Organizational project knowledge is not being captured, consolidated, and organized, making it difficult to learn from past projects, expose the knowledge of the most experienced people, or share experience across geographic project locations. The lack of an ontology for representing this comprehensive project store inhibits its creation and the development of tools to operate on it. Process-orientation links organizational resources or artifacts with process phases and workflow. A process-orientation in knowledge management can be used to add contextual metadata to knowledge artifacts. Context can be used to improve information retrieval precision. Therefore, the study proposed a process-oriented ontology to improve the transfer of software engineering project knowledge. Four questions guided the research: What knowledge about projects should be captured? Are all project artifacts necessary and are they all equally valuable? How can process-orientation be applied to a software engineering project knowledge ontology? Are current knowledge representation languages appropriate for the task? Can software development project knowledge, as represented by this ontology, be captured and retrieved effectively in a KMS? Literature research and an empirical laboratory study answered all of the questions: Four areas of project knowledge are particularly valuable in terms of their impact on project success; requirements, revisions, risks, and resolutions. These areas also cover a meaningful breadth of software engineering project knowledge. A process abstraction was created that breaks a project down into eleven phases. These phases were the basis for a class definition that was added as a peer class to the knowledge artifacts. Using Protégé, the Process-Oriented Ontology for Software Engineering (POSE) was successfully implemented in OWL-DL. Project knowledge from a software organization was used to construct two knowledgebases: one using Google Desktop and the other using Protégé and POSE. Results demonstrated that software engineering project knowledge, as represented by POSE, can be effectively captured and retrieved. POSE-enhanced search was superior to keyword search. Google was comparable in broad text search. But the benefits of metadata and semantics proved to have significant advantages for ontologies. Process-orientation was also validated as a contributor to improved classification and retrieval.

Web usage mining has become popular in various business areas related with Web site development. In Web usage mining, the commonly visited navigational paths are extracted in terms of Web page addresses from the Web server visit logs, and the patterns are used in various applications. The semantic information of the Web page contents is generally not included in Web usage mining. In this thesis, a framework for integrating semantic information with Web usage mining is implemented. The frequent navigational patterns are extracted in the forms of ontology instances instead of Web page addresses and the result is used for making page recommendations to the visitor. Moreover, an evaluation mechanism is implemented to find the success of the recommendation. Test results proved that stronger and more accurate recommendations are obtained by including semantic information in the Web usage mining instead of using on visited Web page addresses.

La recherche d’information sémantique (RIS), cherche à proposer des modèles qui permettent de s’appuyer, au delà des calculs statistiques, sur la signification et la sémantique des mots du vocabulaire, afin de mieux caractériser les documents pertinents au regard du besoin de l’utilisateur et de les retrouver. Le but est ainsi de dépasser les approches classiques purement statistiques (de « sac de mots »), fondées sur des appariements de chaînes de caractères sur la base des fréquences des mots et de l’analyse de leurs distributions dans le texte. Pour ce faire, les approches existantes de RIS, à travers l’exploitation de ressources sémantiques externes (thésaurus ou ontologies), procèdent en injectant des connaissances dans les modèles classiques de RI de manière à désambiguïser le vocabulaire ou à enrichir la représentation des documents et des requêtes. Il s’agit le plus souvent d’adaptations de ces modèles, on passe alors à une approche « sac de concepts » qui permet de prendre en compte la sémantique notamment la synonymie. Les ressources sémantiques, ainsi exploitées, sont « aplaties », les calculs se cantonnent, généralement, à des calculs de similarité sémantique. Afin de permettre une meilleure exploitation de la sémantique en RI, nous mettons en place un nouveau modèle, qui permet d’unifier de manière cohérente et homogène les informations numériques (distributionnelles) et symboliques (sémantiques) sans sacrifier la puissance des analyses. Le réseau sémantico-documentaire ainsi modélisé est traduit en graphe pondéré. Le mécanisme d’appariement est assuré par une propagation d’activation dans le graphe. Ce nouveau modèle permet à la fois de répondre à des requêtes exprimées sous forme de mots clés, de concepts oumême de documents exemples. L’algorithme de propagation a le mérite de préserver les caractéristiques largement éprouvéesdes modèles classiques de recherche d’information tout en permettant une meilleure prise en compte des modèles sémantiques et de leurs richesse. Selon que l’on introduit ou pas de la sémantique dans ce graphe, ce modèle permet de reproduire une RI classique ou