Developing Digital Media Platforms for Early Design

In recent times, mobile devices are becoming an integral part of our daily life. Software applications on these handheld devices are successfully migrating the traditional paper-based activities such as reading news, books, and even navigating through maps, onto the digital medium. While these applications allow information access anywhere and anytime, there is still a necessity for repurposing these digital media to support content/information creation especially in domains such as industrial design where paper-based activities are common. To utilize direct-touch tablets for collaborative conceptual design, we studied their affordances and iteratively developed a web-based wiki system, named skWiki. In this thesis, we first report an evaluation of the impact of utilizing a capacitive stylus for tracing and sketching on direct-touch tablets. This study uncovers the differences in quantitative and qualitative performance of the tablet medium compared to the paper medium when using a stylus (pen) or finger input for both tracing and sketching. While paper performed better overall, we found that the tablet medium, when used with a capacitive stylus, performed comparably to the paper medium for sketching tasks. These findings can guide sketch application designers in developing an appropriate interaction design for various input methods. In order to explore the advantages of the ubiquity of information generated on digital media, we developed Sketchbox, an Android application for sketching and sharing ideas using Dropbox as the storage cloud. An evaluation of the usage patterns of this application in a collaborative toy design scenario provided necessary guidelines for developing the skWiki system. skWiki overcomes the drawbacks of traditional wiki software, that are used as design repositories, by providing a rich editor infrastructure for sketching, text editing, and image editing. Apart from these features, skWiki provides a higher degree of freedom in sharing (cloning, branching, and merging) different versions of a sketch at various data granularities by introducing the concept of paths for maintaining revisions in a collaborative design process. We evaluated the utility of skWiki through a user study by comparing constrained and unconstrained sharing models. Furthermore, skWiki was used by the students of toy design and product design courses for both collaborative ideation and design activities. We discuss the findings and qualitative feedback from the evaluation of skWiki, and potential features for the next version of this tool

Enabling Collaborative Visual Analysis across Heterogeneous Devices

We are surrounded by novel device technologies emerging at an unprecedented pace. These devices are heterogeneous in nature: in large and small sizes with many input and sensing mechanisms. When many such devices are used by multiple users with a shared goal, they form a heterogeneous device ecosystem. A device ecosystem has great potential in data science to act as a natural medium for multiple analysts to make sense of data using visualization. It is essential as today's big data problems require more than a single mind or a single machine to solve them. Towards this vision, I introduce the concept of collaborative, cross-device visual analytics (C2-VA) and outline a reference model to develop user interfaces for C2-VA. This dissertation covers interaction models, coordination techniques, and software platforms to enable full stack support for C2-VA. Firstly, we connected devices to form an ecosystem using software primitives introduced in the early frameworks from this dissertation. To work in a device ecosystem, we designed multi-user interaction for visual analysis in front of large displays by finding a balance between proxemics and mid-air gestures. Extending these techniques, we considered the roles of different devices–large and small–to present a conceptual framework for utilizing multiple devices for visual analytics. When applying this framework, findings from a user study showcase flexibility in the analytic workflow and potential for generation of complex insights in device ecosystems. Beyond this, we supported coordination between multiple users in a device ecosystem by depicting the presence, attention, and data coverage of each analyst within a group. Building on these parts of the C2-VA stack, the culmination of this dissertation is a platform called Vistrates. This platform introduces a component model for modular creation of user interfaces that work across multiple devices and users. A component is an analytical primitive–a data processing method, a visualization, or an interaction technique–that is reusable, composable, and extensible. Together, components can support a complex analytical activity. On top of the component model, the support for collaboration and device ecosystems comes for granted in Vistrates. Overall, this enables the exploration of new research ideas within C2-VA

Haztrailz: Exploratory Analysis of Trajectory and Sensor Data: VAST 2016 Mini Challenge 2 Award: Honorable Mention for Clear Analysis Strategy

International audienceThe mini challenge 2 from VAST 2016 dealt with understanding the operations data from GAStech, a fictional company. We analyzed two weeks of this data including, (1) employee locations collected using proximity cards, and (2) sensor data containing temperatures, heating and cooling status, and chemical concentration levels. Our approach involved data cleaning and consolidation using R, the development of a custom trajectory visualization tool for the analysis of location data, as well as the use of existing analysis tools for the combined analysis of sensor and location data. In this paper, we discuss our analysis process, and report patterns and anomalies, as well as suspicious activities identified within the building

Steering the Craft: UI Elements and Visualizations for Supporting Progressive Visual Analytics

International audienceProgressive visual analytics (PVA) has emerged in recent years to manage the latency of data analysis systems. When analysisis performed progressively, rough estimates of the results are generated quickly and are then improved over time. Analysts cantherefore monitor the progression of the results, steer the analysis algorithms, and make early decisions if the estimates providea convincing picture. In this article, we describe interface design guidelines for helping users understand progressively updatingresults and make early decisions based on progressive estimates. To illustrate our ideas, we present a prototype PVA tool calledI NSIGHTS F EED for exploring Twitter data at scale. As validation, we investigate the tradeoffs of our tool when exploringa Twitter dataset in a user study. We report the usage patterns in making early decisions using the user interface, guidingcomputational methods, and exploring different subsets of the dataset, compared to sequential analysis without progression

Integrating annotations into multidimensional visual dashboards

Multidimensional data is often visualized using coordinated multiple views in an interactive dashboard. However, unlike in infographics where text is often a central part of the presentation, there is currently little knowledge of how to best integrate text and annotations in a visualization dashboard. In this paper, we explore a technique called FacetNotes for presenting these textual annotations on top of any visualization within a dashboard irrespective of the scale of data shown or the design of visual representation itself. FacetNotes does so by grouping and ordering the textual annotations based on properties of (1) the individual data points associated with the annotations, and (2) the target visual representation on which they should be shown. We present this technique along with a set of user interface features and guidelines to apply it to visualization interfaces. We also demonstrate FacetNotes in a custom visual dashboard interface. Finally, results from a user study of FacetNotes show that the technique improves the scope and complexity of insights developed during visual exploration.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Methodologie en Organisatie van Desig