Users are being embraced as partners in developing computer services in many current computer supported cooperative work systems. Many web-based applications, including collaborative authoring tools like wikis, place users into collaborations with unknown and distant partners. Individual participants in such environments need to identify and understand others' contributions for collaboration to succeed and be efficient. One approach to supporting such understanding is to record user activity for later access. Issues with this approach include difficulties in locating activity of interest in large tasks and the history is often recorded at a system-activity level instead of at a human-activity level. To address these issues, this dissertation introduces CoActIVE, an application-independent history mechanism that clusters records of user activity and extracts keywords in an attempt to provide a human-level representation of history. CoActIVE is integrated in three different software applications to show its applicability and validity. Multiple visualization techniques based on this processing are compared in their ability to improve users' location and comprehension of the activity of others. The results show that filmstrip visualization and visual summarization of user activity show significant improvement over traditional list view interfaces. CoActIVE generates an interpretation of large-scale interaction history and provides the interpretation thorough a variety of visualizations that allow users to navigate the evolution of collaborative work. It supports branching history, with the understanding that asynchronous authoring and design tasks often involve the parallel development of alternatives. Additionally, CoActIVE has the potential to be integrated into a variety of applications with little adjustment for compatibility. Especially, the comparison of visualizations for locating and comprehending the work of others is unique.

Software changes constantly and continuously. It is often beneficial to record the progressive changes made to software, so that when any problems arise, it is possible to identify the change that might have caused the problem. Also, recording these changes enables recovery of the software as it was at any point of time. A version control system is used to track modifications to software. Version control systems (VCS) display when and where a change was made. In the case of multiple developers working on the same software system, version control systems also record which developer was responsible for the change. RCS, SCCS and CVS are examples of such version control systems, and they usually have a command-line interface. The widespread use of CVS has however given rise to a host of "CVS clients", which provide a two-dimensional graphical interface to CVS. While working with a version control system in two dimensions is a definite improvement over traditional command line interfaces, it is still not sufficient to display all the necessary information in a single view. Using three dimensions to display the information from a version control system like CVS is an effective and efficient way to represent multiple attributes in a single view. There are many advantages to using a third dimension for visualizing the version history and evolution of software. A three-dimensional visualization tool has been developed to provide insights into the structure and characteristics of the history of a software system. It demonstrates the benefits of three-dimensional visualization and illustrates a framework that can be used to automatically derive information from a version control system. / Master of Information Systems

Project file archives are becoming increasingly large. The number of files, information and data that need to be created, accessed and modified throughout a project can be overwhelming. It is critical for project participants or contributors to find relevant information in project archives quickly. In this thesis, I present VisArchive, an interactive visualization tool that provides users with better awareness of search results within project archives. VisArchive visualizes the relevance-ranked search results with a color-coded stacked bar chart and interactive timelines and provides supporting visual cues to help differentiate search results based on searched keywords. It aims to allow users to interactively search, browse, and explore information in project archives, including access history, effectively and efficiently. I will present two case studies to illustrate how VisArchive can be used to support searching, browsing, and exploring information in building construction and open source software projects. In addition, I discuss how VisArchive can be improved to address information retrieval problems and work across different domains. VisArchive demonstrates the combination and application of several visualization techniques to the problem of searching and navigating project archives. / Graduate / 0984

Project file archives are becoming increasingly large. The number of files, information and data that need to be created, accessed and modified throughout a project can be overwhelming. It is critical for project participants or contributors to find relevant information in project archives quickly. In this thesis, I present VisArchive, an interactive visualization tool that provides users with better awareness of search results within project archives. VisArchive visualizes the relevance-ranked search results with a color-coded stacked bar chart and interactive timelines and provides supporting visual cues to help differentiate search results based on searched keywords. It aims to allow users to interactively search, browse, and explore information in project archives, including access history, effectively and efficiently. I will present two case studies to illustrate how VisArchive can be used to support searching, browsing, and exploring information in building construction and open source software projects. In addition, I discuss how VisArchive can be improved to address information retrieval problems and work across different domains. VisArchive demonstrates the combination and application of several visualization techniques to the problem of searching and navigating project archives. / Graduate / 0984