d’assurer en sus certaines fonctionnalités sémantiques. La co-occurrence dans le graphe permet alors de révélerune sémantique implicite qui améliore la précision en résolvant certaines ambiguïtés sémantiques.L’exploitation explicite des concepts ainsi que des liens du graphe, permettent la résolution des problèmes de synonymie, de term mismatch et de couverture sémantique. Ces fonctionnalités sémantiques, ainsi que le passage à l’échelle du modèle présenté, sont validés expérimentalement sur un corpus dans le domaine médical. / Semantic information retrieval (SIR) aims to propose models that allow us to rely, beyond statistical calculations, on the meaning and semantics of the words of the vocabulary, in order to better represent relevant documents with respect to user’s needs, and better retrieve them.The aim is therefore to overcome the classical purely statistical (« bag of wordsé») approaches, based on strings’ matching and the analysis of the frequencies of the words and their distributions in the text.To do this, existing SIR approaches, through the exploitation of external semantic resources (thesauri, ontologies, etc.), proceed by injecting knowledge into the classical IR models (such as the vector space model) in order to disambiguate the vocabulary or to enrich the representation of documents and queries.These are usually adaptations of the classical IR models. We go so to a « bag of concepts » approach which allows us to take account of synonymy. The semantic resources thus exploited are « flattened », the calculations are generally confined to calculations of semantic similarities.In order to better exploit the semantics in RI, we propose a new model, which allows to unify in a coherent and homogeneous way the numerical (distributional) and symbolic (semantic) information without sacrificing the power of the analyzes of the one for the other. The semantic-documentary network thus modeled is translated into a weighted graph. The matching mechanism is provided by a Spreading activation mechanism in the graph. This new model allows to respond to queries expressed in the form of key words, concepts or even examples of documents. The propagation algorithm has the merit of preserving the well-tested characteristics of classical information retrieval models while allowing a better consideration of semantic models and their richness.Depending on whether semantics is introduced in the graph or not, this model makes it possible to reproduce a classical IR or provides, in addition, some semantic functionalities. The co-occurrence in the graph then makes it possible to reveal an implicit semantics which improves the precision by solving some semantic ambiguities. The explicit exploitation of the concepts as well as the links of the graph allow the resolution of the problems of synonymy, term mismatch, semantic coverage, etc. These semantic features, as well as the scaling up of the model presented, are validated experimentally on a corpus in the medical field.

Context. Information overload is an increasingly important problem of our age where the amount of data we have is expanding drastically with the use of digital communication. Information retrieval models are developed to help overcoming this problem with computerized tools. Semantic information retrieval, which means retrieving information based on the interpretations of meanings of the words, is one of these models and started to be used commonly to handle large amount of data in the Internet and in enterprises to overcome information overload problems. Objectives. In this study we investigate different information retrieval models for using with knowledge management systems in large-scale organizations from the perspective of software engineers. To this end, we aim at identifying existing issues and needs about information overload and then assessing different solutions against these needs. Afterwards, we analyze the chosen solution, which is semantic search, and define and carry out an implementation process to reflect on it. Finally, the usefulness and feasibility of this type of solutions to overcome the specified information overload problems in software engineering is studied and discussed. Methods. We performed a literature review to extract the existing knowledge, technology, and the problems and solutions in the defined context. Then a case study was conducted at a development site of Ericsson AB in Sweden. Case study involved unstructured and semi-structured interviews for data collection, and an implementation attempt for a simple semantic knowledge management system. Thematic Coding Analysis method is used for qualitative data analysis. Results. We identified 23 codes that are categorized under 8 themes from the opinions of company practitioners about semantic knowledge management systems. They are mainly about the existing problems, arguments for using semantic system for solving them, and suggestions and challenges. Conclusions. We conclude that semantic knowledge management systems have a very high potential to solve information overload problems in software engineering if the necessary measures are taken. We found that the problems are related to search engine and the document structure of the tools; usefulness of semantic system is the capability of ontology based retrieval to filter out irrelevant documents and extract hidden data and people’s skills and interests; and finally the challenge is the necessary endeavor to elicit and satisfy all the needs.

