Dans le cadre de cette thèse, nous proposons une prothèse de mémoire « intelligente », appelée CAPTAIN MEMO, destinée aux malades d’Alzheimer, pour pallier leurs problèmes mnésiques. Cette prothèse est basée sur l’ontologie temporelle, floue et multilingue appelée MemoFuzzyOnto.Cette prothèse offre des interfaces accessibles à cette classe particulière d’utilisateurs. Nous proposons, pour mettre en œuvre ces interfaces, une méthodologie de conception appelée InterfaceToAlz pour concevoir des interfaces accessibles aux malades d’Alzheimer, et qui offre un guide de 146 bonnes pratiques ergonomiques. De plus, nous proposons un outil de visualisation d’ontologies appelé Memo Graph qui génère un graphe dont la visualisation et la manipulation sont accessibles aux malades d’Alzheimer. Cette proposition est motivée par le fait que CAPTAIN MEMO a besoin de générer et d’éditer le graphe de la famille et de l’entourage du patient, à partir de l’ontologie MemoFuzzyOnto qui structure sa base de connaissances. Memo Graph est fondé sur notre guide de bonnes pratiques ergonomiques et notre approche, appelée Incremental Key-Instances Extraction and Visualisation, qui permet une extraction et une visualisation incrémentale du résumé des assertions ABox de l’ontologie. Il supporte également la visualisation des données ouvertes liées (Linked Data) et le passage à l’échelle. Par ailleurs, nous proposons, dans le cadre de cette thèse, une typologie de l’imperfection des données saisies (principalement due à la discordance mnésique provoquée par la maladie), et une méthodologie pour permettre à CAPTAIN MEMO d’être tolérante à la saisie des données fausses. Nous proposons un modèle d’évaluation de la crédibilité et une approche, nommée Data Believability Estimation for Applications to Alzheimer Patients, permettant d’estimer qualitativement et quantitativement la crédibilité de chaque donnée saisie. Enfin, pour que CAPTAIN MEMO soit tolérante à la saisie des intervalles temporels imprécis nous proposons deux approches : l’une basée sur un environnement précis et l’autre basée sur un environnement flou. Dans chacune des deux approches, nous étendons l’approche 4D-fluents pour représenter les intervalles temporels imprécis et les relations temporelles qualitatives, puis nous étendons l’algèbre d’Allen pour prendre en compte les intervalles imprécis dans le cadre de notre ontologie MemoFuzzyOnto. Nos contributions sont implémentées et évaluées. Nous avons évalué l’accessibilité de ses interfaces utilisateurs, le service de CAPTAIN MEMO qui a pour but de stimuler la mémoire du patient, notre approche pour l’estimation quantitative de la crédibilité des données saisies ainsi que la visualisation du graphe générée à l’aide de Memo Graph. Nous avons également évalué la performance de Memo Graph et son utilisabilité par des experts du domaine. / In the context of this thesis, we propose a “smart” memory prosthesis, called CAPTAIN MEMO, to help Alzheimer’s disease patients to palliate mnesic problems. It is based on a temporal, fuzzy and multilingual ontology named MemoFuzzyOnto. It provides accessible user interfaces to this demographic. To design these interfaces, we propose a methodology named InterfaceToAlz which serves as an information base for guiding and evaluating the design of user interfaces for Alzheimer’s disease patients. It identifies 146 design guidelines.Besides, we propose an ontology visualization tool called Memo Graph which offers an accessible and understandable visualization to Alzheimer’s disease patients. In fact, in the context of CAPTAIN MEMO, there is a need to generate the patient entourage/family tree from its personal data structured according to MemoFuzzyOnto. Memo Graph is based on our design guidelines and our approach, named Incremental Key-Instances Extraction and Visualisation, to extract and visualize descriptive instance summarizations from a given ontology and generate “summary instance graphs” from the most important data. It supports Linked Data visualization and scaling.Furthermore, we propose a typology of the imperfection of the data entered (mainly due to the memory discordance caused by this disease), and a methodology to allow false data entry. We propose a believability model and an approach called Data Believability Estimation for Applications to Alzheimer Patients to estimate qualitatively and quantitatively the believability of each data entered. Finally, CAPTAIN MEMO allows imprecise time intervals entry. We propose two approaches: a crisp-based approach and a fuzzy-based approach. The first one uses only crisp standards and tools and is modeled in OWL 2. The second approach is based on fuzzy sets theory and fuzzy tools and is modeled in Fuzzy-OWL 2. For the two approaches, we extend the 4D-fluents model to represent imprecise time intervals and qualitative interval relations. Then, we extend the Allen’s interval algebra to compare imprecise time interval in the context of MemoFuzzyOnto. Our contributions are implemented and evaluated. We evaluated the service of CAPTAIN MEMO which has the aim to stimulate the patient’s memory, the accessibility of its user interfaces, the efficiency of our approach to estimate quantitatively the believability of each data entered and the visualization generated with Memo Graph. We also evaluated Memo Graph with domain expert users.

