Vistrates: A Component Model for Ubiquitous Analytics

Abstract

Visualization tools are often specialized for specific tasks, which turns the user's analytical workflow into a fragmented process performed across many tools. In this paper, we present a component model design for data visualization to promote modular designs of visualization tools that enhance their analytical scope. Rather than fragmenting tasks across tools, the component model supports unification, where components-the building blocks of this model-can be assembled to support a wide range of tasks. Furthermore, the model also provides additional key properties, such as support for collaboration, sharing across multiple devices, and adaptive usage depending on expertise, from creating visualizations using dropdown menus, through instantiating components, to actually modifying components or creating entirely new ones from scratch using JavaScript or Python source code. To realize our model, we introduce VISTRATES, a literate computing platform for developing, assembling, and sharing visualization components. From a visualization perspective, Vistrates features cross-cutting components for visual representations, interaction, collaboration, and device responsiveness maintained in a component repository. From a development perspective, Vistrates offers a collaborative programming environment where novices and experts alike can compose component pipelines for specific analytical activities. Finally, we present several Vistrates use cases that span the full range of the classic "anytime" and "anywhere" motto for ubiquitous analysis: from mobile and on-the-go usage, through office settings, to collaborative smart environments covering a variety of tasks and devices.

InsideInsights: Integrating Data‐Driven Reporting in Collaborative Visual Analytics

“…The I nside I nsights system is a proof‐of‐concept of the design described above, implemented as a collaborative web‐based solution (http://github.com/90am/insideinsights). The system is build on top of the computational notebook Codestrates [RNA∗ 17] and the Vistrates component model [BMR∗ 19]. The novel combination of literate computing, hierarchical structure, provenance tracking, and presentation techniques allows for an iterative workflow interleaving composing analysis parts, capturing insights, and sharing the current progress.…”

“…The InsideInsights system supports a visual data‐flow approach, where a user performs sensemaking by assembling components to transform and visualize the data on an interactive canvas (Figure 1c). For this purpose, Vistrates [BMR∗ 19] provides a component template and a reactive data‐flow based execution model within a notebook environment. A component in Vistrates is essentially a piece of code that consumes one or multiple input sources, process the data (e.g., to create a view), and eventually provide an output.…”

“…The InsideInsights system is implemented with standard modern web technologies (JavaScript, HTML, CSS, etc.) as a top layer on the existing technology stack consisting of Webstrates [KEB∗ 15], Codestrates [RNA∗ 17, BRK18], and Vistrates [BMR∗ 19]. Codestrates is a JavaScript‐based computational notebook that provides collaborative editing of code through the DOM synchronization mechanism of Webstrates.…”

“…Thus, notebooks already possess qualities suitable for data‐driven communication and replicability. For these reasons, recent efforts have tried to enhance their functionality; for example, synchronous collaboration in notebooks is becoming the de facto standard [Goo18,RNA∗17], and reactive execution flows are also being supported [Obs18, BMR∗19]. Nevertheless, the linear document nature that is fundamental to all computational notebooks yields a tension between exploration and presentation [RTH18,KRA∗ 18], making it difficult to support non‐linear workflows that alternate between generating and presenting insights.…”

“…However, narration is typically a separate step in current tools, or done in completely different tools [BE18,NK18]. In our work, we build on the success of collaborative notebooks and pipeline‐based methods for data analysis by implementing our system on top of Codestrates [RNA∗17] and Vistrates [BMR∗19] (cf. Section 4.4).…”