abstract: While significant qualitative, user study-focused research has been done on augmented reality, relatively few studies have been conducted on multiple, co-located synchronously collaborating users in augmented reality. Recognizing the need for more collaborative user studies in augmented reality and the value such studies present, a user study is conducted of collaborative decision-making in augmented reality to investigate the following research question: “Does presenting data visualizations in augmented reality influence the collaborative decision-making behaviors of a team?” This user study evaluates how viewing data visualizations with augmented reality headsets impacts collaboration in small teams compared to viewing together on a single 2D desktop monitor as a baseline. Teams of two participants performed closed and open-ended evaluation tasks to collaboratively analyze data visualized in both augmented reality and on a desktop monitor. Multiple means of collecting and analyzing data were employed to develop a well-rounded context for results and conclusions, including software logging of participant interactions, qualitative analysis of video recordings of participant sessions, and pre- and post-study participant questionnaires. The results indicate that augmented reality doesn’t significantly change the quantity of team member communication but does impact the means and strategies participants use to collaborate. / Dissertation/Thesis / Masters Thesis Computer Science 2020

abstract: The volume of available spatial data has increased tremendously. Such data includes but is not limited to: weather maps, socioeconomic data, vegetation indices, geotagged social media, and more. These applications need a powerful data management platform to support scalable and interactive analytics on big spatial data. Even though existing single-node spatial database systems (DBMSs) provide support for spatial data, they suffer from performance issues when dealing with big spatial data. Challenges to building large-scale spatial data systems are as follows: (1) System Scalability: The massive-scale of available spatial data hinders making sense of it using traditional spatial database management systems. Moreover, large-scale spatial data, besides its tremendous storage footprint, may be extremely difficult to manage and maintain due to the heterogeneous shapes, skewed data distribution and complex spatial relationship. (2) Fast analytics: When the user runs spatial data analytics applications using graphical analytics tools, she does not tolerate delays introduced by the underlying spatial database system. Instead, the user needs to see useful information quickly. In this dissertation, I focus on designing efficient data systems and data indexing mechanisms to bolster scalable and interactive analytics on large-scale geospatial data. I first propose a cluster computing system GeoSpark which extends the core engine of Apache Spark and Spark SQL to support spatial data types, indexes, and geometrical operations at scale. In order to reduce the indexing overhead, I propose Hippo, a fast, yet scalable, sparse database indexing approach. In contrast to existing tree index structures, Hippo stores disk page ranges (each works as a pointer of one or many pages) instead of tuple pointers in the indexed table to reduce the storage space occupied by the index. Moreover, I present Tabula, a middleware framework that sits between a SQL data system and a spatial visualization dashboard to make the user experience with the dashboard more seamless and interactive. Tabula adopts a materialized sampling cube approach, which pre-materializes samples, not for the entire table as in the SampleFirst approach, but for the results of potentially unforeseen queries (represented by an OLAP cube cell). / Dissertation/Thesis / Doctoral Dissertation Computer Science 2020

Att visualisera rörelsedata är ett kraftigt undersökt område och en komplex uppgift. I det här projektet har jag använt rörelsedata insamlad av sensorer från Akademiska hus utplacerade på Örebro Universitetscampus. Datan är använd för att visualisera rörelser gjorda inuti byggnaderna genom en webapplikation skriven med enbart Python. Anslutbarhet mellan sensorer är undersökt huruvida det är möjligt att generera anslutbarhetsgrafer med informationen kopplad till specifika sensorer automatiskt eller för hand. I projektet så undersöks även huruvida rörelseflöden är möjliga att visualisera via den datan tillgängliggjord av Akademiska hus. / Visualizing movement data is a heavily researched area and complex task. In this project I have used movement data collected by sensors from Akademiska hus placed on campus of Örebro University. The data is used to visualize movement made inside the buildings through a developed webapp written entirely in Python. Connectivity between sensors is studied whether it is possible to generate connectivity graphs with the information associated to specific sensors automatically or done by hand. The project also researches whether movement flows are possible to visualize with the data available from Akademiska hus.

The goal of this master thesis is to construct a software system, named the LIFE Spatial Data Visualization System (LIFE-SDVS), to automatically visualize the data obtained in the LIFE project spatially. LIFE stands for the Leipzig Research Centre for Civilization Diseases. It is part of the Medical Faculty of the University of Leipzig and conducts a large medical research project focusing on civilization diseases in the Leipzig population. Currently, more than 20,000 participants have joined this population-based cohort study. The analyses in LIFE have been mostly limited to non-spatial aspects. To integrate geographical facet into the findings, a spatial visualization tool is necessary. Hence, LIFE-SDVS, an automatic map visualization tool wrapped in an interactive web interface, is constructed. LIFE-SDVS is conceptualized with a three-layered architecture: data source, functionalities and spatial visualization layers. The implementation of LIFE-SDVS was achieved by two software components: an independent, self-contained R package lifemap and the LIFE Shiny Application. The package lifemap enables the automatic spatial visualization of statistics on the map of Leipzig and to the extent of the authors knowledge, is the first R package to achieve boundary labeling for maps. The package lifemap also contains two self-developed algorithms. The Label Positioning Algorithm was constructed to find good positions within each region on a map for placing labels, statistical graphics and as starting points for boundary label leaders. The Label Alignment Algorithm solves the leader intersection problem of boundary labeling. However, to use the plotting functions in lifemap, the users need to have basic knowledge of R and it is a tedious job to manually input the argument values whenever changes on the maps are necessary. An interactive Shiny web application, the LIFE Shiny Application, is therefore built to create a user friendly data exploration and map generation tool. LIFE Shiny Application is capable of obtaining experimental data directly from the LIFE database at runtime. Additionally, a data preprocessing unit can transform the raw data into the format needed for spatial visualization. On the LIFE Shiny Application user interface, users can specify the data to display, including what data to be fetched from database and which part of the data shall be visualized, by using the filter functions provided. Many map features are also available to improve the aesthetic presentation of the maps. The resulting maps can also be downloaded for further usage in scientific publications or reports. Two use cases using LIFE hand grip strength and body mass index data demonstrate the functionalities of LIFESDVS. The current LIFE-SDVS sets a foundation for the spatial visualization of LIFE data. Suggestions on adding further functionalities into the future version are also provided.

Virtual reality is currently in the spotlight, attracting intense scrutiny by the press, technology companies, and consumers. After twenty years of dormancy, the technology has experienced a renaissance following advancements in both hardware and software. Most of these developments, and thus press attention, have been centered on entertainment. However, if the technology is going to continue to grow, it must be useful in a wide variety of situations. This paper explores the effectiveness of visualizing data in virtual reality in comparison to traditional presentations. In this thesis, we present an approach to displaying data in a virtual reality environment. We drew upon various visualization and design principles in two dimensions (2D) and extended and implemented them in three dimensions (3D). Finally, we experimented with animations to highlight how the immersive qualities of virtual reality could help direct the user's attention to important features. To verify our work, we tested users' ability to understand worldwide economic data represented as graphs. We measured the speed and accuracy of each subject's responses as they viewed the economic data in two environments: a virtual reality (VR) environment using the Oculus Rift to look at our 3D animated chart, and a more traditional environment with a series of 2D paper charts. We concluded that for newcomers to VR, 2D charts are faster and more accurate. However, 3D visualizations are more engaging and are superior when searching for certain kinds of information such as the highest and lowest values in a set.

The diploma thesis focuses on the usage of Business Intelligence for the analysis of the provided employee data. It describes the process of creating dashboards in the chosen Business Intelligence tools, compares them based on the defined criteria and chooses the most suitable tool. The diploma thesis also contains a description of an implementation process of the created solution and an economic evaluation including costs and benefits.