Subject of information entity is one of the fundamental concepts in the field of information science. Subject of any document represents its intellectual potential -- 'aboutness' of the document. Traditionally, subject (along with title and author) is the one of three major ways to access information, so subject metadata plays a central role in this process and the role is constantly growing. Previous research concluded that the larger bibliographic database is, the richer subject vocabularies and classification schemes are needed to support information discovery. Further, a high proportion of information objects are unretrievable without subject headings in metadata records. This exploratory study provides the analysis of the subject metadata in MARC 21 bibliographic records created in 2020; and develops understanding of the level and patterns of 'aboutness' representation in the MARC 21 bibliographic records. Study also examines how these records apply the recent RDA and MARC21 guidelines and features intended to support functionality in a Linked Data environment. Methods of Social Network Analysis were applied along with content analysis, to answer research questions of this study. Suggestions for future research, implications for education, and practical recommendations for library metadata creation and management are discussed.

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Currently, the development of embedded system requires a variety of software and tools. Moreover, most of this software and tools are standalone applications, thus they are unconnected and their data can be inconsistent and duplicated. This increase both heterogeneity and the complexity of the development environment. To address this situation, tool integration solutions based on Linked Data are used, as they provide scalable and sustainable integration across different engineering tools. Different systems can access and share data by following the Linked-Data-based Open Service for Lifecycle Collaboration (OSLC) specification. OSLC uses the Tracked Resource Set (TRS) protocol to enable a server to expose a resource set and to enable a client to discover a resource in the resource set. Currently, the TRS protocol uses a client pull for the client to update its data and to synchronize with the server. However, this method is inefficient and time consuming. Moreover, high-frequency pulling may introduce an extra burden on the network and server, while low-frequency pulling increases the system’s latency (as seen by the client). A push-based low-latency solution for the TRS protocol was implemented using Message Queue Telemetry Transport (MQTT) technology. The TRS server uses MQTT to push the update patch (called a ChangeEvent) to the TRS client, then the client updates its content according to this ChangeEvent. As a result, the TRS client synchronizes with the TRS server in real time. Furthermore, a TRS adaptor was developed for Atlassian’s JIRA, a widely-used project and issue management tool. This JIRA-TRS adaptor provides a TRS provider with the ability to share data via JIRA with other software or tools which utilize the TRS protocol. In addition, a simulator was developed to simulate the operations in JIRA for a period of time (specifically the create, modify, and delete actions regarding issues) and acts as a validator to check if the data in TRS client matches the data in JIRA. An evaluation of the push-based TRS system shows an average synchronization delay of around 30 milliseconds. This is a huge change compared with original TRS system that synchronized every 60 seconds. / Nuvarande inbyggda system kräver en mängd olika program och verktyg för att stödja dess utveckling. Dessutom är de flesta av dessa programvara och verktyg fristående applikationer. De är oanslutna och deras data kan vara inkonsistent och duplicerad. Detta medför ökad heterogenitet och ökar komplexiteten i utvecklingsmiljön. För att hantera denna situation används verktygsintegrationslösningar baserade på Länkad Data, eftersom de ger en skalbar och hållbar integrationslösning för olika tekniska verktyg. Olika system kan komma åt och dela data genom att följa den Länkad Data-baserade tjänsten Open Service for Lifecycle Collaboration (OSLC). OSLC använder TRS-protokollet (Tracked Resource Set) så att en server kan exponera en resursuppsättning och för att möjliggöra för en klient att upptäcka en resurs i resursuppsättningen. TRS-protokollet använder för tillfället pull-metoden så att klienten kan uppdatera sin data och synkronisera med servern. Denna metod är emellertid ineffektiv och tidskrävande. Vidare kan en högfrekvensdriven pull-metod införa en extra börda på nätverket och servern, medan lågfrekvensdriven ökar systemets latens (som ses av klienten). I det här examensprojektet implementerar vi en pushbaserad låg latenslösning för TRS-protokollet. Den teknik som används är Message Queue Telemetry Transport (MQTT). TRS-servern använder MQTT för att pusha uppdateringspatchen (som kallas ChangeEvent) till TRS-klienten. Därefter uppdaterar klienten dess innehåll enligt denna ChangeEvent. Vilket resulterar i att TRS-klienten synkroniseras med TRS-servern i realtid. Dessutom utvecklas en TRS-adapter för Atlassians JIRA som är ett välanvänt projekt och problemhanteringsverktyg. JIRA-TRS-adaptern tillhandahåller en TRS-leverantör med möjlighet att dela data via JIRA med annan programvara eller verktyg som använder TRS-protokollet. Dessutom utvecklade vi en simulator för att simulera verksamheten i JIRA under en tidsperiod (specifikt skapa, ändra och ta bort åtgärder rörande problem) och en validator för att kontrollera om data i TRS-klienten matchar data i JIRA. En utvärdering av det pushbaserade TRS-systemet visar en genomsnittlig synkroniseringsfördröjning på cirka 30 millisekunder. Detta är en stor förändring jämfört med det ursprungliga TRS-systemet som synkroniseras var 60:e sekund.

