Vega-Lite combines a traditional grammar of graphics, providing visual encoding rules and a composition algebra for layered and multi-view displays, with a novel grammar of interaction, that enables rapid specification of interactive data visualizations.
Abstract:
We present Vega-Lite, a high-level grammar that enables rapid specification of interactive data visualizations. Vega-Lite combines a traditional grammar of graphics, providing visual encoding rules and a composition algebra for layered and multi-view displays, with a novel grammar of interaction. Users specify interactive semantics by composing selections. In Vega-Lite, a selection is an abstraction that defines input event processing, points of interest, and a predicate function for inclusion testing. Selections parameterize visual encodings by serving as input data, defining scale extents, or by driving conditional logic. The Vega-Lite compiler automatically synthesizes requisite data flow and event handling logic, which users can override for further customization. In contrast to existing reactive specifications, Vega-Lite selections decompose an interaction design into concise, enumerable semantic units. We evaluate Vega-Lite through a range of examples, demonstrating succinct specification of both customized interaction methods and common techniques such as panning, zooming, and linked selection.
TL;DR: A process model for dashboard onboarding is proposed that formalizes and unifies a variety of onboarding strategies employed, including videos, narration, and interactive tutorials, and introduces the onboarding loop alongside the dashboard usage loop.
TL;DR: PVD, a system that visualization designers can use to co-design the interface and system architecture of scalable and expressive visualization, is demonstrated.
TL;DR: In this paper , the authors present the first characterisation of distributed tracing visualisation through a qualitative interview study with six practitioners from two large internet companies, using grounded theory coding to establish users, extract concrete use cases and identify shortcomings of existing distributed tracing tools.
TL;DR: This research proposes Diököl, a programming environment developed with Lua and OpenVG to facilitate the learning process of programmers with little experience in the implementation of visualizations to make it an efficient alternative to learning about and program visualizations.
TL;DR: This paper draws together nine strategies for creative visualization activities to provide an initial starting point of methods and strategies to craft creative visualisation learning activities, and provide a foundation for developing best practices in visualization education.
TL;DR: This work shows how representational transparency improves expressiveness and better integrates with developer tools than prior approaches, while offering comparable notational efficiency and retaining powerful declarative components.
TL;DR: The approach is based on graphical perception—the visual decoding of information encoded on graphs—and it includes both theory and experimentation to test the theory, providing a guideline for graph construction.
TL;DR: APT as discussed by the authors is an application-independent presentation tool that automatically designs effective graphical presentations (such as bar charts, scatter plots, and connected graphs) of relational information, based on the view that graphical presentations are sentences of graphical languages.
TL;DR: This work is an unprecedented attempt to synthesize principles of graphic communication with the logic of standard rules applied to writing and topography in an array of more than 1,000 maps and diagrams.
TL;DR: Seven general categories of interaction techniques widely used in Infovis are proposed, organized around a user's intent while interacting with a system rather than the low-level interaction techniques provided by a system.
Q1. What are the contributions in "Vega-lite: a grammar of interactive graphics" ?
The authors present Vega-Lite, a high-level grammar that enables rapid specification of interactive data visualizations. The Vega-Lite compiler automatically synthesizes requisite data flow and event handling logic, which users can override for further customization.
Q2. What are the future works in "Vega-lite: a grammar of interactive graphics" ?
One promising avenue for future work is to develop models and techniques to analogously recommend suitable interaction methods for given visualizations and underlying data types.
Q3. What is the function that applies the selection against the backing datasets?
The filterWith data transform applies the selection against the backing datasets such that only data values that fall within the selection are displayed.
Q4. What are the primary features of a low-level grammar?
Low-level grammars such as Protovis [3], D3 [4], and Vega [22] are useful for explanatory data visualization or as a basis for customized analysis tools, as their primitives offer fine-grained control.
Q5. What is the function that offsets the spatial properties of the backing points?
by): Offsets the spatial properties (or corresponding data fields) of backing points by an amount determined by the coordinates of the sequenced events.
Q6. What is the process of merging components?
Once the necessary components have been built, the compiler performs a bottom-up traversal of the model tree to merge redundant components.
Q7. How does Vega-Lite support expressive interaction methods?
To support expressive interaction methods, the authors first contribute an algebra to compose singleview Vega-Lite specifications into multi-view displays using layer, concatenate, facet and repeat operators.
Q8. What is the function that augments the selection’s event processing?
nearest(): Computes a Voronoi decomposition, and augments the selection’s event processing, such that the data value or visual elementnearest the selection’s triggering event is selected (approximating a Bubble Cursor [11]).
Q9. What is the syntax for creating a composite view?
Their formal definitions are instantiated in a JSON (JavaScript Object Notation) syntax, as shown in Fig. 2.Given multiple unit specifications, composite views can be created using a set of composition operators.
Q10. How can you adapt techniques to a different design?
Specifying common techniques can be time-consuming, requiring tens of lines of JSON, and it is difficult to know how to adapt techniques in pursuit of alternative designs.