Techniques d'interaction 'phygitales' pour l'exploration de systèmes informationnels complexes

Durant cette dernière décennie, la quantité de données numériques n'a cessé d'augmenter. Ces données provenant de l'Internet des Objets ou de smartphones permettent aux utilisateurs de comprendre et d'analyser leur santé, leur mode de vie ou encore leur consommation énergétique, et aux différentes institutions (villes, campus, promoteurs immobiliers) de gérer le flux de population, le trafic routier ou les pertes énergétiques dans les bâtiments administrés. Le domaine de la "ville intelligente" en tire particulièrement profit. Il est donc capital de mettre à disposition des visualisations interactives de ces données pour pouvoir faire émerger des connaissances et faciliter la prise de décision. Une approche récente propose de représenter ces données proches de l'objet qui les capte ou les produit. Cependant, ce domaine est encore assez récent et il reste de nombreux défis à explorer. Un des défis majeurs identifié par Thomas et collab. (Thomas et al., 2018) est le développement et la conception de techniques d'interaction pour faciliter l'analyse de données situées. L'objectif de nos travaux de thèse est de concevoir et d'évaluer des solutions interactives tirant profit du référent physique pour interagir avec des données numériques situées en se focalisant sur une tâche interactive fondamentale en IHM : la sélection. Dans ce manuscrit nous abordons cette tâche selon une approche fonctionnelle et une approche conceptuelle.Over the past decade, the amount of digital data has been increasing. This data from the Internet of Things or smartphones allows users to understand and analyse their health, lifestyle or energy consumption, and different institutions (cities, campuses, real estate developers) to manage the flow of people, road traffic or energy losses in the buildings they manage. One particular topic that benefits from this is the "smart city". It is therefore essential to make interactive visualisations of this data available in order to generate knowledge and facilitate decision-making. A recent approach proposes to represent these data close to the object that captures or produces them. However, this field is still quite new and there are still many challenges to explore. One of the major challenges identified by Thomas et al. (Thomas et al., 2018) is the development and design of interaction techniques to facilitate the analysis of situated data. The objective of our thesis work is to design and evaluate interactive solutions leveraging the physical referent to interact with situated digital data by focusing on a fundamental interactive task in HCI: selection. In this manuscript we study this task from both a practical and a conceptual approach

Use of Landmarks to Improve Spatial Learning and Revisitation in Computer Interfaces

Efficient spatial location learning and remembering are just as important for two-dimensional Graphical User Interfaces (GUI) as they are for real environments where locations are revisited multiple times. Rapid spatial memory development in GUIs, however, can be difficult because these interfaces often lack adequate landmarks that have been predominantly used by people to learn and recall real-life locations. In the absence of sufficient landmarks in GUIs, artificially created visual objects (i.e., artificial landmarks) could be used as landmarks to support spatial memory development of spatial locations. In order to understand how spatial memory development occurs in GUIs and explore ways to assist users’ efficient location learning and recalling in GUIs, I carried out five studies exploring the use of landmarks in GUIs – one study that investigated interfaces of four standard desktop applications: Microsoft Word, Facebook, Adobe Photoshop, and Adobe Reader, and other four that tested artificial landmarks augmented two prototype desktop GUIs against non-landmarked versions: command selection interfaces and linear document viewers; in addition, I tested landmarks’ use in variants of these interfaces that varied in the number of command sets (small, medium, and large) and types of linear documents (textual and video). Results indicate that GUIs’ existing features and design elements can be reliable landmarks in GUIs that provide spatial benefits similar to real environments. I also show that artificial landmarks can significantly improve spatial memory development of GUIs, allowing support for rapid spatial location learning and remembering in GUIs. Overall, this dissertation reveals that landmarks can be a valuable addition to graphical systems to improve the memorability and usability of GUIs