How to tell stories using visualization: strategies towards narrative visualization

Os benefícios da utilização das narrativas são desde há muito conhecidos e o seu potencial para simplificar conceitos, transmitir valores culturais e experiências, criar ligações emocionais e capacidade para ajudar a reter a informação tem sido explorado em diferentes áreas. As narrativas não são só a principal forma como as pessoas obtêm o sentido do mundo, mas também a forma mais fácil que encontrámos para partilhar informações complexas. Devido ao seu potencial, as narrativas foram recentemente abordadas na área da Visualização de Informação e do Conhecimento, muitas vezes apelidada de Visualização Narrativa. Esta questão é particularmente importante para os media, uma das áreas que tem impulsionado a investigação em Visualização Narrativa. A necessidade de incorporar histórias nas visualizações surge da necessidade de partilhar dados complexos de um modo envolvente. Hoje em dia somos confrontados com a elevada quantidade de informação disponível, um desafio difícil de resolver. Os avanços da tecnologia permitiram ir além das formas tradicionais de narrativa e de representação de dados, dando-nos meios mais atraentes e sofisticados para contar histórias. Nesta tese, exploro os benefícios da introdução de narrativas nas visualizações. Adicionalmente também exploro formas de combinar histórias com a visualizações e métodos eficientes para representar e dar sentido aos dados de uma forma que permite que as pessoas se relacionem com a informação. Esta investigação está bastante próxima da área do jornalismo, no entanto estas técnicas podem ser aplicadas em diferente áreas (educação, visualização científica, etc.). Para explorar ainda mais este tema foi adotada um avaliação que utiliza diferentes metodologias como a tipologia, vários casos de estudo, um estudo com grupos de foco, e ainda estudos de design e análise de técnicas.The benefits of storytelling are long-known and its potential to simplify concepts, convey cultural values and experiences, create emotional connection, and capacity to help retain information has been explored in di erent areas, such as journalism, education, marketing, and others. Narratives not only have been the main way people make sense of the world, but also the easiest way humans found out to share complex information. Due to its potential narratives have also recently been approached in the area of Information and Knowledge Visualization, several times being referred to as Narrative Visualization. This matter is also particularly important for news media, one of the areas that has been pushing the research on Narrative Visualization. The necessity to incorporate storytelling in visualizations arises from the need to share complex data in a way that is engaging. Nowadays we also have the challenge of the high amount of information available, which can be hard to cope with. Advances in technology have enabled us to go beyond the traditional forms of storytelling and representing data, giving us more attractive and sophisticated means to tell stories. In this dissertation, I explore the benefits of infusing visualizations with narratives. In addition I also present ways of combining storytelling with visualization and e cient methods to represent and make sense of data in a way that allows people to relate with the information. This research is closely related to journalism, but these techniques can be applied to completely di erent areas (education, scientific visualization, etc.). To further explore this topic a mixedmethod evaluation that consists of a typology, several case studies and a focus group study was chosen, as well as design studies and techniques review. This dissertation is intended to contribute to the evolving understanding of the field of narrative visualization

Casual Information Visualization on Exploring Spatiotemporal Data

The goal of this thesis is to study how the diverse data on the Web which are familiar to everyone can be visualized, and with a special consideration on their spatial and temporal information. We introduce novel approaches and visualization techniques dealing with different types of data contents: interactively browsing large amount of tags linking with geospace and time, navigating and locating spatiotemporal photos or videos in collections, and especially, providing visual supports for the exploration of diverse Web contents on arbitrary webpages in terms of augmented Web browsing

How Visualization Supports the Daily Work in Traditional Humanities on the Example of Visual Analysis Case Studies