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[pt] Esta dissertação discute técnicas para automaticamente analisar, comparar e recomendar conferências, usando dados bibliográficos. Apresenta uma implementação das técnicas propostas e descreve experimentos com os dados extraídos de uma versão triplificada do repositório DBLP. A análise de conferências baseia-se em medidas estatísticas e medidas para a análises de redes sociais aplicadas à rede de coautoria das conferências. As técnicas para comparar conferências exploram um conjunto de medidas de similaridades como, por exemplo, o coeficiente de similaridade de Jaccard, a similaridade por correlação de Pearson e o Cosseno, além de uma nova medida de similaridade baseada em comunidades de coautores. As medidas para calcular similaridade entre conferências são usadas em um sistema de recomendação baseado na estratégia de filtragem colaborativa. Finalmente, a dissertação introduz duas técnicas para recomendar conferências a um determinado autor, usando uma medida de relação entre autores. A primeira alternativa usa o índice de Katz, que pode ser computacionalmente lento para grandes grafos, enquanto a segunda adota uma aproximação do índice de Katz, que mostrou ser computacionalmente mais eficiente. Os experimentos sugerem que as melhores técnicas são: a técnica de comparação de conferências que utiliza a nova medida de similaridade baseada em comunidades de coautores; e a técnica para recomendação de conferências que explora os autores mais relacionados na rede de coautores. / [en] This dissertation discusses techniques to automatically analyze, compare and recommend conferences, using bibliographic data, outlines an implementation of the proposed techniques and describes experiments with data extracted from a triplified version of the DBLP repository. Conference analysis applies statistical and social network analysis measures to the co-authorship network. The techniques for comparing conferences explore familiar similarity measures, such as the Jaccard similarity coefficient, the Pearson correlation similarity and the cosine similarity, and a new measure, the co-authorship network communities similarity index. These similarity measures are used to create a conference recommendation system based on the Collaborative Filtering strategy. Finally, the work introduces two techniques for recommending conferences to a given prospective author based on the strategy of finding the most related authors in the co-authorship network. The first alternative uses the Katz index, which can be quite costly for large graphs, while the second one adopts an approximation of the Katz index, which proved to be much faster to compute. The experiments suggest that the best performing techniques are: the technique for comparing conferences that uses the new similarity measure based on co-authorship communities; and the conference recommendation technique that explores the most related authors in the co-authorship network.

