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 visualizations usability for a better encoding and decoding of data patterns. Data Visualization Literacy (DVL) is the ability of encoding and decoding 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 43 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 of DVL.

翻译：随着数据时代的到来，以及支持决策的新型智能界面的出现，越来越需要定义、建模和评估人类能力与数据可视化的可用性，以实现数据模式更优的编码与解码。数据可视化素养（DVL）是将数据编码为视觉语言以及从视觉语言解码数据的能力。尽管这种能力及其测量对于推进人类知识和决策能力至关重要，却鲜有研究对其进行探讨，更遑论系统性的研究。为弥补这一空白，本文采用PRISMA方法对43篇关于DVL的研究报告进行了系统性文献综述。我们的研究成果包括：识别了DVL的目的、其相关维度、提出的模型，以及为评估人群DVL水平而设计的测评工具。最终，我们提出了多项研究方向，其中最富挑战性的方向之一是建立DVL的（标准化）统一理论框架。