Characterizing Data Visualization Literacy for Standardization: A Systematic Literature Review
Year: 2025
Type: review
Study design: Systematic Review
Abstract: With the advent of the data era and of new, more intelligent interfaces for supporting decision-making, there is a growing need to define, model and assess human ability and data visualization usability for better encoding and decoding of data patterns. Data Visualization Literacy (DVL) is the ability to encode and decode data into and from a visual language. Although this ability and its measurement are crucial for advancing human knowledge and decision capacity, they have seldom been investigated, let alone systematically. To address this gap, this paper presents a systematic literature review comprising 45 reports on DVL, analyzed using the PRISMA methodology. Our results include the identification of the purposes of DVL, its satellite aspects, the models proposed, and the assessments designed to evaluate the degree of DVL of people. Eventually, we devise many research directions including, among the most challenging, the definition of a (standard) unifying construct and protocol for DVL.
Source: IEEE Access
Authors: Sara Beschi, Davide Falessi, Silvia Golia, Angela Locoro
Institutions: University of Brescia, University of Rome Tor Vergata
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,075
OpenAlex ID: W4409310934