La recherche interroge, par la création de projets de design et par une thèse écrite, le rôle et le pouvoir de la visualisation de données dans l’approche des problématiques économiques. Dans cette étude critique et théorique, je me demande d’abord en quoi les visualisations de données qui construisent des accès aux informations et aux questionnements économiques façonnent des représentations et des comportements singuliers. Je fais l’hypothèse que les « technologies intellectuelles » (Goody) qui rendent visibles ces données – les diagrammes, les réseaux, les cartes – ont construit depuis le début du XIXe siècle, une vision particulièrement étroite, désincarnée et dépolitisante de l’économie. Cependant, le design dispose de moyens favorisant, dans certaines conditions, la réappropriation des sujets économiques par les non-expert·e·s. Il s’agit alors de comprendre, en étudiant l’évolution de ses méthodes, la nature du régime contemporain de visualisation des phénomènes économiques, que je qualifie de néolibéral, et d’explorer ensuite les espaces d’intervention du design où des alternatives peuvent se déployer.Dans un second temps, au-delà de décrire, de comprendre ou de faire comprendre des phénomènes économiques, il m’a semblé que le rôle du design dans la visualisation de données était d’opérer des actes de « saisie » : saisir les données et les phénomènes, sur le plan cognitif, pour les comprendre ; mais aussi saisir les phénomènes économiques, dans leur sens, leur signification et leur raison d’être, le sens de l’économie et les objectifs qu’elle poursuit ; enfin, saisir par les sens, sur le plan sensoriel et sensible, en nous rappelant qu’au-delà de l’œil et de la vue, c’est le corps tout entier qui peut opérer la saisie. Ne parvenant pas à saisir l’économie, en me concentrant sur la performance cognitive ou communicationnelle des visualisations de données, l’hypothèse d’une « emprise sorcière » (Stengers et Pignarre), s’est alors imposée comme un terrain d’expérimentation fécond et comme une clé de lecture précieuse pour positionner, dans mon travail, l’imagination, les corps, les sens, les représentations mentales en tant qu’éléments essentiels pour penser l’économie. La magie qui habite nos rapports à l’économie m’oriente d’abord vers le pouvoir de rendre visible l’invisible, que détiennent les visualisations de données, et m’amène à questionner leur puissance liée à leur nature d’image. J’esquisse ensuite, avec la magie des liens (Bruno), une théorie de la visualisation comme pouvoir de relier et introduit la méthode des microcosmogrammes. Enfin, avec la sorcellerie, c’est la capacité à rendre tangible l’impalpable qui est examinée et confrontée au concept de désorcèlement (Favret-Saada), d’où j’extrais des principes méthodologiques et un questionnement sur la figure de la ou du designer-désorceleur. / Through the creation of design projects and a written thesis, the research questions the role and power of data visualisation in the approach to economic issues. In this critical and theoretical study, I first wonder how data visualisations that construct access to economic information and issues, shape specific representations and behaviours. I hypothesise that the 'intellectual technologies' (Goody) that make these data visible – charts, diagrams, networks, maps – have built a particularly narrow, disembodied and depoliticising view of the economy since the early nineteenth century. However, under certain conditions, design has the means to encourage the reappropriation of economic subjects by non-experts. I try to understand, by studying the evolution of its methods, the nature of the contemporary regime of visualisation of economic phenomena, which I describe as neoliberal. I then explore the design spaces where alternatives can be deployed.Secondly, beyond describing, understanding or making economic phenomena understood, it seemed to me that the role of design in data visualisation was to allow to grasp: to grasp data and phenomena, on a cognitive level, in order to understand them; but also to grasp economic phenomena, in their meaning, their significance and their raison d'être, the meaning of the economy and the objectives it pursues; finally, to grasp through the senses, on a sensory and sensitive level, reminding us that beyond the eye and the sight, it is the whole body that can carry out the grasping. As I was unable to grasp the economy by focusing on the cognitive or communicative performance of data visualisations, the hypothesis of a 'sorcerer's capture' (Stengers and Pignarre), became a fertile field of experimentation and as a precious key to understanding. It has allowed to position, in my work, imagination, bodies, senses and mental representations as essential elements for thinking about the economy. Firstly, with the magic that inhabits our relationship to the economy, I focus on the power of data visualisations to make the invisible visible, and then I question their power linked to their nature as images. Then, with the magical bondings (Bruno), I sketch a theory of visualisation as a power to bind and introduce the method of microcosmograms. Finally, with witchcraft, it is the capacity to touch the impalpable that is examined and confronted with the concept of unbewitching (Favret-Saada), from which I extract methodological principles and a questioning of the figure of the designer-unbewitcher. / Doctorat en Art et Sciences de l'Art / info:eu-repo/semantics/nonPublished

