Land use change has an impact on regional sustainability which can be assessed using social, economic and environmental indicators. Stakeholder engagement tools provide a platform that can demonstrate the possible future impacts land use change may have to better inform stakeholder groups of the impact of policy changes or plausible climatic variations. To date some engagement tools are difficult to use or understand and lack user interaction whilst other tools demonstrate model environments with a tightly coupled user interface, resulting in poor performance. The research and development described herein relates to the development and testing of a visualisation engine for rendering the output of an Agent Based Model (ABM) as a 3D Virtual Environment via a loosely-coupled data driven communications protocol called Protocol Buffers. The tool, named Rural Sustainability Visualisation Tool (R.S.V.T) is primarily aimed to enhance nonexpert knowledge and understanding of the effects of land use change, driven by farmer decision making, on the sustainability of a region. Communication protocols are evaluated and Protocol Buffers, a binarybased communications protocol is selected, based on speed of object serialization and data transfer, to pass message from the ABM to the 3D Virtual Environment. Early comparative testing of R.S.V.T and its 2D counterpart RepastS shows R.S.V.T and its loosely-coupled approach offers an increase in performance when rendering land use scenes. The flexibility of Protocol Buffer’s and MongoDB are also shown to have positive performance implications for storing and running of loosely-coupled model simulations. A 3D graphics Application Programming Interface (API), commonly used in the development of computer games technology is selected to develop the Virtual Environment. Multiple visualisation methods, designed to enhance stakeholder engagement and understanding, are developed and tested to determine their suitability in both user preference and information retrieval. The application of a prototype is demonstrated using a case study based in the Lunan catchment in Scotland, which has water quality and biodiversity issues due to intense agriculture. The region is modelled using three scenario storylines that broadly describe plausible futures. Business as Might Be Usual (BAMBU), Growth Applied Strategy (GRAS) and the Sustainable European Development Goal (SEDG) are the applied scenarios. The performance of the tool is assessed and it is found that R.S.V.T can run faster than its 2D equivalent when loosely coupled with a 3D Virtual Environment. The 3D Virtual Environment and its associated visualisation methods are assessed using non-expert stakeholder groups and it is shown that 3D ABM output is generally preferred to 2D ABM output. Insights are also gained into the most appropriate visualisation techniques for agricultural landscapes. Finally, the benefit of taking a loosely-coupled approach to the visualisation of model data is demonstrated through the performance of Protocol Buffers during testing, showing it is capable of transferring large amounts of model data to a bespoke visual front-end.

La visualisation de données est un aspect important de la recherche scientifique dans de nombreux domaines.Elle permet d'aider à comprendre les phénomènes observés voire simulés et d'en extraire des informations à des fins notamment de validations expérimentales ou tout simplement pour de la revue de projet.Nous nous intéressons dans le cadre de cette étude doctorale à la visualisation de données volumiques en imagerie médicale et biomédicale, obtenues grâce à des appareils d'acquisition générant des champs scalaires ou vectoriels représentés sous forme de grilles régulières 3D.La taille croissante des données, due à la précision grandissante des appareils d'acquisition, impose d'adapter les algorithmes de visualisation afin de pouvoir gérer de telles volumétries.De plus, les GPUs utilisés en visualisation de données volumiques, se trouvant être particulièrement adaptés à ces problématiques, disposent d'une quantité de mémoire très limitée comparée aux données à visualiser.La question se pose alors de savoir comment dissocier les unités de calculs, permettant la visualisation, de celles de stockage.Les algorithmes se basant sur le principe dit "out-of-core" sont les solutions permettant de gérer de larges ensembles de données volumiques.Dans cette thèse, nous proposons un pipeline complet permettant de visualiser et de traiter, en temps réel sur GPU, des volumes de données dépassant très largement les capacités mémoires des CPU et GPU.L'intérêt de notre pipeline provient de son approche de gestion de données "out-of-core" permettant de virtualiser la mémoire qui se trouve être particulièrement adaptée aux données volumiques.De plus, cette approche repose sur une structure d'adressage virtuel entièrement gérée et maintenue sur GPU.Nous validons notre modèle grâce à plusieurs applications de visualisation et de traitement en temps réel.Tout d'abord, nous proposons un microscope virtuel interactif permettant la visualisation 3D auto-stéréoscopique de piles d'images haute résolution.Puis nous validons l'adaptabilité de notre structure à tous types de données grâce à un microscope virtuel multimodale.Enfin, nous démontrons les capacités multi-rôles de notre structure grâce à une application de visualisation et de traitement concourant en temps réel. / Data visualisation is an essential aspect of scientific research in many fields.It helps to understand observed or even simulated phenomena and to extract information from them for purposes such as experimental validations or solely for project review.The focus given in this thesis is on the visualisation of volume data in medical and biomedical imaging.The acquisition devices used to acquire the data generate scalar or vector fields represented in the form of regular 3D grids.The increasing accuracy of the acquisition devices implies an increasing size of the volume data.Therefore, it requires to adapt the visualisation algorithms in order to be able to manage such volumes.Moreover, visualisation mostly relies on the use of GPUs because they suit well to such problematics.However, they possess a very limited amount of memory compared to the generated volume data.The question then arises as to how to dissociate the calculation units, allowing visualisation, from those of storage.Algorithms based on the so-called "out-of-core" principle are the solutions for managing large volume data sets.In this thesis, we propose a complete GPU-based pipeline allowing real-time visualisation and processing of volume data that are significantly larger than the CPU and GPU memory capacities.The pipeline interest comes from its GPU-based approach of an out-of-core addressing structure, allowing the data virtualisation, which is adequate for volume data management.We validate our approach using different real-time applications of visualisation and processing.First, we propose an interactive virtual microscope allowing 3D auto-stereoscopic visualisation of stacks of high-resolution images.Then, we verify the adaptability of our structure to all data types with a multimodal virtual microscope.Finally, we demonstrate the multi-role capabilities of our structure through a concurrent real-time visualisation and processing application.