Empreendimentos hospitalares são reconhecidos pela complexidade que está associada a todas as fases de seu ciclo de vida: projeto, construção e operação. Os projetos da saúde são altamente influenciados por regulamentações locais. Estes conjuntos de códigos e legislações contém informações prescritivas e são importantes ao projeto, uma vez que as especificações são, usualmente, definidas de acordo com os critérios neles contidos. Ao longo do processo de desenvolvimento de produto, as especificações devem ser verificadas frente aos requisitos extraídos destas regulamentações. Este processo, se realizado manualmente, tende a ser demorado e propenso a erros. Tentativas de desenvolvimento de sistemas de verificação automatizada não se mostraram completamente satisfatórias. Muitos dos problemas estão relacionados à forma como novas abordagens são concebidas, muitas vezes desenvolvidas de acordo com métodos codificados e fragmentados, e à tipologia de informação que está nas normas e regulamentações. A abordagem metodológica utilizada nesta pesquisa foi a Design Science Research. Como artefato, foi desenvolvido um framework com base na abordagem semântica, para fornecer suporte ao desenvolvimento de sistemas de verificação automatizada, com ênfase em requisitos regulamentares no contexto de projetos de edificações hospitalares. As principais contribuições teóricas deste estudo, portanto, estão relacionadas às taxonomias e às transformações da informação, bem como às relações entre os constructos utilizados. Os resultados indicam que a natureza das regulamentações possui impacto significativo na possibilidade de tradução em regra lógica parametrizável. Apesar de a automação ser desejável, os resultados deste estudo indicam, ainda, que atualmente nem todos os requisitos podem ser completamente traduzidos em termos de processamento e verificação automatizados. Apesar de este fato diminuir o nível geral de automatização no processo, ele pode trazer benefícios ao contexto de projetos da saúde. O atendimento de alguns dos requisitos depende em um certo grau, em critérios subjetivos, que estão relacionados à interpretação humana e à criatividade. / Healthcare facilities are recognized for the complexity associated to all phases of their lifecycle: design, construction and operation. The design of healthcare projects is highly influenced by local healthcare regulations. These legislations usually contain prescriptive information and play an important role, as design specifications should be defined based on the criteria defined therein. In the design phase, during the product development process, requirements extracted from legal regulations must be verified against design specifications. This process, if done manually, tends to be time consuming and error prone. Attempts to develop automated rule checking systems for healthcare projects have not been fully successful. Most flaws appear to be related to the way new approaches are conceived, being mostly developed according to hard-coded and fragmented approaches, and the typology of information bounded by the regulations. The methodological approach adopted in this investigation was the Design Science Research. The main outcome of this research study is a semantic-based framework, devised to support the development of automated rule checking systems, focused on regulatory requirements of healthcare building design. The main theoretical contributions of this research work are concerned with the taxonomies and information transformation, as well as the relationships among the constructs involved. The results indicate that the nature of regulations have a major impact on the possibility of translating them into logic rules. Even though automation is desirable, the findings of this study also indicate that currently not all requirements can be fully translated into rules for automated processing and checking. Although this decreases the overall degree of automation in the process, this fact may provide benefits to the healthcare context. The fulfillment of some requirements to some extend should rely on subjective criteria, which depends on human interpretation and creativity.

Les avancées récentes des Technologies de l'Information et de la Communication (TIC) ont entraîné des transformations radicales de plusieurs secteurs de l'industrie. L'adoption des technologies du Web Sémantique a démontré plusieurs avantages, surtout dans une application de Recherche d'Information (RI) : une meilleure représentation des données et des capacités de raisonnement sur celles-ci. Cependant, il existe encore peu d’applications industrielles car il reste encore des problèmes non résolus, tels que la représentation de documents hétérogènes interdépendants à travers des modèles de données sémantiques et la représentation des résultats de recherche accompagnés d'informations contextuelles.Dans cette thèse, nous abordons deux défis principaux. Le premier défi porte sur la représentation de la connaissance relative à un corpus de documents hétérogènes couvrant à la fois le contenu des documents fortement lié à un domaine métier ainsi que d'autres aspects liés à la structure de ces documents tels que leurs métadonnées, les relations inter et intra-documentaires (p. ex., les références entre documents ou parties de documents), etc. Le deuxième défi porte sur la construction des résultats de RI, à partir de ce corpus de documents hétérogènes, aidant les utilisateurs à mieux interpréter les informations pertinentes de leur recherche surtout quand il s'agit d'exploiter les relations inter/intra-documentaires.Pour faire face à ces défis, nous proposons tout d'abord une représentation sémantique du corpus de documents hétérogènes à travers un modèle de graphe sémantique couvrant à la fois les dimensions structurelle et métier du corpus. Ensuite, nous définissons une nouvelle structure de données pour les résultats de recherche, extraite à partir de ce graphe, qui incorpore les informations pertinentes directes ainsi qu'un contexte structurel et métier. Afin d'exploiter cette nouvelle structure dans un modèle de RI novateur, nous proposons une chaine de traitement automatique de la requête de l'utilisateur, allant du module d'interprétation de requête, aux modules de recherche, de classement et de présentation des résultats. Bien que nous proposions une chaine de traitement complète, nos contributions se focalisent sur les modules de recherche et de classement.Nous proposons une solution générique qui peut être appliquée dans différents domaines d'applications métiers. Cependant, dans cette thèse, les expérimentations ont été appliquées au domaine du Bâtiment et Travaux Publics (BTP), en s'appuyant sur des projets de construction. / The recent advances of Information and Communication Technology (ICT) have resulted in the development of several industries. Adopting semantic technologies has proven several benefits for enabling a better representation of the data and empowering reasoning capabilities over it, especially within an Information Retrieval (IR) application. This has, however, few applications in the industries as there are still unresolved issues, such as the shift from heterogeneous interdependent documents to semantic data models and the representation of the search results while considering relevant contextual information. In this thesis, we address two main challenges. The first one focuses on the representation of the collective knowledge embedded in a heterogeneous document corpus covering both the domain-specific content of the documents, and other structural aspects such as their metadata, their dependencies (e.g., references), etc. The second one focuses on providing users with innovative search results, from the heterogeneous document corpus, helping the users in interpreting the information that is relevant to their inquiries and tracking cross document dependencies.To cope with these challenges, we first propose a semantic representation of a heterogeneous document corpus that generates a semantic graph covering both the structural and the domain-specific dimensions of the corpus. Then, we introduce a novel data structure for query answers, extracted from this graph, which embeds core information together with structural-based and domain-specific context. In order to provide such query answers, we propose an innovative query processing pipeline, which involves query interpretation, search, ranking, and presentation modules, with a focus on the search and ranking modules.Our proposal is generic as it can be applicable in different domains. However, in this thesis, it has been experimented in the Architecture, Engineering and Construction (AEC) industry using real-world construction projects.