Many business intelligence tools aim to digest data into easy, understandable and visualizable information for helping decision-making, while they are still lack of ability to support visualizing the history of selections. This limitation concerns the coming future when everything is about data. Due to it, users are not able to share their thinking paths to the decision. Here a history selection path means a sequence of previous selections. As an approach, it helps users in decision-making and discovery insight. This study investigated an efficient graphical visualization system of history selection paths to support communicating and iterative analysis. We selected tree representation as the main visualization model and also propose features needed for the system. Specifically, we researched the significance of this study, existing solutions and also the proper designs and functions for the idea. It is initiated by user research including targeting users and scenario mapping. Based on the understanding, we applied a parallel design to narroww down the suitable design. As a result, tree representation was selected as the visualization model. To evaluate whether it touched user needs or not, we applied usability test to collect quantitative data and qualitative comments. For making the test environment as real as possible, a webbased interactive prototype supported by D3.js library was implemented for testing. We analyzed the user experience and also consolidated improvements. As a case study, we implemented the solution on Qlik Sense to verify the possibility to place this solution into real data visualization tool. Generally, the result of this study formed a valuable initiative for further development and we saw potentials of this tree model system to be used in other areas when it comes to reviewing history as well. / Många verktyg för affärsintelligens avser till att bryta ner data till enkel, förståelig och visualiserar information för att hjälpa till beslutsantagande, medan det fortfarande saknar förmåga att stödja visualiseringen av urvalens historik. Den här begränsningen berör framtiden när allt är om data. På grund av det, användaren är inte kunniga till att dela deras sökväg till beslutet. Här menas historik urvalsväg en sekvens av tidigare val. Som ett tillvägagångsätt, hjälper det användare att fatta beslut och upptäcka insikt. Denna studie undersökte ett effektivt grafiskt visualiseringssystem av historik urvalsvägar för att stödja kommunikation och iterativ analys. Vi valde trädrepresentation som huvudligavisualisering modell och föreslår också funktioner som behövs för systemet. Specifikt har vi undersökt betydelsen av denna studie, befintliga lösningar och även rätt design och funktioner för denna idé. Det initieras av användare undersökningar inklusive målriktning av användare och scenariokartläggning. Baserat på förståelsen använde vi en parallell design för att begränsa den lämpliga designen. Som ett resultat, valdes trädrepresentation som visualiseringsmodell. För att utvärdera om det rörde användarnas behov eller inte, använde vi användbarhetstest för att samla in kvantitativa data och kvalitativa kommentarer. För att testmiljön ska bli så verklig som möjligt implementerades en webbaserad interaktiv prototyp som stöds av D3.js biblioteket för testning. Vi analyserade användare upplevelsen och konsoliderade förbättringar. Som en fallstudie implementerade vi lösningen på Qlik Sense för att verifiera möjligheten att placera denna lösning i ett verkligt data visualiseringsverktyg. I allmänhet bildade resultatet av den här studien ett värdefullt initiativ för vidare utveckling och vi såg potentialerna i detta trädmodellsystem som kan användas på andra områden när det gäller till att granska historik.

[pt] Nos dias de hoje, temos acesso a dados de tamanho, dimensionalidade e complexidade sem precedentes. Para extrair informações desconhecidas e inesperadas desses dados complexos e dinâmicos, necessitamos de estratégias efetivas e eficientes. Uma dessas estratégias é usar aplicações de análise visual (visual analytics), que combinam técnicas de análise de dados e de visualização. Depois do processo de descoberta de conhecimento, um grande desafio é filtrar a informação essencial que levou à descoberta e comunicar os achados a outras pessoas. Nós propomos tirar proveito do traço deixado pela análise exploratória de dados, sob a forma do histórico da interação do usuário, para ajudar nesse processo. Com o traço, o usuário pode escolher os passos de interação desejados e criar uma narrativa, compartilhando o conhecimento adquirido com os leitores. Para atingir nosso objetivo, desenvolvemos o arcabouço BONNIE (Building Online Narratives from Noteworthy Interaction Events - Construindo Narrativas Online a partir de Eventos de Interação Relevantes). O arcabouço compreende um modelo de log para registrar os eventos de interação, código auxiliar para ajudar o(a) desenvolvedor(a) a instrumentar o seu próprio código, e um ambiente para visualizar o histórico de interação e construir narrativas. Esta tese apresenta nossa proposta para comunicar descobertas em aplicações de análise visual, o arcabouço BONNIE, e alguns estudos empíricos que realizamos para avaliar nossa solução. / [en] Nowadays, we have access to data of unprecedentedly large size, high dimensionality, and complexity. To extract unknown and unexpected information from such complex and dynamic data, we need effective and efficient strategies. One such strategy is to combine data analysis and visualization techniques, which is the essence of visual analytics applications. After the knowledge discovery process, a major challenge is to filter the essential information that led to a discovery and to communicate the findings to other people. We propose to take advantage of the trace left by the exploratory data analysis, in the form of ser interaction history, to aid in this process. With the trace, the user can choose the desired interaction steps and create a narrative, sharing the acquired knowledge with readers. To achieve our goal, we have developed the BONNIE (Building Online Narratives from Noteworthy Interaction Events) framework. The framework comprises a log model to register the interaction events, auxiliary code to help the developer instrument his or her own code, and an environment to view the user s own interaction history and build narratives. This thesis presents our proposal for communicating discoveries in visual analytics applications, the BONNIE framework, and a few empirical studies we conducted to evaluate our solution.