Profound knowledge of the business landscape is crucial for any company wanting to affect its position in the market. Whereas corresponding data is publicly available, visual interfaces that inform on the distribution of companies operating in different sectors are rare. To close the gap for the Danish market, we developed the Danish Company Dashboard (DCD), which uses the Danish Business Authority’s database on company data to visually explore how the different companies, grouped by industries, are geographically scattered across Denmark on a regional and municipality plane. Moreover, the study and the accompanying visualisations provide insights into how the profit of each industry and company differs throughout the regions and municipalities, thereby supporting strategic decision making tasks of industry stakeholders.

Allt mer naturvetenskapsdidaktisk forskning intresserar sig för systemtänkande och elevers utvecklande av förmågor som att förstå, förklara och tolka komplexa och dynamiska system. I detta ingår identifikation av fenomen på olika biologiska organisationsnivåer och relationerna dem emellan. Kolets kretslopp är exempel på ett komplext system som innefattar komponenter och processer på flera olika mikro- och makronivåer. Denna studie undersöker elevers uppfattning och användning av olika biologiska organisationsnivåer vid förklaring av kolets kretslopp med hjälp av en interaktiv visualisering. För datainsamlingen användes think aloud-intervjuer med gymnasieelever som, indelade i par, genomförde en övning i visualiseringen och med hjälp av den förklarade kolets kretslopp. I analysen kategoriserades elevernas uttalanden till olika organisationsnivåer (molekyl, cell, organism, ekosystem och global) och beskrivningar av nivåerna upprättades utifrån kodning. Resultatet visar att eleverna framförallt förklarar kolets kretslopp på organism- och ekosystemnivå, men också att samtliga fem utvalda organisationsnivåer behandlas. Dessutom består resultatet av beskrivningar av, och exempel på, organisationsnivåerna utifrån elevers användande av dem, vilka kan fungera som stöd för biologilärare i utveckling av elevers systemtänkande. / An increasing amount of science education research concerns systems thinking and the development of students’ ability to understand, explain and interpret complex and dynamic systems. This includes the identification of phenomena on different biological levels of organisation, as well as their interrelationships. The carbon cycle constitutes a complex system including components and processes on several micro- and macrolevels. This study investigates students’ perception and use of different biological levels of organisation in explaining the carbon cycle through an interactive visualisation. Data collection was carried out through think aloud-interviews with Swedish upper secondary school students divided into pairs. The students performed an exercise in the visualisation and used it for explaining the carbon cycle. In the analysis students’ expressions were categorised according to five selected levels of organisation (molecule, cell, organism, ecosystem and global). Coding of the expressions was performed to characterise each level of organisation. The result shows that the students primarily explained the carbon cycle through the organismal and ecosystem levels, but that all five of the selected levels of organisation were used. Additionally, the results contain descriptions and examples of the levels of organisation based on students’ use. This can serve to support biology teachers in developing students’ systems thinking.