The Applied Semiotics of Visual Modelling

视觉建模的应用符号学

• 批准号: EP/R043949/1
• 负责人: Jim Burton
• 金额: $ 9.1万
• 依托单位: University of Brighton
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FR043949%2F1
• 关键词: Applied; Semiotics; Visual; Modelling

In the digital age, every member of society needs to process, interrogate and understandcomplex data. In addition, more and more of us take part in or depend on specialised fields in whichinformation has to be absolutely precise, such as the design and creation ofsoftware. Graphical forms of communication are widely recognised as an effective way ofcommunicating certain types of information, whether through a simple data visualisation such asa bar chart accompanying a newspaper article, or through a complex diagram which specifies acomputer system. Thus, there are many benefits inherent to understanding how these graphicalforms work, and what makes them more or less effective (relative to, say, the written word) forcertain tasks.Semiotics is the perspective that analyses these graphical notations as so many arrangements ofsigns. The field of semiotics began with the work of Charles Peirce, who provided a richlythorough analysis of the types of signs, their components, the relations of the components toone another and so on. Despite several initial approaches and numerous differing perspectiveson the same problem, no one has yet applied the semiotic method in depth to the analysis ofdiagrammatic languages to make predictions of their cognitive potentials; that is what thisproject sets out to do.We will begin by analysing several widely used data visualisations, including those which areused interactively, from a Peircean perspective. That is, we will use Peirce's classificationof types of sign and their correlation with different types of information to make predictionsabout the potential effectiveness and suitability of the visualisations for particulartasks. We will correlate these predictions with findings from cognitive science and HCI, wheresuch visualisations are studied from different points of view. This evaluation will result inguidelines for the use of existing techniques and generalised criteria for the design of datavisualisations. The next step in our project is to use the frame of reference explained above to analyse thelogic of concept diagrams. Concept diagrams were designed for knowledge representation and havebeen found to be more effective than symbolic alternatives for some tasks. A diagrammatic logicis more than data visualisation; it is a precisely defined graphical notation (e.g. Venndiagrams or concept diagrams), together with a set of rules for transforming and possiblycombining diagrams in logically valid ways. Although they are not a panacea, when diagrammaticlogics are used in place of "traditional" symbolic alternatives, certain advantages can arise:in some circumstances a diagram effectively reveals more information than was required for itsconstruction. This is a key source of the power of diagrammatic communication, wherebyinformation is revealed "by construction" that would need to be inferred as a result of somechain of reasoning if the information were presented in a symbolic language. The means by whichthis takes place are a central part of Peircean semiotics, and are also of great interest todisciplines outside semiotics, such as human-computer interaction and cognitive science. One ofour contributions will be our attempt to reconcile and find agreements or inconsistencies amongthese different accounts of the "natural" or "intuitive" power of diagrams and datavisualisation. In this way, we aim to enable people to make better use of existing notationsand design more effective notations for the future.

在数字时代，社会的每个成员都需要处理、询问和理解复杂的数据。此外，我们中越来越多的人参与或依赖于信息必须绝对精确的专业领域，例如软件的设计和创建。图形形式的通信被广泛认为是一种有效的方式ofcommunicating某些类型的信息，无论是通过一个简单的数据可视化，阿萨条形图伴随着报纸文章，或通过一个复杂的图表，指定计算机系统。因此，理解这些图形形式是如何工作的，以及是什么使它们在某些任务上更有效或更不有效（相对于，比如说，书面文字），有许多内在的好处。符号学是分析这些图形符号作为符号的许多安排的视角。符号学领域始于查尔斯·皮尔士的著作，他对符号的类型、符号的组成部分、符号组成部分之间的关系等进行了非常透彻的分析。尽管对同一问题有几种初步的研究方法和许多不同的观点，但还没有人将符号学方法深入地应用于分析图形语言，以预测其认知潜力。我们将开始分析几种广泛使用的数据可视化，包括那些交互式使用的，从皮尔斯的角度。也就是说，我们将使用Peirce对符号类型的分类及其与不同类型信息的相关性来预测特定任务的可视化的潜在有效性和适用性。我们将把这些预测与认知科学和人机交互的发现相关联，从不同的角度研究这些可视化。该评估将为现有技术的使用提供指导方针，并为数据可视化的设计提供通用标准。我们项目的下一步是使用上面解释的参考框架来分析概念图的逻辑。概念图是为知识表示而设计的，并且在某些任务中被发现比符号替代方案更有效。一个图表逻辑图比数据可视化;它是一个精确定义的图形符号（例如文氏图或概念图），以及一套规则，用于转换和可能的组合图表在逻辑上有效的方式。虽然它们不是万灵药，但当使用图解逻辑代替“传统”的符号替代品时，某些优势可能会出现：在某些情况下，图表有效地揭示了比其构建所需的更多的信息。这是图解交流力量的一个关键来源，通过这种方式，信息被“通过构造”揭示出来，如果信息是用符号语言呈现的，那么需要通过某种推理链来推断。这是皮尔士符号学的核心部分，也是符号学之外的学科，如人机交互和认知科学的兴趣所在。我们的贡献之一将是我们试图调和和找到协议或不一致的这些不同的帐户的“自然”或“直观”的权力图表和数据可视化。通过这种方式，我们的目标是使人们能够更好地利用现有的符号，并为未来设计更有效的符号。

项目成果

Diagrams for Navya-Nyaya

Navya-Nyaya 图表

• DOI: 10.1007/s10781-020-09419-0
• 发表时间: 2020
• 期刊: Journal of Indian Philosophy
• 影响因子: 0.3
• 作者: Burton J