A Design Framework for Instrumenting Analytic Provenance for Problem-Solving Tasks

Autor: Pierre Morizet-Mahoudeaux, Lingxue Yang, Assia Mouloudi, Anne Guenand
Přispěvatelé: Heuristique et Diagnostic des Systèmes Complexes [Compiègne] (Heudiasyc), Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS), Roberval (Roberval), Université de Technologie de Compiègne (UTC)
Rok vydání: 2018
Předmět:
Zdroj: Advances in Intelligent Systems and Computing ISBN: 9789811086113
7th International Conference on Kansei Engineering and Emotion Research 2018 (KEER 2018)
7th International Conference on Kansei Engineering and Emotion Research 2018 (KEER 2018), Mar 2018, Kuching, Sarawak, Malaysia. pp.633-643, ⟨10.1007/978⟩
DOI: 10.1007/978-981-10-8612-0_66
Popis: International audience; In the context of analytics applications, the recall of interaction historyoften happens when users are identifying the root causes of a given problembased on a visual analytics task, which can be interrupted or suspended. The researchof analytic provenance focuses on retrieving users’ interaction history,reinstating their reasoning process so that they can quickly resume an interruptedor suspended task. Although many visualization analytic tools are available,they lack extended capabilities for giving access to users’ interaction history ina natural coupling with their actions. We propose a design framework for instrumentinganalytic provenance in a mode allowing users to “re-commit” totheir tasks. We realize a first experiment to see how one's history activities hasan impact on the way he/she resolves the task. We investigate the interactionpossibilities of two design approaches: the user interface (UI) design in whichthe history path is considered as “put down” in the environment; the user experience(UX) design considers it as a coupling device between the user and theworld, being “in hand” mode. The first part of our analysis shows that users usethe history path for supporting their reasoning process. However, the indirectcoupling between users’ actions and provenance function keeps them outside ofthe history path so that they cannot easily link it to their current problem. Wehypothesize that the "in hand" mode of interaction history will allow a naturalcoupling between a user’s action and the provenance function, which may leadto a positive user experience. We then propose the lines for designing dynamichistory path interaction tools.
Databáze: OpenAIRE