Provenance in the context of workflows, both for the data they derive and for their specification, is an essential component to allow for result reproducibility, sharing, and knowledge re-use in the scientific community. Several workshops have been held on the topic, and it has been the focus of many research projects and prototype systems. This tutorial provides an overview of research issues in provenance for scientific workflows, with a focus on recent literature and technology in this area. It is aimed at a general database research audience and at people who work with scientific data and workflows. We will (1) provide a general overview of scientific workflows, (2) describe research on provenance for scientific workflows and show in detail how provenance is supported in existing systems; (3) discuss emerging applications that are enabled by provenance; and (4) outline open problems and new directions for database-related research.

Understanding perception is critical to effective visualization design. With its low cost and scalability, crowdsourcing presents an attractive option for evaluating the large design space of visualizations; however, it first requires validation. In this paper, we assess the viability of Amazon’s Mechanical Turk as a platform for graphical perception experiments. We replicate previous studies of spatial encoding and luminance contrast and compare our results. We also conduct new experiments on rectangular area perception (as in treemaps or cartograms) and on chart size and gridline spacing. Our results demonstrate that crowdsourced perception experiments are viable and contribute new insights for visualization design. Lastly, we report cost and performance data from our experiments and distill recommendations for the design of crowdsourced studies. ACM Classification: H5.2 [Information interfaces and presentation]:

The Web is ephemeral. Pages change frequently, and it is nearly impossible to find data or follow a link after the underlying page evolves. We present Zoetrope, a system that enables interaction with the historical Web (pages, links, and embedded data) that would otherwise be lost to time. Using a number of novel interactions, the temporal Web can be manipulated, queried, and analyzed from the context of familar pages. Zoetrope is based on a set of operators for manipulating content streams. We describe these primitives and the associated indexing strategies for handling temporal Web data. They form the basis of Zoetrope and enable our construction of new temporal interactions and visualizations. ACM Classification: H5.2 [Information interfaces and

Abstract—Building visualization and analysis pipelines is a large hurdle in the adoption of visualization and workflow systems by domain scientists. In this paper, we propose techniques to help users construct pipelines by consensus—automatically suggesting completions based on a database of previously created pipelines. In particular, we compute correspondences between existing pipeline subgraphs from the database, and use these to predict sets of likely pipeline additions to a given partial pipeline. By presenting these predictions in a carefully designed interface, users can create visualizations and other data products more efficiently because they can augment their normal work patterns with the suggested completions. We present an implementation of our technique in a publicly-available, open-source scientific workflow system and demonstrate efficiency gains in real-world situations.

Fig. 1: Creating an Astrophysics VisMashup to explore a binary star system. Abstract—Visualization is essential for understanding the increasing volumes of digital data. However, the process required to create insightful visualizations is involved and time consuming. Although several visualization tools are available, including tools with sophisticated visual interfaces, they are out of reach for users who have little or no knowledge of visualization techniques and/or who do not have programming expertise. In this paper, we propose VISMASHUP, a new framework for streamlining the creation of customized visualization applications. Because these applications can be customized for very specific tasks, they can hide much of the complexity in a visualization specification and make it easier for users to explore visualizations by manipulating a small set of parameters. We describe the framework and how it supports the various tasks a designer needs to carry out to develop an application, from mining and exploring a set of visualization specifications (pipelines), to the creation of simplified views of the pipelines, and the automatic generation of the application and its interface. We also describe the implementation of the system and demonstrate its use in two real application scenarios.

When information is known only to friends in a social network, traditional crowdsourcing mechanisms struggle to motivate a large enough user population and to ensure accuracy of the collected information. We thus introduce friendsourcing, a form of crowdsourcing aimed at collecting accurate information available only to a small, socially-connected group of individuals. Our approach to friendsourcing is to design socially enjoyable interactions that produce the desired information as a side effect. We focus our analysis around Collabio, a novel social tagging game that we developed to encourage friends to tag one another within an online social network. Collabio encourages friends, family, and colleagues to generate useful information about each other. We describe the design space of incentives in social tagging games and evaluate our choices by a combination of usage log analysis and survey data. Data acquired via Collabio is typically accurate and augments tags that could have been found on Facebook or the Web. To complete the arc from data collection to application, we produce a trio of prototype applications to demonstrate how Collabio tags could be utilized: an aggregate tag cloud visualization, a personalized RSS feed, and a question and answer system. The social data powering these applications enables them to address needs previously difficult to support, such as question answering for topics comprehensible only to a few of a user’s friends.

We propose that collaborative software visualization can improve team software maintenance. We first review how visualization can support software maintenance from the perspectives of system understanding, process understanding and software evolution. From this, we conclude that visualization tools are rarely designed to provide explicit support for collaborative authoring and sharing of views. We then provide an overview of research from a Computer Supported Cooperative Work perspective, and propose that this research should be applied to software visualization. We explore the opportunities and challenges this research focus presents and conclude that more attention paid to the social aspects of software visualization should improve both individual and team processes in software maintenance. 1.

Designers of mobile, social systems must carefully think about how to help their users manage spatial, semantic, and social modes of navigation. Here, we describe our deployment of MobiTags, a system to help museum visitors interact with a collection of “open storage ” exhibits, those where the museum provides little curatorial information. MobiTags integrates social tagging, art information, and a map to support navigation and collaborative curation of these open storage collections. We studied 23 people’s use of MobiTags in a local museum, combining interview data with device use logs and tracking of people’s movements to understand how MobiTags affected their navigation and experience in the museum. Despite a lack of social cues, people feel a strong sense of social presence—and social pressure—through seeing others ’ tags. The tight coupling of tags, item information, and map features also supported a rich set of practices around these modes of navigation. Author Keywords Mobile tagging, museum, experience, presence, navigation

Since its inception, a large amount of software has been written in Java and surprisingly little is known about the structure of Java programs in the wild. There are very few software visualization tools for analytical reasoning of Java software. We are creating a visual software analytics tool that will help to characterize our Java software corpus. Our tool will help to provide insight into a collection of Java programs, detect the expected, and discover the unexpected.

Dido is an application (and application development environment) in a web page. It is a single web page containing rich structured data, an AJAXy interactive visualizer/editor for that data, and a “metaeditor ” for WYSIWYG editing of the visualizer/editor. Historically, users have been limited to the data schemas, visualizations, and interactions offered by a small number of heavyweight applications. In contrast, Dido encourages and enables the end user to edit (not code) in his or her web browser a distinct ephemeral interaction “wrapper ” for each data collection that is specifically suited to its intended use. Dido’s active document metaphor has been explored before but we show how, given today’s web infrastructure, it can be deployed in a small self-contained HTML document without touching a web client or server. ACM Classification: H5.2 [Information interfaces and presentation]: