A Review of Guidance Approaches in Visual Data Analysis: A Multifocal Perspective

Abstract

Visual data analysis can be envisioned as a collaboration of the user and the computational system with the aim of completing a given task. Pursuing an effective system‐user integration, in which the system actively helps the user to reach his/her analysis goal has been focus of visualization research for quite some time. However, this problem is still largely unsolved. As a result, users might be overwhelmed by powerful but complex visual analysis systems which also limits their ability to produce insightful results. In this context, guidance is a promising step towards enabling an effective mixed‐initiative collaboration to promote the visual analysis. However, the way how guidance should be put into practice is still to be unravelled. Thus, we conducted a comprehensive literature research and provide an overview of how guidance is tackled by different approaches in visual analysis systems. We distinguish between guidance that is provided by the system to support the user, and guidance that is provided by the user to support the system. By identifying open problems, we highlight promising research directions and point to missing factors that are needed to enable the envisioned human‐computer collaboration, and thus, promote a more effective visual data analysis.

LightGuider: Guiding Interactive Lighting Design using Suggestions, Provenance, and Quality Visualization

“…Moreover, all participants expressed the wish to fine-tune the suggestion generation, or as P2 phrased it: "...means to guide the guidance". While we did not yet include such a functionality, integrating mechanisms for designers to provide guidance themselves, and thus, to reveal the whole potential of guidance as a mixed-initiative process (as discussed by Ceneda et al [7]), in which the guidance mechanism dynamically adjusts the provided suggestions to the designer's actions and feedback is an interesting research challenge stated by Ceneda et al [8]. In particular, our study participants wanted to be able to set restrictions to limit the parameter space for suggested modeling steps, and thus, to steer the suggestions into a desired direction.…”

Guide Me in Analysis: A Framework for Guidance Designers

“…In summary, the literature seems to be in agreement on the potential benefits and the general requirements of guidance. However, there is no unified framework for designing effective guidance in VA. Based on a thorough inspection of existing work [CGM19], our research aims to narrow this gap in the literature by proposing a design framework built around questions that a guidance designer has to address when developing guidance for VA.…”

“…Motion and animation could also be used to communicate guidance [JLJC05]. However, glyphs and visual artefacts are the most common way for encoding guidance suggestions [CGM19].…”

“…Thus, our examples demonstrate practical solutions to specific issues, rather than guidance designs for comprehensive systems. This is a common issue in the literature: Existing works do not provide any comprehensive guidance solution or complete design examples [CGM19]. In the following, to overcome such issue and to ease the application of our framework to other contexts, we describe a comprehensive and complete step‐by‐step design process.…”

“…The main aim of guidance is to ease problematic situations and mitigate issues that might hinder the analyst from achieving results, generating insights, and in the end producing new knowledge. Recent studies show that including guidance in the analysis may be beneficial for the user [CGMT18, MSDK12, HB05, JLJC05, CGM19, CAS*18]. Interest in guidance is quite recent and research has just started scratching the surface of this field.…”