End-users publishing structured information on the web: an observational study of what, why, and how

End-users are accustomed to filtering and browsing styled collections of data on professional web sites, but they have few ways to create and publish such information architectures for themselves. This paper presents a full-lifecycle analysis of the Exhibit framework - an end-user tool which provides such functionality - to understand the needs, capabilities, and practices of this class of users. We include interviews, as well as analysis of over 1,800 visualizations and 200,000 web interactions with these visualizations. Our analysis reveals important findings about this user population which generalize to the task of providing better end-user structured content publication tools.Intel Science & Technology Center for Big Dat

Uvis: A Formula-Based End-User Tool for Data Visualization

© 2013 IEEE. Existing approaches to data visualization are one of these two: accessible to end-user developers but limited in customizability, or inaccessible and expressive. For instance, commercial charting tools are easy to use, but support only predefined visualizations, while programmatic visualization tools support custom visualizations, but require advanced programming skills. We show that it is possible to combine the learnability of charting tools and the expressiveness of visualization tools. Uvis is an interactive visualization and user interface design tool that targets end-user developers with skills comparable to spreadsheet formulas. With Uvis, designers drag and drop visual objects, set visual properties to formulas, and see the result immediately. The formulas are declarative and similar to spreadsheet formulas. The formulas compute the property values and can refer to data from database, visual objects, and end-user input. To substantiate our claim, we compared Uvis with popular visualization tools. Further, we conducted usability studies that test the ability of designers to customize visualizations with our approach. Our results show that end-user developers can learn the basics of Uvis relatively fast

User-centric Visualization of Data Provenance

The need to understand and track files (and inherently, data) in cloud computing systems is in high demand. Over the past years, the use of logs and data representation using graphs have become the main method for tracking and relating information to the cloud users. While it is still in use, tracking and relating information with ‘Data Provenance’ (i.e. series of chronicles and the derivation history of data on meta-data) is the new trend for cloud users. However, there is still much room for improving representation of data activities in cloud systems for end-users. In this thesis, we propose “UVisP (User-centric Visualization of Data Provenance with Gestalt)”, a novel user-centric visualization technique for data provenance. This technique aims to facilitate the missing link between data movements in cloud computing environments and the end-users’ uncertain queries over their files’ security and life cycle within cloud systems. The proof of concept for the UVisP technique integrates D3 (an open-source visualization API) with Gestalts’ theory of perception to provide a range of user-centric visualizations. UVisP allows users to transform and visualize provenance (logs) with implicit prior knowledge of ‘Gestalts’ theory of perception.’ We presented the initial development of the UVisP technique and our results show that the integration of Gestalt and the existence of ‘perceptual key(s)’ in provenance visualization allows end-users to enhance their visualizing capabilities, extract useful knowledge and understand the visualizations better. This technique also enables end-users to develop certain methods and preferences when sighting different visualizations. For example, having the prior knowledge of Gestalt’s theory of perception and integrated with the types of visualizations offers the user-centric experience when using different visualizations. We also present significant future work that will help profile new user-centric visualizations for cloud users

Arthroplasty Data Visualization

This master's thesis presents the work done in the field of visualization and interactivity conducted within the Design Science framework. The main goal was to make the data analysis using the arthroplasty register data into a more independent, easy, and user-friendly experience. The visualization artifact was created to support presentation of data material and results from data mining with a purpose of understand patient outcomes, longevity of implants, and present demographic and other data in a more contemporary way. There is a wealth of information and reports at the website of the Norwegian Arthroplasty Register, but very little in terms of interactivity and independent user exploration of data. The work was carried out as a part of a back- and front-end development with data mining methods developed for knee and hip prosthesis data being the back-end, and the front-end consisted of a user interface in addition to visualization. This setup had several advantages, where the selection of data mining methods and implementation of a high-fidelity user interface all contributed to a better user experience of the visualizations. The resulting artifact is comprised of visualizations of demographic data, Kaplan-Meier, and an interactive map of Norway. Interactivity enabled exploring data for selected periods of time, comparison of performance in different prostheses, and exploring patient population behind certain points on a survival graph. The map of Norway offers features such as demographic data and comparison of top 5 prostheses in different counties. The evaluation was carried out with the use of three different evaluation tools and interviews with domain and usability experts. Feedback during interviews was encouraging and indicated the potential usefulness of the visualizations. The system in its current form is more directed towards expert users, but can be easily adjusted to patients and the wider public, which could be a subject of future research. More visualizations and data analytical methods could further enhance the current solutions.Masteroppgåve i informasjonsvitskapINFO390MASV-INF