Overview of Data Visualization

Yunhan Zeng Shangru Yang Shengjia Cao + 1 lainnya

1 Januari 2021

In recent years, researchers at home and abroad have accumulated a lot of experience in the research of data visualization technology, and they have played animportant role in scientific discovery, medical diagnosis, business decision-making, and engineering applications. As a library developed using Python language, Matplotlib has a concise language, high drawing accuracy, and simple and easy-to-understand code. This article first introduces data visualization and related technologies used and then uses Python’s Matplotlib library and pyecharts library to realize data visualization. Through representative examples, combined with the use of correct charts, visual processing of data in different fields, so as to further analyze the effect of visualization.

Zezhong Wang Lovisa Sundin Dave Murray-Rust + 1 lainnya

18 Januari 2020

This paper introduces the concept of 'cheat sheets' for data visualization techniques, a set of concise graphical explanations and textual annotations inspired by infographics, data comics, and cheat sheets in other domains. Cheat sheets aim to address the increasing need for accessible material that supports a wide audience in understanding data visualization techniques, their use, their fallacies and so forth. We have carried out an iterative design process with practitioners, teachers and students of data science and visualization, resulting six types of cheat sheet (anatomy, construction, visual patterns, pitfalls, false-friends and well-known relatives) for six types of visualization, and formats for presentation. We assess these with a qualitative user study using 11 participants that demonstrates the readability and usefulness of our cheat sheets.

Chaoli Wang

1 Juli 2022

This article describes the motivation, design, and evaluation of the VisVisual toolkit to engage students in learning essential visualization concepts, algorithms, and techniques. The toolkit includes four independent components: 1) VolumeVisual, 2) FlowVisual, 3) GraphVisual, and 4) TreeVisual, covering scalar and vector data visualization in scientific visualization and graph and tree layouts in information visualization. Complementary to the toolkit design is resource development, aiming to help instructors integrate VisVisual into their curriculum.

Richard Hill Tariq A. A. Alsboui H. M. Shakeel + 2 lainnya

2022

Data visualization is a powerful skill for the demonstration of meaningful data insights in an interactive and effective way. In this survey article, we collected 70 articles from last five years (2017-2022) to identify, classify, and investigate the various scopes, aspects and theories of data visualization. We also investigated the powerful applications of data visualization in various domains and fields such as visualization apps for health sector, Internet of things (IoTs), business dashboards, urban traffic management, smart buildings and environmental data visualization. However, after thorough investigation and classification, we conclude that, a comprehensive study is still missing about interactive, effective and efficient data visualization survey explaining basic current state-of-the-art best interactive visualization techniques, web-based tools and platforms, best performance theories, data structures and algorithms. In this survey article, we perform a thorough investigation to fill the gap on theoretical, analytical, statistical models and techniques for improving the performance of visualization. Current primary and domain specific future challenges are also reviewed, and related future research directions and opportunities are recommended.

Shakira Khan

6 Desember 2021

Data visualization is graph representation of data. It produces interactive graphs that explain the relationships among the data to viewers of the graph. The aim of data visualization is to communicate data value clearly and effectively through graphs [1]. Here we take the advantage of data visualization to explore the countries dataset to provide a holistic and interpretive view about the world. In addition to examine some hypotheses about gross domestic product (GDP) and Literacy and more of the countries effects on different factors showing on the dataset such as the literacy and the migration.