Objective: Access to, and reliance upon, high quality data is an enabling cornerstone of modern health delivery systems. Sadly, health systems are often awash with poor quality data which contributes both to adverse outcomes and can compromise the search for new knowledge. Traditional approaches to purging poor data from health information systems often require manual, laborious and time-consuming procedures at the collection, sanitizing and processing stages of the information life cycle with results that often remain sub-optimal. A promising solution may lie with semantic technologies - a family of computational standards and algorithms capable of expressing and deriving the meaning of data elements. Semantic approaches purport to offer the ability to represent clinical knowledge in ways that can support complex searching and reasoning tasks. It is argued that this ability offers exciting promise as a novel approach to assessing and improving data quality. This study examines the effectiveness of semantic web technologies as a mechanism by which high quality data can be collected and assessed in health settings. To make this assessment, key study objectives include determining the ability to construct of valid semantic data model that sufficiently expresses the complexity present in the data as well as the development of a comprehensive set of validation rules that can be applied semantically to test the effectiveness of the proposed semantic framework. Methods: The Semantic Framework for Data Quality Assessment (SemDQ) was designed. A core component of the framework is an ontology representing data elements and their relationships in a given domain. In this study, the ontology was developed using openEHR standards with extensions to capture data elements used in for patient care and research purposes in a large organ transplant program. Data quality dimensions were defined and corresponding criteria for assessing data quality were developed for each dimension. These criteria were then applied using semantic technology to an anonymized research dataset containing medical data on transplant patients. Results were validated by clinical researchers. Another test was performed on a simulated dataset with the same attributes as the research dataset to confirm the computational accuracy and effectiveness of the framework. Results: A prototype of SemDQ was successfully implemented, consisting of an ontological model integrating the openEHR reference model, a vocabulary of transplant variables and a set of data quality dimensions. Thirteen criteria in three data quality dimensions were transformed into computational constructs using semantic web standards. Reasoning and logic inconsistency checking were first performed on the simulated dataset, which contains carefully constructed test cases to ensure the correctness and completeness of logical computation. The same quality checking algorithms were applied to an established research database. Data quality defects were successfully identified in the dataset which was manually cleansed and validated periodically. Among the 103,505 data entries, application of two criteria did not return any error, while eleven of the criteria detected erroneous or missing data, with the error rates ranging from 0.05% to 79.9%. Multiple review sessions were held with clinical researchers to verify the results. The SemDQ framework was refined to reflect the intricate clinical knowledge. Data corrections were implemented in the source dataset as well as in the clinical system used in the transplant program resulting in improved quality of data for both clinical and research purposes. Implications: This study demonstrates the feasibility and benefits of using semantic technologies in data quality assessment processes. SemDQ is based on semantic web standards which allows easy reuse of rules and leverages generic reasoning engines for computation purposes. This mechanism avoids the shortcomings that come with proprietary rule engines which often make ruleset and knowledge developed for one dataset difficult to reuse in different datasets, even in a similar clinical domain. SemDQ can implement rules that have shown to have a greater capacity of detect complex cross-reference logic inconsistencies. In addition, the framework allows easy extension of knowledge base to cooperate more data types and validation criteria. It has the potential to be incorporated into current workflow in clinical care setting to reduce data errors during the process of data capture.

Structured data has been a major component of web resources since the very beginning of the web. Metadata that was originally mostly meant for display purposes gradually expanded to incorporate the semantic content of a page. Until now semantic data on the web has mostly focused on factual knowledge, namely trying to capture “what humans know”. This thesis instead focuses on procedural knowledge, or in other words, “how humans do things”, and in particular on step-by-step instructions. I will present a semantic framework to capture the meaning of sets of instructions with respect to their potential execution. This framework is based on a logical model which I evaluated in terms of its expressiveness and it compatibility with existing languages. I will show how this type of procedural knowledge can be automatically acquired from human-generated instructions on the web, while at the same time bridging the semantic gap, from unstructured to structured, by mapping these resources into a formal process description language. I will demonstrate how procedural and factual data on the web can be integrated automatically using Linked Data, and how this integration results in an overall richer semantic representation. To validate these claims I have conducted large scale knowledge acquisition and integration experiments on two prominent instructional websites and evaluated the results against a human benchmark. Finally, I will demonstrate how existing web technologies allow for this data to seamlessly enrich existing web resources and to be used on the web without the need for centralisation. I have explored the potential uses of formalised instructions by the implementation and testing of concrete prototypes which enable human users to explore know-how and collaborate with machines in novel ways.

