Contextual in situ help for visual data interfaces

IF 1.8 4区计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Information Visualization Pub Date : 2022-09-09 DOI:10.1177/14738716221120064

Pramod Chundury, M. A. Yalçın, Jon Crabtree, A. Mahurkar, Lisa M Shulman, N. Elmqvist

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引用次数: 2

Abstract

As the complexity of data analysis increases, even well-designed data interfaces must guide experts in transforming their theoretical knowledge into actual features supported by the tool. This challenge is even greater for casual users who are increasingly turning to data analysis to solve everyday problems. To address this challenge, we propose data-driven, contextual, in situ help features that can be implemented in visual data interfaces. We introduce five modes of help-seeking: (1) contextual help on selected interface elements, (2) topic listing, (3) overview, (4) guided tour, and (5) notifications. The difference between our work and general user interface help systems is that data visualization provide a unique environment for embedding context-dependent data inside on-screen messaging. We demonstrate the usefulness of such contextual help through two case studies of two visual data interfaces: Keshif and POD-Vis. We implemented and evaluated the help modes with two sets of participants, and found that directly selecting user interface elements was the most useful.

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可视化数据接口的上下文原位帮助

随着数据分析的复杂性增加，即使是设计良好的数据接口也必须指导专家将他们的理论知识转化为工具支持的实际功能。对于那些越来越多地转向数据分析来解决日常问题的普通用户来说，这一挑战甚至更大。为了应对这一挑战，我们提出了数据驱动的、上下文相关的、可在可视化数据界面中实现的原位帮助特性。我们介绍了五种求助模式:(1)选定界面元素的上下文帮助，(2)主题列表，(3)概述，(4)导览，(5)通知。我们的工作与一般用户界面帮助系统的不同之处在于，数据可视化为在屏幕消息传递中嵌入上下文相关的数据提供了一个独特的环境。我们通过两个可视化数据接口的两个案例研究来证明这种上下文帮助的有用性:keshiif和POD-Vis。我们用两组参与者实现并评估了帮助模式，发现直接选择用户界面元素是最有用的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Information Visualization COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.40

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Information Visualization is essential reading for researchers and practitioners of information visualization and is of interest to computer scientists and data analysts working on related specialisms. This journal is an international, peer-reviewed journal publishing articles on fundamental research and applications of information visualization. The journal acts as a dedicated forum for the theories, methodologies, techniques and evaluations of information visualization and its applications. The journal is a core vehicle for developing a generic research agenda for the field by identifying and developing the unique and significant aspects of information visualization. Emphasis is placed on interdisciplinary material and on the close connection between theory and practice. This journal is a member of the Committee on Publication Ethics (COPE).