Browsing by Author "Ceneda, Davide"

Now showing 1 - 5 of 5
  • Thumbnail Image
    Item
    Guide Me in Analysis: A Framework for Guidance Designers
    (© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Ceneda, Davide; Andrienko, Natalia; Andrienko, Gennady; Gschwandtner, Theresia; Miksch, Silvia; Piccolotto, Nikolaus; Schreck, Tobias; Streit, Marc; Suschnigg, Josef; Tominski, Christian; Benes, Bedrich and Hauser, Helwig
    Guidance is an emerging topic in the field of visual analytics. Guidance can support users in pursuing their analytical goals more efficiently and help in making the analysis successful. However, it is not clear how guidance approaches should be designed and what specific factors should be considered for effective support. In this paper, we approach this problem from the perspective of guidance designers. We present a framework comprising requirements and a set of specific phases designers should go through when designing guidance for visual analytics. We relate this process with a set of quality criteria we aim to support with our framework, that are necessary for obtaining a suitable and effective guidance solution. To demonstrate the practical usability of our methodology, we apply our framework to the design of guidance in three analysis scenarios and a design walk‐through session. Moreover, we list the emerging challenges and report how the framework can be used to design guidance solutions that mitigate these issues.
  • Thumbnail Image
    Item
    A Methodology for Task-Driven Guidance Design
    (The Eurographics Association, 2023) Pérez-Messina, Ignacio; Ceneda, Davide; Miksch, Silvia; Angelini, Marco; El-Assady, Mennatallah
    Mixed-initiative Visual Analytics (VA) systems are becoming increasingly important; however, the design of such systems still needs to be formulated. We present a methodology to aid and structure the design of guidance for mixed-initiative VA systems consisting of four steps: (1) defining the target of analysis, (2) identifying the user search tasks, (3) describing the system guidance tasks, and (4) specifying which and when guidance is provided. In summary, it specifies a space of possible user tasks and then maps it to the corresponding space of guidance tasks, using recent VA task typologies for guidance and visualizations. We illustrate these steps through a case study in a real-world model-building task involving decision-making with unevenlyspaced time-oriented data. Our methodology's goal is to enrich existing VA systems with guidance, being its output a structured description of a complex guidance task schema.
  • Thumbnail Image
    Item
    Persistent Interaction: User-Generated Artefacts in Visual Analytics
    (The Eurographics Association, 2024) Pérez-Messina, Ignacio; Ceneda, Davide; Schetinger, Victor; Miksch, Silvia; El-Assady, Mennatallah; Schulz, Hans-Jörg
    While traditional approaches in visual analytics (VA) prioritize insight generation and knowledge discovery, we argue that user-generated artefacts-annotations, model parameters, subset selections, spatializations, and other constructs-constitute a significant outcome of the analytical process. Drawing from theoretical models in VA literature, we introduce persistent interaction as techniques capturing user decisions. These interactions, called operations, provide a formalization of how users attach subjective judgments to datasets, condensing this input into artefacts serving specific purposes within broader workflows. We provide a description and classification of persistent interaction techniques and outcomes, demonstrating their practical implications in VA systems for system design, information transferability, and guidance capabilities.
  • Thumbnail Image
    Item
    A Review of Guidance Approaches in Visual Data Analysis: A Multifocal Perspective
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Ceneda, Davide; Gschwandtner, Theresia; Miksch, Silvia; Laramee, Robert S. and Oeltze, Steffen and Sedlmair, Michael
    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.
  • Thumbnail Image
    Item
    A Typology of Guidance Tasks in Mixed-Initiative Visual Analytics Environments
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Pérez-Messina, Ignacio; Ceneda, Davide; El-Assady, Mennatallah; Miksch, Silvia; Sperrle, Fabian; Borgo, Rita; Marai, G. Elisabeta; Schreck, Tobias
    Guidance has been proposed as a conceptual framework to understand how mixed-initiative visual analytics approaches can actively support users as they solve analytical tasks. While user tasks received a fair share of attention, it is still not completely clear how they could be supported with guidance and how such support could influence the progress of the task itself. Our observation is that there is a research gap in understanding the effect of guidance on the analytical discourse, in particular, for the knowledge generation in mixed-initiative approaches. As a consequence, guidance in a visual analytics environment is usually indistinguishable from common visualization features, making user responses challenging to predict and measure. To address these issues, we take a system perspective to propose the notion of guidance tasks and we present it as a typology closely aligned to established user task typologies. We derived the proposed typology directly from a model of guidance in the knowledge generation process and illustrate its implications for guidance design. By discussing three case studies, we show how our typology can be applied to analyze existing guidance systems. We argue that without a clear consideration of the system perspective, the analysis of tasks in mixed-initiative approaches is incomplete. Finally, by analyzing matchings of user and guidance tasks, we describe how guidance tasks could either help the user conclude the analysis or change its course.