Empreendimentos hospitalares são reconhecidos pela complexidade que está associada a todas as fases de seu ciclo de vida: projeto, construção e operação. Os projetos da saúde são altamente influenciados por regulamentações locais. Estes conjuntos de códigos e legislações contém informações prescritivas e são importantes ao projeto, uma vez que as especificações são, usualmente, definidas de acordo com os critérios neles contidos. Ao longo do processo de desenvolvimento de produto, as especificações devem ser verificadas frente aos requisitos extraídos destas regulamentações. Este processo, se realizado manualmente, tende a ser demorado e propenso a erros. Tentativas de desenvolvimento de sistemas de verificação automatizada não se mostraram completamente satisfatórias. Muitos dos problemas estão relacionados à forma como novas abordagens são concebidas, muitas vezes desenvolvidas de acordo com métodos codificados e fragmentados, e à tipologia de informação que está nas normas e regulamentações. A abordagem metodológica utilizada nesta pesquisa foi a Design Science Research. Como artefato, foi desenvolvido um framework com base na abordagem semântica, para fornecer suporte ao desenvolvimento de sistemas de verificação automatizada, com ênfase em requisitos regulamentares no contexto de projetos de edificações hospitalares. As principais contribuições teóricas deste estudo, portanto, estão relacionadas às taxonomias e às transformações da informação, bem como às relações entre os constructos utilizados. Os resultados indicam que a natureza das regulamentações possui impacto significativo na possibilidade de tradução em regra lógica parametrizável. Apesar de a automação ser desejável, os resultados deste estudo indicam, ainda, que atualmente nem todos os requisitos podem ser completamente traduzidos em termos de processamento e verificação automatizados. Apesar de este fato diminuir o nível geral de automatização no processo, ele pode trazer benefícios ao contexto de projetos da saúde. O atendimento de alguns dos requisitos depende em um certo grau, em critérios subjetivos, que estão relacionados à interpretação humana e à criatividade. / Healthcare facilities are recognized for the complexity associated to all phases of their lifecycle: design, construction and operation. The design of healthcare projects is highly influenced by local healthcare regulations. These legislations usually contain prescriptive information and play an important role, as design specifications should be defined based on the criteria defined therein. In the design phase, during the product development process, requirements extracted from legal regulations must be verified against design specifications. This process, if done manually, tends to be time consuming and error prone. Attempts to develop automated rule checking systems for healthcare projects have not been fully successful. Most flaws appear to be related to the way new approaches are conceived, being mostly developed according to hard-coded and fragmented approaches, and the typology of information bounded by the regulations. The methodological approach adopted in this investigation was the Design Science Research. The main outcome of this research study is a semantic-based framework, devised to support the development of automated rule checking systems, focused on regulatory requirements of healthcare building design. The main theoretical contributions of this research work are concerned with the taxonomies and information transformation, as well as the relationships among the constructs involved. The results indicate that the nature of regulations have a major impact on the possibility of translating them into logic rules. Even though automation is desirable, the findings of this study also indicate that currently not all requirements can be fully translated into rules for automated processing and checking. Although this decreases the overall degree of automation in the process, this fact may provide benefits to the healthcare context. The fulfillment of some requirements to some extend should rely on subjective criteria, which depends on human interpretation and creativity.