Attempts to convince humanities scholars of digital approaches are met with resistance, often. The so-called Digitization Anxiety is the phenomenon that describes the fear of many traditional scientists of being replaced by digital processes. This hinders not only the progress of the scientific domains themselves – since a lot of digital potential is missing – but also makes the everyday work of researchers unnecessarily difficult. Over the past eight years, we have made various attempts to walk the tightrope between 'How can we help traditional humanities to exploit their digital potential?' and 'How can we make them understand that their expertise is not replaced by digital means, but complemented?' We will present our successful interdisciplinary collaborations: How they came about, how they developed, and the problems we encountered. In the first step, we will look at the theoretical basics, which paint a comprehensive picture of the digital humanities and introduces us to the topic of visualization. The field of visualization has shown a special ability: It manages to walk the tightrope and thus keeps digitization anxiety at bay, while not only making it easier for scholars to access their data, but also enabling entirely new research questions. After an introduction to our interdisciplinary collaborations with the Musical Instrument Museum of Leipzig University, as well as with the Bergen-Belsen Memorial, we will present a series of user scenarios that we have collected in the course of 13 publications. These show our cooperation partners solving different research tasks, which we classify using Brehmer and Munzner’s Task Classification. In this way, we show that we provide researchers with a wide range of opportunities: They can answer their traditional research questions – and in some cases verify long-standing hypotheses about the data for the first time – but also develop their own interest in previously impossible, new research questions and approaches. Finally, we conclude our insights on individual collaborative ideas with perspectives on our newest projects. These have risen from the growing interest of collaborators in the methods we deliver. For example, we get insights into the music of real virtuosos of the 20th century. The necessary music storage media can be heard for the first time through digital tools without risking damage to the old material. In addition, we can provide computer-aided analysis capabilities that help musicologists in their work. In the course of the visualization project at the Bergen-Belsen memorial, we will see that what was once a small diary project has grown into a multimodal and international project with institutions of culture and science from eight countries. This is dedicated not only to the question of preserving cultural objects from Nazi persecution contexts but also to modern ways of disseminating and processing knowledge around this context. Finally, we will compile our experience and accumulated knowledge in the form of problems and challenges at the border between computer science and traditional humanities. These will serve as preparation and assistance for future and current interested parties of such interdisciplinary collaborative project

Exploratory Browsing

In recent years the digital media has influenced many areas of our life. The transition from analogue to digital has substantially changed our ways of dealing with media collections. Today‟s interfaces for managing digital media mainly offer fixed linear models corresponding to the underlying technical concepts (folders, events, albums, etc.), or the metaphors borrowed from the analogue counterparts (e.g., stacks, film rolls). However, people‟s mental interpretations of their media collections often go beyond the scope of linear scan. Besides explicit search with specific goals, current interfaces can not sufficiently support the explorative and often non-linear behavior. This dissertation presents an exploration of interface design to enhance the browsing experience with media collections. The main outcome of this thesis is a new model of Exploratory Browsing to guide the design of interfaces to support the full range of browsing activities, especially the Exploratory Browsing. We define Exploratory Browsing as the behavior when the user is uncertain about her or his targets and needs to discover areas of interest (exploratory), in which she or he can explore in detail and possibly find some acceptable items (browsing). According to the browsing objectives, we group browsing activities into three categories: Search Browsing, General Purpose Browsing and Serendipitous Browsing. In the context of this thesis, Exploratory Browsing refers to the latter two browsing activities, which goes beyond explicit search with specific objectives. We systematically explore the design space of interfaces to support the Exploratory Browsing experience. Applying the methodology of User-Centered Design, we develop eight prototypes, covering two main usage contexts of browsing with personal collections and in online communities. The main studied media types are photographs and music. The main contribution of this thesis lies in deepening the understanding of how people‟s exploratory behavior has an impact on the interface design. This thesis contributes to the field of interface design for media collections in several aspects. With the goal to inform the interface design to support the Exploratory Browsing experience with media collections, we present a model of Exploratory Browsing, covering the full range of exploratory activities around media collections. We investigate this model in different usage contexts and develop eight prototypes. The substantial implications gathered during the development and evaluation of these prototypes inform the further refinement of our model: We uncover the underlying transitional relations between browsing activities and discover several stimulators to encourage a fluid and effective activity transition. Based on this model, we propose a catalogue of general interface characteristics, and employ this catalogue as criteria to analyze the effectiveness of our prototypes. We also present several general suggestions for designing interfaces for media collections

Cognitive Foundations for Visual Analytics

In this report, we provide an overview of scientific/technical literature on information visualization and VA. Topics discussed include an update and overview of the extensive literature search conducted for this study, the nature and purpose of the field, major research thrusts, and scientific foundations. We review methodologies for evaluating and measuring the impact of VA technologies as well as taxonomies that have been proposed for various purposes to support the VA community. A cognitive science perspective underlies each of these discussions