Segmentation of web pages is one of the disciplines of information extraction. It allows to divide the page into different semantic blocks. This thesis deals with the segmentation as such and also with the implementation of the segmentation method. In this paper, we describe various examples of methods such as VIPS, DOM PS etc. There is a theoretical description of the chosen method and also the FITLayout Framework, which will be extended by this method. The implementation of the chosen method is also described in detail. The implementation description is focused on describing the different problems we had to solve. We also describe the testing that helped to reveal some weaknesses. The conclusion is a summary of the results and possible ideas for extending this work.

Cloud computing is a disruptive technology that aims to provide a utility approach to computing, where users can obtain their required computing resources without investment in infrastructure, computing platforms or services. Cloud computing resources can be obtained from a number internal or external sources. The heterogeneity of cloud service provision makes comparison of services difficult, with further complexity being introduced by a number of provision approaches such as reserved purchase, on-demand provisioning and spot markets. The aim of the research was to develop a semantic framework for cloud computing services which incorporated Cloud Service Agreements, requirements, pricing and Benefits Management. The proposed approach sees the development of an integrated framework where Cloud Service Agreements describe the relationship between cloud service providers and cloud service users. Requirements are developed from agreements and can use the concepts, relationships and assertions provided as requirements. Pricing in turn is established from requirements. Benefits Management is pervasive across the semantic framework developed. The methods used were to provide a comprehensive review of literature to establish a good theoretical basis for the research undertaken. Then problem solving ontology was developed that defined concepts and relationships for the proposed semantic framework. A number of case studies were used to populate the developed ontology with assertions. Reasoning was used to test the framework was correct. The results produced were a proposed framework of concepts, relationships and assertions for a cloud service descriptions, which are presented as ontology in textual and graphical form. Several parts of the ontology were published on public ontology platforms and, in journal and conference papers. The original contribution to knowledge is seen in the results produced. The proposed framework provides the foundations for development of a unified semantic framework for cloud computing service description and has been used by other researchers developing semantic cloud service description. In the area of Cloud Service Agreements a full coverage of the documents described by major standards organisations have been encoded into the framework. Requirements have been modelled as a unique multilevel semantic representation. Pricing of cloud services has been developed using semantic description that can be mapped to requirements. The existing Benefits Management approach has been reimplemented using semantic description. In conclusion a proposed framework has been developed that allows the semantic description of cloud computing services. This approach provides greater expression than simplistic frameworks that use mathematical formulas or models with simple relationships between concepts. The proposed framework is limited to a narrow area of service description and requires expansion to be viable in a commercial setting. Further work sees the development of software toolsets based on the semantic description developed to realise a viable product for mapping high level cloud service requirements to low level cloud resources.

