Abstract
Statistical graphics, and data visualization, play an essential but under-utilized, role for data analysis in animal science, and also to visually illustrate the concepts, ideas, or outputs of research and in curricula. The recent rise in web technologies and ubiquitous availability of web browsers enables easier sharing of interactive and dynamic graphics. Interactivity and dynamic feedback enhance human–computer interaction and data exploration. Web applications such as decision support systems coupled with multimedia tools synergize with interactive and dynamic graphics. However, the importance of graphics for effectively communicating data, understanding data uncertainty, and the state of the field of interactive and dynamic graphics is underappreciated in animal science. To address this gap, we describe the current state of graphical methodology and technology that might be more broadly adopted. This includes an explanation of a conceptual framework for effective graphics construction. The ideas and technology are illustrated using publicly available animal datasets. We foresee that many new types of big and complex data being generated in precision livestock farming create exciting opportunities for applying interactive and dynamic graphics to improve data analysis and make data-supported decisions.
Highlights
Graphics in science are visual representations often employed to illustrate the concepts, ideas, or outputs of research
We foresee that many new types of big and complex data being generated in precision livestock farming create exciting opportunities for applying interactive and dynamic graphics to improve data analysis and make data-supported decisions
In 1987, Becker et al (1987) stated that interactive and dynamic graphics would be ubiquitous in the future
Summary
Graphics in science are visual representations often employed to illustrate the concepts, ideas, or outputs of research. The user creates a blue-shaded rectangular box interactively using a mouse in the scatter plot and selects the data points of interest (Figure 10A) This triggers dynamic updates of the box plot and the table to display information about only the selected data points. Gutiérrez et al (2019) provided a topical systematic review of visualization techniques applied to supporting decision-making processes in agriculture They classified a number of journal articles according to their application areas, targeting endusers, design methodologies, visualization techniques used to communicate data, and usability based on a human–computer interaction perspective. They reported that 2D geo-spatial maps, heatmaps, time-series plots, and histograms were dominantly used as visualization techniques in agriculture. The software allows users to quantify the sustainability status of their farm operations by collecting herd data and inventory records
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