DATA-DRIVEN STORYTELLING FOR CASUAL USERS

Today’s overwhelming volume of data has made effective analysis virtually inaccessible for the general public. The emerging practice of data-driven storytelling is addressing this by framing data using familiar mechanisms such as slideshows, videos, and comics to make even highly complex phenomena understandable. However, current data stories still do not utilize the full potential of the storytelling domain. One reason for this is that current data-driven storytelling practice does not leverage the full repertoire of media that can be used for storytelling, such as speech, e-learning, and video games. In this dissertation, we propose a taxonomy focused specifically on media types for the purpose of widening the purview of data-driven storytelling by putting more tools in the hands of designers. We expand the idea of data-driven storytelling into the group of casual users, who are the consumers of information and non-professionals with limited time, skills, and motivation , to bridge the data gap between the advanced data analytics tools and everyday internet users. To prove the effectiveness and the wide acceptance of our taxonomy and data-driven storytelling among the casual users, we have collected examples for data-driven storytelling by finding, reviewing, and classifying ninety-one examples. Using our taxonomy as a generative tool, we also explored two novel storytelling mechanisms, including live-streaming analytics videos—DataTV—and sequential art (comics) that dynamically incorporates visual representations—Data Comics. Meanwhile, we widened the genres we explored to fill the gaps in the literature. We also evaluated Data Comics and DataTV with user studies and expert reviews. The results show that Data Comics facilitates data-driven storytelling in terms of inviting reading, aiding memory, and viewing as a story. The results also show that an integrated system as DataTV encourages authors to create and present data stories

The Songs of Our Past

Advancements in technology have resulted in unique changes in the way people interact with music today: Small, portable devices allow listening to it everywhere and provide access to thousands or, via streaming, even millions of songs. In addition, all played tracks can be logged with an accuracy down to the second. So far, these music listening histories are mostly used for music recommendation and hidden from their actual creators. But people may also benefit from this data more directly: as memory extensions that allow retrieving the name of a title, for rediscovering old favorites and reflecting about their lives. Additionally, listening histories can be representations of the implicit relationships between musical items. In this thesis, I discuss the contents of these listening histories and present software tools that give their owners the chance to work with them. As a first approach to understanding the patterns contained in listening histories I give an overview of the relevant literature from musicology, human-computer-interaction and music information retrieval. This literature review identifies the context as a main influence for listening: from the musical and temporal to the demographical and social. I then discuss music listening histories as digital memory extensions and a part of lifelogging data. Based on this notion, I present what an ideal listening history would look like and how close the real-world implementations come. I also derive a design space, centered around time, items and listeners, for this specific type of data and shortcomings of the real-world data regarding the previously identified contextual factors. The main part of this dissertation describes the design, implementation and evaluation of visualizations for listening histories. The first set of visualizations presents listening histories in the context of lifelogging, to allow analysing one’s behavior and reminiscing. These casual information visualizations vary in complexity and purpose. The second set is more concerned with the musical context and the idea that listening histories also represent relationships between musical items. I present approaches for improving music recommendation through interaction and integrating listening histories in regular media players. The main contributions of this thesis to HCI and information visualization are: First, a deeper understanding of relevant aspects and important patterns that make a person’s listening special and unique. Second, visualization prototypes and a design space of listening history visualizations that show approaches how to work with temporal personal data in a lifelogging context. Third, ways to improve recommender systems and existing software through the notion of seeing relationships between musical items in listening histories. Finally, as a meta-contribution, the casual approach of all visualizations also helps in providing non-experts with access to their own data, a future challenge for researchers and practitioners alike

Visualization of analytic provenance for sensemaking

Sensemaking is an iterative and dynamic process, in which people collect data relevant to their tasks, analyze the collected information to produce new knowledge, and possibly inform further actions. During the sensemaking process, it is difficult for the human’s working memory to keep track of the progress and to synthesize a large number of individual findings and derived hypotheses, thus limits the performance. Analytic provenance captures both the data exploration process and and its accompanied reasoning, potentially addresses these information overload and disorientation problems. Visualization can help recall, revisit and reproduce the sensemaking process through visual representations of provenance data. More interesting and challenging, analytic provenance has the potential to facilitate the ongoing sensemaking process rather than providing only post hoc support. This thesis addresses the challenge of how to design interactive visualizations of analytic provenance data to support such an iterative and dynamic sensemaking. Its original contribution includes four visualizations that help users explore complex temporal and reasoning relationships hidden in the sensemaking problems, using both automatically and manually captured provenance. First SchemaLine, a timeline visualization, enables users to construct and refine narratives from their annotations. Second, TimeSets extends SchemaLine to explore more complex relationships by visualizing both temporal and categorical information simultaneously. Third, SensePath captures and visualizes user actions to enable analysts to gain a deep understanding of the user’s sensemaking process. Fourth, SenseMap visualization prevents users from getting lost, synthesizes new relationship from captured information, and consolidates their understanding of the sensemaking problem. All of these four visualizations are developed using a user-centered design approach and evaluated empirically to explore how they help target users make sense of their real tasks. In summary, this thesis contributes novel and validated interactive visualizations of analytic provenance data that enable users to perform effective sensemaking