Submitted by Patrícia Sales (patriciarsales@gmail.com) on 2018-04-11T17:01:08Z No. of bitstreams: 1 DISSERTAÇÃO_PATRÍCIA_REIS.pdf: 3464705 bytes, checksum: 5e23815f93e10de42134123fd8c03a11 (MD5) / Approved for entry into archive by Urania Araujo (urania@ufba.br) on 2018-05-03T19:29:26Z (GMT) No. of bitstreams: 1 DISSERTAÇÃO_PATRÍCIA_REIS.pdf: 3464705 bytes, checksum: 5e23815f93e10de42134123fd8c03a11 (MD5) / Made available in DSpace on 2018-05-03T19:29:26Z (GMT). No. of bitstreams: 1 DISSERTAÇÃO_PATRÍCIA_REIS.pdf: 3464705 bytes, checksum: 5e23815f93e10de42134123fd8c03a11 (MD5) / Esta pesquisa pretendeu analisar a informação através da tatuagem a partir de sujeitos cognoscentes. Partindo de uma abordagem qualitativa e descritiva em relação aos objetivos pretendidos, a pesquisa visa abordar, com uma perspectiva inter e multidisciplinar, o movimento da informação em uma sociedade totalmente dinâmica articulada com outros elementos informacionais, corroborando para a criação da tatuagem. Foi preciso ampliar o entendimento sobre a linguagem representada pela imagem tatuada ao conteúdo informacional semântico e estético. Para tanto, desvenda-se, neste estudo, o corpo humano como suporte da informação, a percepção da informação, e, a partir de então, se visa adquirir o esclarecimento necessário para alcançar a compreensão da informação social proposta por Erving Goffman. Apresenta-se histórico sobre a tatuagem, possibilidades e justificativas sobre seu uso. Utilizou-se a entrevista para a coleta de dados junto a 13 sujeitos tatuados. A análise do discurso teve o fito de averiguar as respostas e considerar a percepção que os sujeitos têm a partir das enunciações tatuadas em sua pele. A pesquisa demonstrou que a tatuagem se revela como um conjunto de informação articulado com aspectos vividos e sociais, uma obra de arte, e constatou a existência do preconceito em torno dessa “arte em pele”. Dessa forma, a pesquisa teve como intenção ampliar o estudo do objeto informação para além de suportes convencionais e assim fortalecer a consolidação da Ciência da Informação. / Abstract: This research provided an advertisement through photography from cognoscing subjects. Starting from a qualitative and descriptive approach in relation to the intended objectives, a visa research, an inter and multidisciplinary perspective, the information movement in a totally dynamic society articulated with other informational elements, corroborating for a creation of the tattoo. It was necessary to broaden the understanding of a language represented by the tattooed image to the semantic and aesthetic informational content. For more information, contact the vendor, visit the portal, and receive information on the subject. It presents history about a tattoo, possibilities and justifications about its use. An interview was used to collect data from 13 tattooed subjects. An analysis of the discourse with the aim of ascertaining how responses and considerations about perception and subjects from the enunciations tattooed on their skin. One research has shown that a tattoo is revealed as a set of information articulated with living and social actions, a work of art, and found the existence of the prejudice around "art on the skin." In this way, the research had the intention to extend the study of the informative document in addition to conventional supports and to assimilate a consolidation of the Information Science.

Empreendimentos hospitalares são reconhecidos pela complexidade que está associada a todas as fases de seu ciclo de vida: projeto, construção e operação. Os projetos da saúde são altamente influenciados por regulamentações locais. Estes conjuntos de códigos e legislações contém informações prescritivas e são importantes ao projeto, uma vez que as especificações são, usualmente, definidas de acordo com os critérios neles contidos. Ao longo do processo de desenvolvimento de produto, as especificações devem ser verificadas frente aos requisitos extraídos destas regulamentações. Este processo, se realizado manualmente, tende a ser demorado e propenso a erros. Tentativas de desenvolvimento de sistemas de verificação automatizada não se mostraram completamente satisfatórias. Muitos dos problemas estão relacionados à forma como novas abordagens são concebidas, muitas vezes desenvolvidas de acordo com métodos codificados e fragmentados, e à tipologia de informação que está nas normas e regulamentações. A abordagem metodológica utilizada nesta pesquisa foi a Design Science Research. Como artefato, foi desenvolvido um framework com base na abordagem semântica, para fornecer suporte ao desenvolvimento de sistemas de verificação automatizada, com ênfase em requisitos regulamentares no contexto de projetos de edificações hospitalares. As principais contribuições teóricas deste estudo, portanto, estão relacionadas às taxonomias e às transformações da informação, bem como às relações entre os constructos utilizados. Os resultados indicam que a natureza das regulamentações possui impacto significativo na possibilidade de tradução em regra lógica parametrizável. Apesar de a automação ser desejável, os resultados deste estudo indicam, ainda, que atualmente nem todos os requisitos podem ser completamente traduzidos em termos de processamento e verificação automatizados. Apesar de este fato diminuir o nível geral de automatização no processo, ele pode trazer benefícios ao contexto de projetos da saúde. O atendimento de alguns dos requisitos depende em um certo grau, em critérios subjetivos, que estão relacionados à interpretação humana e à criatividade. / Healthcare facilities are recognized for the complexity associated to all phases of their lifecycle: design, construction and operation. The design of healthcare projects is highly influenced by local healthcare regulations. These legislations usually contain prescriptive information and play an important role, as design specifications should be defined based on the criteria defined therein. In the design phase, during the product development process, requirements extracted from legal regulations must be verified against design specifications. This process, if done manually, tends to be time consuming and error prone. Attempts to develop automated rule checking systems for healthcare projects have not been fully successful. Most flaws appear to be related to the way new approaches are conceived, being mostly developed according to hard-coded and fragmented approaches, and the typology of information bounded by the regulations. The methodological approach adopted in this investigation was the Design Science Research. The main outcome of this research study is a semantic-based framework, devised to support the development of automated rule checking systems, focused on regulatory requirements of healthcare building design. The main theoretical contributions of this research work are concerned with the taxonomies and information transformation, as well as the relationships among the constructs involved. The results indicate that the nature of regulations have a major impact on the possibility of translating them into logic rules. Even though automation is desirable, the findings of this study also indicate that currently not all requirements can be fully translated into rules for automated processing and checking. Although this decreases the overall degree of automation in the process, this fact may provide benefits to the healthcare context. The fulfillment of some requirements to some extend should rely on subjective criteria, which depends on human interpretation and creativity.