L’Internet des Objets (IdO) intègre les réseaux de capteurs à Internet, et ouvre la voie pour des systèmes ou des écosystèmes ayant pour but d’aider les gens à vivre dans des mondes à la fois physiques et cybernétiques. L’IdO offre l’omniprésence d’objets capables d'interagir les uns avec les autres et de coopérer avec leurs voisins pour atteindre des objectifs communs. Ces objets dits"Intelligents" (OI), peuvent détecter l'environnement et communiquer avec d’autres objets. La création d’OI et de systèmes d’IdO fait intervenir des acteurs d’expertises très diverses. Ainsi, il devient indispensable d’avoir des descriptions standardisées et sémantiques pour résoudre les problèmes liés à l’interopérabilité et l’hétérogénéité sémantique entre les différentes ressources disponibles d’une part, et entre les différents intervenants à la conception/fabrication des OI, d’autre part. De ce fait, nous avons proposé le Framework sémantique et générique FSMS, structuré en un ensemble de modules ontologiques pour la conception/fabrication d’un OI. Une méthodologie de support à ce Framework a été proposée. Elle se fonde sur les mêmes modules ontologiques identifiés dans la composante sémantique du FSMS. Ces modules ontologiques forment l’ontologie SMS pierre angulaire de cette thèse. Un processus générique basé sur une description sémantique des composants structurels et comportementaux d’un OI a été également proposé en vue d'une gestion intelligente de la conceptiond’un OI. Ce processus a ensuite été mis en application pour des Vêtements Intelligents de sport. Un OI étant destiné à être réutilisé à différents contextes d’usage, une approche de reconfiguration/adaptationdu fonctionnement de l'OI a été proposée. Celle-ci trouve à son tour son fondement dans l’ontologie modulaire SMS. / The Internet of Things (IoT) integrates sensor networks with the Internet, and paves the way for systems or ecosystems to help people live in both physical and cyber worlds. IoT offers the ubiquity of objects that are able to interact with each other and cooperate with their neighbors to achieve common goals. These objects, called "Smart" (SO), can detect the environment and communicate with other objects. The creation of SO and IoT system involves actors of very diverse expertise. Hence, it becomes essential to have standardized and semantic descriptions to solve the problems related to the interoperability and the semantic heterogeneity between the different available resources on the one hand, and between the different stakeholders designing/manufacturing the SO, on the other hand. Therefore, we have proposed the FSMS semantic and generic framework, which is structured into a set of ontological modules to design/manufacture a given SO. A support methodology for this framework has been equally proposed. It is based on the same ontological modules identified in the semantic component of the FSMS. These ontological modules form the SMS ontology that is proposed and constitutes the corner stone of this thesis. In order to intelligently manage an SO design, we proposed a generic process based on a semantic description of the structural and behavioral components of an SO. This process was thereafeter implemented for Smart Clothing of sports. This Sportswear is intended to be used in different contexts of use, an approach to reconfiguration/adaptation of the operation of the Smart Clothing has been proposed. This one is also based on the modular ontology SMS.

The aim of this thesis was to examine the conditions for democratic bildung-oriented education for students in the school science discourse. This is something that the Swedish curriculum is based on and thereby the education should develop students' capacity for social, political and cultural awareness. The theoretical framework used is grounded in critical didactics and feminist theories which assume that students should feel involved and get their voices heard. The Swedish national test in chemistry (2009-2012) and student answers (198n) from one of the items in the 2009 test have been analyzed using discourse analysis. The first study explored the norms and values present in the national tests in chemistry, in relation to people, society and nature. The second study focused on student’s evaluative language in their free-text answers to one of the items. Thereby attitudes in student answers were projected in relation to the norms and values found in the first study. Finally, the student answers were used once more in a third study, where students’ positioning in relation to the scientific discourse in the chemistry test (2009) was explored, as well as which feminist figurations these subject positions express. The results show that the national tests harbor an elitist image and anandrocentric bias.The normative message is that students should adopt an objective, rational, non-judgmental and non-emotional role. Topics connected to young people’s everyday life, that might interest students, are rare. Contrary to the normative messages mediated by the tests, students use evaluative and embodied language to a high extent in their answers. They choose to write about topics that are close to their everyday life and they show that they are emotionally engaged. Through feminist figurations theories used in the third study one can see how the student-subject positions offer resistance in different ways. This is shown in their criticism of science and technology, human society and nature. The students' responses have embraced an embodied chemistry that can be interpreted as teaching based on bildung and deliberative discussions.