While semantic web data is machine-understandable and well suited for advanced filtering, in its raw representation it is not conveniently understandable to humans. Therefore, visualization is needed. A core challenge when visualizing the structured but heterogeneous data turned out to be a flexible mapping to Visual Variables. This work deals with a highly flexible, semi-automatic solution with a maximum support of the visualization process, reducing the mapping possibilities to a useful subset. The basis for this is knowledge, concerning metrics and structure of the data on the one hand and available visualization structures, platforms and common graphical facts on the other hand — provided by a novel basic visualization ontology. A declarative, platform-independent mapping vocabulary and a framework was developed, utilizing current standards from the semantic web and the Model-Driven Architecture (MDA). / Während Semantic-Web-Daten maschinenverstehbar und hervorragend filterbar sind, sind sie — in ihrer Rohform — nicht leicht von Menschen verstehbar. Eine Visualisierung der Daten ist deshalb notwendig. Die Kernherausforderung dabei ist eine flexible Abbildung der strukturierten aber heterogenen Daten auf Visuelle Variablen. Diese Arbeit beschreibt eine hochflexible halbautomatische Lösung bei maximaler Unterstützung des Visualisierungsprozesses, welcher die Abbildungsmöglichkeiten, aus denen der Nutzer zu wählen hat, auf eine sinnvolle Teilmenge reduziert. Die Grundlage dafür sind einerseits Metriken und das Wissen über die Struktur der Daten und andererseits das Wissen über verfügbare Visualisierungsstrukturen, -plattformen und bekannte grafische Fakten, welche durch eine neuentwickelte Visualisierungsontologie bereitgestellt werden. Basierend auf Standards des Semantic Webs und der Model-getriebenen Architektur, wurde desweiteren ein deklaratives, plattformunabhängiges Visualisierungsvokabular und -framework entwickelt.

While semantic web data is machine-understandable and well suited for advanced filtering, in its raw representation it is not conveniently understandable to humans. Therefore, visualization is needed. A core challenge when visualizing the structured but heterogeneous data turned out to be a flexible mapping to Visual Variables. This work deals with a highly flexible, semi-automatic solution with a maximum support of the visualization process, reducing the mapping possibilities to a useful subset. The basis for this is knowledge, concerning metrics and structure of the data on the one hand and available visualization structures, platforms and common graphical facts on the other hand — provided by a novel basic visualization ontology. A declarative, platform-independent mapping vocabulary and a framework was developed, utilizing current standards from the semantic web and the Model-Driven Architecture (MDA).:ABSTRACT S. x 1. INTRODUCTION S. 1 2. VISUALIZATION OF STRUCTURED DATA IN GENERAL S. 4 2.1. Global and Local Interfaces S. 4 2.2. Steps of the Visualization Process S. 4 2.3. Existing Visual Selection Mechanisms S. 6 2.4. Existing Visualizations of Structured Data S. 12 2.5. Categorizing SemVis S. 25 3. REQUIREMENTS FOR A FLEXIBLE VISUALIZATION S. 27 3.1. Actors S. 27 3.2. Use Cases S. 27 4. FRESNEL, A STANDARD DISPLAY VOCABULARY FOR RDF S. 31 4.1. Fresnel Lenses S. 31 4.2. Fresnel Formats S. 33 4.3. Fresnel Groups S. 33 4.4. Primaries (Starting Points) S. 33 4.5. Selectors and Inference S. 34 4.6. Application and Reusability S. 34 4.7. Implementation S. 35 5. A VISUALIZATION ONTOLOGY S. 37 5.1. Describing and Formalizing the Field of Visualization S. 37 5.2. Overview S. 37 5.3. VisualVariable S. 38 5.4. DiscreteVisualValue S. 39 5.5. VisualElement S. 41 5.6. VisualizationStructure S. 42 5.7. VisualizationPlatform S. 42 5.8. PresentationScenario S. 43 5.9. Facts S. 44 6. A NOVEL MAPPING VOCABULARY FOR SEMANTIC VISUALIZATION S. 45 6.1. Overview S. 45 6.2. Mapping S. 46 6.3. PropertyMapping S. 47 