Im Bereich der städtebasierten siedlungsstrukturellen Analysen spielen Gebäudedaten mit Informationen zur Gebäudenutzung und dem Gebäudetyp eine wichtige Rolle. Auf diesen Daten basiert die Modellierung von demografischen und sozioökonomischen Kenngrößen, welche bei Aufgaben der Siedlungsentwicklung oder in der Infrastrukturplanung zum Einsatz kommen. Vonseiten der amtlichen Vermessungsanstalten stehen kleinräumige und flächendeckende Daten zur Gebäudenutzung nur in begrenztem Umfang zur Verfügung. Eine darauf aufbauende Bevölkerungsabschätzung ist aus diesem Grund nur eingeschränkt möglich. Das Ziel dieser Arbeit war es, die Integration von nutzergenerierten Geodaten aus dem OpenStreetMap (OSM) Projekt für den Einsatz zur Abschätzung gebäudebasierter Bevölkerungs- und Wohnungszahlen zu untersuchen. Der Fokus liegt dabei besonders auf der Abgrenzung von Wohn- und Nichtwohnnutzung innerhalb von Gebäuden. Diese Informationen sind in den amtlichen Geobasisdaten nicht zu finden, können jedoch aus OSM Punkt- und Polygondaten extrahiert werden. Hauptgegenstand der Untersuchung ist die Entwicklung eines Modells zur Integration der Nichtwohnnutzungsinformationen aus OSM, welches Gewerbeinformationen anhand der OSM-Tags analysiert. Dazu war neben einer geeigneten Typologie, die Festlegung von Regeln zur Verarbeitung mehrerer Gewerbe in einem amtlichen Gebäude notwendig. Über räumliche Verschneidungen der Datensätze erfolgt die eigentliche Datenintegration. Zur Umsetzung des Modells wurden drei Python-Skripte erarbeitet, welche alle notwendigen Vorverarbeitungsschritte und anschließenden Modellberechnungen automatisiert durchführen. Zusätzlich zur Bestimmung des Nichtwohnnutzungsanteiles in den Gebäuden, fand eine Wohnung- und Bevölkerungsabschätzung mittels gebäudetypischer Kenngrößen auf Gebäudebasis statt. Mittels der Abschätzungsergebnisse ohne und mit OSM-Gewerbeinformationen, konnte eine Bewertung dieser Methode erfolgen. Eine Beurteilung der Qualität des Modells im Vergleich zur Realität benötigt geeignete Validierungsdaten. Diese wurden in Form von baublockbezogenen statistischen Einwohner- und Wohnungszahlen von der Stadt Dresden bereitgestellt und zur Ergebnisdiskussion herangezogen. Regionale Unterschiede konnten anhand von Übersichts- und Detailkarten sowie statistischen Analysen herausgearbeitet werden.:Inhaltsverzeichnis ............................................................................. I Abkürzungsverzeichnis ..................................................................... V Abbildungsverzeichnis ...................................................................... VII Tabellenverzeichnis .......................................................................... IX 1 Einleitung ...................................................................................... 11 1.1 Motivation ................................................................................... 11 1.2 Zielstellung und Aufbau der Arbeit ............................................. 12 2 Theoretische und praktische Grundlagen ...................................... 15 2.1 Räumliche Modellierung der Siedlungsstruktur ........................... 15 2.1.1 Siedlungsstrukturelle Begriffe ................................................. 15 2.1.2 Räumliche Daten ..................................................................... 18 2.2 Semantische Integration ............................................................ 23 2.2.1 Interoperabilität ...................................................................... 24 2.2.2 Datenintegration ..................................................................... 25 2.3 Semantik in Geodaten ................................................................ 28 2.3.1 Attributierung in OpenStreetMap ............................................. 28 2.3.2 Nutzungsinformationen in amtlichen Geobasisdaten ............... 31 3 Modellierung sozioökonomischer Kenngrößen ............................... 33 3.1 Bedarf an kleinräumigen Nutzungsinformationen ....................... 33 3.2 Modellierungsansätze ................................................................. 35 3.2.1 Ableitung sozioökonomischer Daten aus der Fernerkundung .. 35 3.2.2 Modellierung mit Hilfe von Geobasisdaten ............................... 36 3.3 Vorteile und Mängel der vorgestellten Ansätze .......................... 40 3.4 Möglichkeiten von OSM zur Verbesserung der Modellierung ....... 42 4 Methodik ........................................................................................ 43 4.1 Herangehensweise ..................................................................... 43 4.2 Flächen- und Gebäudenutzungen in amtlichen und OSM-Daten .. 44 4.2.1 Typologie der Flächen- und Gebäudenutzung .......................... 44 4.2.2 Typologie der Flächenbeanspruchung von Gewerben .............. 47 4.3 Modell zur Abschätzung des Nichtwohnnutzungsanteils ............. 50 4.3.1 Gebäudetypische Kenngrößen ................................................. 51 4.3.2 Vorgehensweise ...................................................................... 52 5 Daten ............................................................................................. 55 5.1 Untersuchungsgebiet .................................................................. 55 5.2 OpenStreetMap ........................................................................... 56 5.3 Amtliche Geobasisdaten .............................................................. 57 6 Praktische Umsetzung .................................................................... 59 6.1 Datenmanagement ...................................................................... 59 6.1.1 Eingesetzte Software ............................................................... 59 6.1.2 OSM-Import .............................................................................. 60 6.1.3 Datenorganisation ................................................................... 