This paper attempts to identify and characterize some context-dependent dimensions of Human-Data Visualization Interaction that are crucial to estimate the complexity of data-driven decision making. These dimensions are only partly related to off-line considerations such as the kind of charts, the data represented, and the like, and are mapped with operationalization constructs for their characterization and assessment. A what-if scenario in an industrial company is the starting point to reflect upon living constraints, such as the level of expertise in visual analytics of managers (the so-called Visual Information Literacy), the strategy that drives the decision process, and the flexibility and adaptability of the technology design to the data characterizing the decisions and both the previous aspects. How can we relate these three aspects for a better estimate of the data-driven decision-making flaws and complexity? Some hypotheses are proposed here.

Mapping Context-Dependent Dimensions of Human-Data Viz Interaction

Sara Beschi;Angela Locoro
2026-01-01

Abstract

This paper attempts to identify and characterize some context-dependent dimensions of Human-Data Visualization Interaction that are crucial to estimate the complexity of data-driven decision making. These dimensions are only partly related to off-line considerations such as the kind of charts, the data represented, and the like, and are mapped with operationalization constructs for their characterization and assessment. A what-if scenario in an industrial company is the starting point to reflect upon living constraints, such as the level of expertise in visual analytics of managers (the so-called Visual Information Literacy), the strategy that drives the decision process, and the flexibility and adaptability of the technology design to the data characterizing the decisions and both the previous aspects. How can we relate these three aspects for a better estimate of the data-driven decision-making flaws and complexity? Some hypotheses are proposed here.
2026
9783031953330
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/634585
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