destination’s environmental sensitivity and potential recreational adverse impacts on the area’s ecosystem services. Consequently, the research reviews Volunteered Geographic Data within the studied area and employs Geographic Information Systems-based Multi-Criteria Decision Analysis to determine environmental trail suitability. The research identified that more than half of the studied area exhibits substantial environmental sensitivity. Additionally, it highlights that multiple used and established trails intersect considerably sensitive areas, which must be considered for future tourism planning to attain sustainable destination development. Moreover, the study furthers on the requisite to recognise nature-based activities beyond the means of low impact due to their increasing popularity and anthropogenic impacts.

Point datasets that relate to highly populated places, such as ones retrieved from social media or volunteered geographic information in general, can often result in dense point clusters when presented on maps. Therefore, it can be useful to visualize the relevant point density information directly on the urban geometry to tackle the problem of point counting and density range identification in highly cluttered areas. One solution is to relate each point to the nearest geometry object. While this is a straightforward approach, its major drawback is that local point clusters could disappear by assigning them to larger objects, e.g., long roads. To address this issue, we introduce two new point density visualization approaches by which points are related to the underlying geometry objects. In this process, we use grid cells and heatmap contour lines to divide roads, squares, and pedestrian zones into subgeometry units. Comparison of our visualization approaches with conventional density visualization methods shows that our approaches provide a more comprehensive insight into the point distribution over space, i.e., over existing urban geometry. / Wenn Punktdatensätze, die sich auf dicht bevölkerte Räume beziehen – beispielsweise räumliche Daten aus Sozialen Medien oder von VGI-Plattformen – auf Karten dargestellt werden, kommt es häufig zu dichten Punktclustern, was Aussagen über die Anzahl der Punkte oder die Intensität der Punktdichte an bestimmten Orten schwierig bis unmöglich macht. Daher kann es nützlich sein, relevante Informationen über die Punktdichte direkt mit Bezug zu urbanen Geometrien zu visualisieren. Eine Lösung besteht darin, jeden Punkt dem nächstgelegenen Geometrieobjekt zuzuordnen. Ein großer Nachteil dieses Ansatzes ist jedoch, dass lokale Punktcluster verschwinden könnten, indem sie größeren Objekten, z. B. langen Straßen, zugewiesen werden. Um dieses Problem zu lösen, werden zwei neue Ansätze zur Visualisierung der Punktdichte eingeführt, bei denen die Punkte mit den urbanen Geometrieobjekten in Beziehung gesetzt werden, lokale räumliche Eigenschaften jedoch erhalten bleiben. Dafür werden Straßen, Plätze und Fußgängerzonen mithilfe von Rasterzellen und Konturlinien von Kerndichteschätzungen in Teilgeometrieeinheiten unterteilt. Der Vergleich dieser Visualisierungsansätze mit herkömmlichen Dichtevisualisierungsmethoden zeigt, dass die vorgestellten Ansätze einen detaillierteren Einblick in die räumliche Punktverteilung mit Bezug zur bestehenden urbanen Geometrie liefern können.