<p>CAL (Computer Assisted Learning) programs are widespread today in schools and families due to the effectiveness of CAL programs in improving students’ learning and task performance. The flourishing of CAL programs in education has brought large amounts of students’ learning data including log data, performance data, mouse movement data, eye movement data, video data, etc. These data can present students’ learning or problem-solving processes and reflect underlying cognitive processes. These data are valuable resources for educators to comprehend students’ learning and difficulties. However, few data analysis methods can analyze and present CAL data for educators quickly and clearly. Traditional video analysis methods can be time-consuming. Current visualization analysis methods are limited to simple charts or visualizations of a single data type. In this dissertation, I propose a visual learning analytic approach to analyze and present students' problem-solving data from CAL programs. More specifically, a visualization system was developed to present students’ problem-solving data, including eye movement, mouse movement, and performance data, to help educational researchers understand student problem-solving processes and identify students’ problem-solving strategies and difficulties. An evaluation experiment was conducted to compare the visualization system with traditional video analysis methods. Seven educational researchers were recruited to diagnose students’ problem-solving patterns, strategies, and difficulties using either the visualization system or video. The diagnosis task loads and evaluators’ diagnosis processes were measured and the evaluators were interviewed. The results showed that analyzing student problem-solving tasks using the proposed visualization method was significantly quicker than using the video method. In addition, diagnosis using the visualization system can achieve results at least as reliable as the video analysis method. Evaluators’ preferences between the two methods are summarized and illustrated in the dissertation. Finally, the implications of the visual analytic approach in education and data visualization areas are discussed. </p>

In this paper we present CubeViz.js, the successor of CubeViz, as an approach for lightweight visualization and exploration of statistical data using the RDF Data Cube vocabulary. In several use cases, such as the European Unions Open Data Portal, in which we deployed CubeViz, we were able to gather various requirements that eventually led to the decision of reimplementing CubeViz as JavaScript-only application. As part of this paper we showcase major functionalities of CubeViz.js and its improvements in comparison to the prior version.

Människor i informations samhället är omringade av teknologier och medium som ständigt sänder information av alla slag till sina användare. Visualisering av denna information blir då en kritisk aspekt för den vardagliga användaren. Detta kandidatarbetet syftar till att utmana visuell kommunikation av information och data. Genomförandet av frågeställningen sker med hjälp av designperspektivet minimalism och metoden prototypande. Vi presenterar relevant forskning och metoder som skapar en utgångspunkt för en designprocess som experimenterar med visuella gestaltningar i olika design situationer. Genom utmanandet av metoder för visuell kommunikation ville vi få fram experimentella gestaltningar som bearbetar och förmedlar information till en mottagare. Resultatet av designprocessen är en prototyp som testar visualiseringar och möjliga interaktiviteter i den valda kontexten. / People in the information society are surrounded by technologies and mediums that constantly transmit information of all kinds to their users. The design of this informationbecomes a critical aspect for the everyday user. This bachelor thesis aims to challenge visual communication of information and data. The question is carried out using methods such as prototyping and the design perspective minimalism. We present relevant research and methods that create a starting point for a design process that experiments with visual designs in a design situation. Through the challenge of methods of visual communication, we want to develop experimental designs that process and convey information to a recipient. The result of the design process is a prototype that tests visualizations and possible interactivity in the chosen context.