Nathalie Henry Riche

Priyan Vaithilingam, Elena L. Glassman, Nathalie Henry Riche et al.

People working with data often move their data across multiple applications, because they rely on these apps' complementing user experiences to best complete their tasks. Since traditional copy-and-paste approaches do not accommodate diverse table representations adopted by different apps, users spend considerable effort to reconstruct data formats and visual representations, making cross-app workflows costly. For example, when transferring a spreadsheet table with conditional formatting to a markup document, users spend substantial time translating its structure into appropriate tags and manually reformat color. This paper introduces MagicCopy, an AI-powered cross-app copy-and-paste, leveraging source and target contexts and user-specified instructions in natural language to automatically extract, parse, transform, and (re)format data from one app to another. In a study with sixteen participants, users quickly learned and applied MagicCopy to move data across three pairs of tools. Participants further explored diverse applications of MagicCopy to support more streamlined crossed-application interaction in their workflows.

Arjun Srinivasan, Bongshin Lee, Nathalie Henry Riche et al.

While tablet devices are a promising platform for data visualization, supporting consistent interactions across different types of visualizations on tablets remains an open challenge. In this paper, we present multimodal interactions that function consistently across different visualizations, supporting common operations during visual data analysis. By considering standard interface elements (e.g., axes, marks) and grounding our design in a set of core concepts including operations, parameters, targets, and instruments, we systematically develop interactions applicable to different visualization types. To exemplify how the proposed interactions collectively facilitate data exploration, we employ them in a tablet-based system, InChorus that supports pen, touch, and speech input. Based on a study with 12 participants performing replication and fact-checking tasks with InChorus, we discuss how participants adapted to using multimodal input and highlight considerations for future multimodal visualization systems.

Michel Pahud, Eyal Ofek, Nathalie Henry Riche et al.

We propose a set of techniques leveraging mobile devices as lenses to explore, interact and annotate n-dimensional data visualizations. The democratization of mobile devices, with their arrays of integrated sensors, opens up opportunities to create experiences for anyone to explore and interact with large information spaces anywhere. In this paper, we propose to revisit ideas behind the Chameleon prototype of Fitzmaurice et al. initially envisioned in the 90s for navigation, before spatially-aware devices became mainstream. We also take advantage of other input modalities such as pen and touch to not only navigate the space using the mobile as a lens, but interact and annotate it by adding toolglasses.