64 6.2 Praktische Umsetzung des Modell zur Abschätzung des Nichtwohnnutzungsanteils ................................................................ 65 6.2.1 Vorverarbeitung ....................................................................... 65 6.2.2 Modellberechnungen und Bevölkerungsabschätzung .............. 74 6.3 Validierung des Modells .............................................................. 79 6.3.1 Validierungsdaten .................................................................... 79 6.3.2 Durchführung ........................................................................... 80 7 Ergebnisse ..................................................................................... 83 7.1 Untersuchung zur Vollständigkeit der semantischen Informationen anhand der Gewerbe POI .......................................................................................................... 83 7.1.1 Datengrundlagen ..................................................................... 84 7.1.2 Gewerbevergleich durch zufällige Straßenwahl ........................ 84 7.1.3 Gezielter Gewerbevergleich durch Ortsbegehung .................... 86 7.2 Charakterisierung des Ergebnisdatensatzes .............................. 88 7.3 Validierung .................................................................................. 91 7.4 Ergebnisvisualisierung ................................................................ 93 8 Ergebnisdiskussion ........................................................................ 97 8.1 Kleinräumige Betrachtung ........................................................... 97 8.2 Dateninkonsistenz ...................................................................... 101 8.3 Methodische Schwächen und Stärken ........................................ 103 8.4 Weitere Analysemöglichkeiten .................................................... 104 9 Zusammenfassung ........................................................................ 105 9.1 Fazit ........................................................................................... 105 9.2 Ausblick ...................................................................................... 106 Literaturverzeichnis .......................................................................... 109 A Anhang .......................................................................................... 115 Anhang 1: IÖR Flächenschema ......................................................... 115 Anhang 2: Flächen- und Gebäudenutzungstypologie........................ 116 Anhang 3: Klassifikationsschema nach (Burckhardt, 2012) .............. 118 Anhang 4: Skript-Auszug 1 - Datenverarbeitung in der OSM-Punktdatei ................................................................................ 120 Anhang 5: Skript-Auszug 2 - Die Funktion „calculateGWTotal“ .......... 121 Anhang 6: Karten - Untersuchungsgebiet Dresden in 1:100.000 ..... 122 Anhang 7: CD-Inhalt ......................................................................... 122 / Building data with information of building uses and building types play an important role for city-based settlement structure analyses. The estimation of demographic and socio-economic parameters is based on this data. They were used in the field of settlement development or in infrastructure planning. The availability of area-wide and small-scale data of building uses from surveying authorities is limited. For this reason, the estimation of population based on this data cannot be realised sufficiently. Therefore, it was the aim of this research paper to analyse the integration of user-generated geodata from OpenStreetMap (OSM)-project for estimating building-based population and housing units. The research focuses on the separation of residential and non-residential usage within buildings. Not being detected in official geodatasets, the information can be retrieved from OSM-point and polygondata. The development of a model for the integration of non-residential information from OSM is the main subject of this research. It contains the analyses of commercial information out of the OSM Tags. Besides an appropriate typology specifications are necessary to process multiple businesses within one official building. The actual data integration occurs with the help of spatial intersections between the datasets. The implementation of the model is based on three Python-scripts, executing all pre-processing and following calculation steps automatically. In addition to the identification of non-residential building-parts, an estimation of population and housing units per building, based on typical building parameters took place. By means of the estimation results with and without OSM-information it was possible to valuate this method. Validation data is necessary to measure the quality of the model in comparison to reality. This datasets was provided by the City of Dresden, consisting of statistical population and building unit numbers based on building blocks, and used for the discussion of the results. To describe regional differences, maps with overview and detailed scales as well as statistical schemata where used.:Inhaltsverzeichnis ............................................................................. I Abkürzungsverzeichnis ..................................................................... V Abbildungsverzeichnis ...................................................................... VII Tabellenverzeichnis .......................................................................... IX 1 Einleitung ...................................................................................... 11 1.1 Motivation ................................................................................... 11 1.2 Zielstellung und Aufbau der Arbeit ............................................. 12 2 Theoretische und praktische Grundlagen ...................................... 