6.4. ImplicitMapping S. 48 6.5. ExplicitMapping S. 53 6.6. MixedMapping S. 54 6.7. ComplexMapping S. 55 6.8. Inference S. 58 6.9. Explicit Display of Relations S. 58 6.10. Limitations s. 59 7. A MODEL-DRIVEN ARCHITECTURE FOR FLEXIBLE VISUALIZATION S. 60 7.1. A Model-Driven Architecture S. 61 7.2. Applications of the MDA Pattern S. 62 7.3. Complete System Overview S. 71 7.4. Additional Knowledge of the System S. 72 7.5. Comparison to the Graphical Modelling Framework — GMF S. 77 8. VISUALIZATION PLATFORMS S. 80 8.1. Extensible 3D (X3D) S. 80 8.2. Scalable Vector Graphics (SVG) S. 81 8.3. XHTML + CSS S. 82 8.4. Text S. 82 9. OUTLOOK AND CONCLUSION S. 84 9.1. Advanced Mapping Vocabulary S. 84 9.2. Reusing Standardized Ontologies S. 84 9.3. Enabling Dynamic, Interaction and Animation S. 84 9.4. Implementation and Evaluation S. 85 9.5. Conclusion S. 85 GLOSSARY S. 86 BIBLIOGRAPHY S. 87 A. S. 90 A.1. Schemata S. 90 / Während Semantic-Web-Daten maschinenverstehbar und hervorragend filterbar sind, sind sie — in ihrer Rohform — nicht leicht von Menschen verstehbar. Eine Visualisierung der Daten ist deshalb notwendig. Die Kernherausforderung dabei ist eine flexible Abbildung der strukturierten aber heterogenen Daten auf Visuelle Variablen. Diese Arbeit beschreibt eine hochflexible halbautomatische Lösung bei maximaler Unterstützung des Visualisierungsprozesses, welcher die Abbildungsmöglichkeiten, aus denen der Nutzer zu wählen hat, auf eine sinnvolle Teilmenge reduziert. Die Grundlage dafür sind einerseits Metriken und das Wissen über die Struktur der Daten und andererseits das Wissen über verfügbare Visualisierungsstrukturen, -plattformen und bekannte grafische Fakten, welche durch eine neuentwickelte Visualisierungsontologie bereitgestellt werden. Basierend auf Standards des Semantic Webs und der Model-getriebenen Architektur, wurde desweiteren ein deklaratives, plattformunabhängiges Visualisierungsvokabular und -framework entwickelt.:ABSTRACT S. x 1. INTRODUCTION S. 1 2. VISUALIZATION OF STRUCTURED DATA IN GENERAL S. 4 2.1. Global and Local Interfaces S. 4 2.2. Steps of the Visualization Process S. 4 2.3. Existing Visual Selection Mechanisms S. 6 2.4. Existing Visualizations of Structured Data S. 12 2.5. Categorizing SemVis S. 25 3. REQUIREMENTS FOR A FLEXIBLE VISUALIZATION S. 27 3.1. Actors S. 27 3.2. Use Cases S. 27 4. FRESNEL, A STANDARD DISPLAY VOCABULARY FOR RDF S. 31 4.1. Fresnel Lenses S. 31 4.2. Fresnel Formats S. 33 4.3. Fresnel Groups S. 33 4.4. Primaries (Starting Points) S. 33 4.5. Selectors and Inference S. 34 4.6. Application and Reusability S. 34 4.7. Implementation S. 35 5. A VISUALIZATION ONTOLOGY S. 37 5.1. Describing and Formalizing the Field of Visualization S. 37 5.2. Overview S. 37 5.3. VisualVariable S. 38 5.4. DiscreteVisualValue S. 39 5.5. VisualElement S. 41 5.6. VisualizationStructure S. 42 5.7. VisualizationPlatform S. 42 5.8. PresentationScenario S. 43 5.9. Facts S. 44 6. A NOVEL MAPPING VOCABULARY FOR SEMANTIC VISUALIZATION S. 45 6.1. Overview S. 45 6.2. Mapping S. 46 6.3. PropertyMapping S. 47 6.4. ImplicitMapping S. 48 6.5. ExplicitMapping S. 53 6.6. MixedMapping S. 54 6.7. ComplexMapping S. 55 6.8. Inference S. 58 6.9. Explicit Display of Relations S. 58 6.10. Limitations s. 59 7. A MODEL-DRIVEN ARCHITECTURE FOR FLEXIBLE VISUALIZATION S. 60 7.1. A Model-Driven Architecture S. 61 7.2. Applications of the MDA Pattern S. 62 7.3. Complete System Overview S. 71 7.4. Additional Knowledge of the System S. 72 7.5. Comparison to the Graphical Modelling Framework — GMF S. 77 8. VISUALIZATION PLATFORMS S. 80 8.1. Extensible 3D (X3D) S. 80 8.2. Scalable Vector Graphics (SVG) S. 81 8.3. XHTML + CSS S. 82 8.4. Text S. 82 9. OUTLOOK AND CONCLUSION S. 84 9.1. Advanced Mapping Vocabulary S. 84 9.2. Reusing Standardized Ontologies S. 84 9.3. Enabling Dynamic, Interaction and Animation S. 84 9.4. Implementation and Evaluation S. 85 9.5. Conclusion S. 85 GLOSSARY S. 86 BIBLIOGRAPHY S. 87 A. S. 90 A.1. Schemata S. 90