15 2.1 Räumliche Modellierung der Siedlungsstruktur ........................... 15 2.1.1 Siedlungsstrukturelle Begriffe ................................................. 15 2.1.2 Räumliche Daten ..................................................................... 18 2.2 Semantische Integration ............................................................ 23 2.2.1 Interoperabilität ...................................................................... 24 2.2.2 Datenintegration ..................................................................... 25 2.3 Semantik in Geodaten ................................................................ 28 2.3.1 Attributierung in OpenStreetMap ............................................. 28 2.3.2 Nutzungsinformationen in amtlichen Geobasisdaten ............... 31 3 Modellierung sozioökonomischer Kenngrößen ............................... 33 3.1 Bedarf an kleinräumigen Nutzungsinformationen ....................... 33 3.2 Modellierungsansätze ................................................................. 35 3.2.1 Ableitung sozioökonomischer Daten aus der Fernerkundung .. 35 3.2.2 Modellierung mit Hilfe von Geobasisdaten ............................... 36 3.3 Vorteile und Mängel der vorgestellten Ansätze .......................... 40 3.4 Möglichkeiten von OSM zur Verbesserung der Modellierung ....... 42 4 Methodik ........................................................................................ 43 4.1 Herangehensweise ..................................................................... 43 4.2 Flächen- und Gebäudenutzungen in amtlichen und OSM-Daten .. 44 4.2.1 Typologie der Flächen- und Gebäudenutzung .......................... 44 4.2.2 Typologie der Flächenbeanspruchung von Gewerben .............. 47 4.3 Modell zur Abschätzung des Nichtwohnnutzungsanteils ............. 50 4.3.1 Gebäudetypische Kenngrößen ................................................. 51 4.3.2 Vorgehensweise ...................................................................... 52 5 Daten ............................................................................................. 55 5.1 Untersuchungsgebiet .................................................................. 55 5.2 OpenStreetMap ........................................................................... 56 5.3 Amtliche Geobasisdaten .............................................................. 57 6 Praktische Umsetzung .................................................................... 59 6.1 Datenmanagement ...................................................................... 59 6.1.1 Eingesetzte Software ............................................................... 59 6.1.2 OSM-Import .............................................................................. 60 6.1.3 Datenorganisation ................................................................... 64 6.2 Praktische Umsetzung des Modell zur Abschätzung des Nichtwohnnutzungsanteils ................................................................ 65 6.2.1 Vorverarbeitung ....................................................................... 65 6.2.2 Modellberechnungen und Bevölkerungsabschätzung .............. 74 6.3 Validierung des Modells .............................................................. 79 6.3.1 Validierungsdaten .................................................................... 79 6.3.2 Durchführung ........................................................................... 80 7 Ergebnisse ..................................................................................... 83 7.1 Untersuchung zur Vollständigkeit der semantischen Informationen anhand der Gewerbe POI .......................................................................................................... 83 7.1.1 Datengrundlagen ..................................................................... 84 7.1.2 Gewerbevergleich durch zufällige Straßenwahl ........................ 84 7.1.3 Gezielter Gewerbevergleich durch Ortsbegehung .................... 86 7.2 Charakterisierung des Ergebnisdatensatzes .............................. 88 7.3 Validierung .................................................................................. 91 7.4 Ergebnisvisualisierung ................................................................ 93 8 Ergebnisdiskussion ........................................................................ 97 8.1 Kleinräumige Betrachtung ........................................................... 97 8.2 Dateninkonsistenz ...................................................................... 101 8.3 Methodische Schwächen und Stärken ........................................ 103 8.4 Weitere Analysemöglichkeiten .................................................... 104 9 Zusammenfassung ........................................................................ 105 9.1 Fazit ........................................................................................... 105 9.2 Ausblick ...................................................................................... 106 Literaturverzeichnis .......................................................................... 109 A Anhang .......................................................................................... 115 Anhang 1: IÖR Flächenschema ......................................................... 115 Anhang 2: Flächen- und Gebäudenutzungstypologie........................ 116 Anhang 3: Klassifikationsschema nach (Burckhardt, 2012) .............. 118 Anhang 4: Skript-Auszug 1 - Datenverarbeitung in der OSM-Punktdatei ................................................................................ 120 Anhang 5: Skript-Auszug 2 - Die Funktion „calculateGWTotal“ .......... 121 Anhang 6: Karten - Untersuchungsgebiet Dresden in 1:100.000 ..... 122 Anhang 7: CD-Inhalt ......................................................................... 122