Opportunities for information visualization in risk communication

Opportunities for information visualization in risk communication Ángel Vizoso Universidade de Santiago de Compostela ange[email protected] Gabriela Coronel-Salas Universidad Técnica Particular de Loja glc[email protected] Carlos Toural-Bran Universidade de Santiago de Compostela ca[email protected] Accepted version of the chapter published by Routledge How to cite: Vizoso, Á., Coronel-Salas, G. & Toural-Bran, C. (2024). Opportunities for information visualization in risk communication. In: J. Sixto-García, S. Pérez-Seijo, & B. García- Orosa, B. (eds) Communicating public health risk. The case of radon gas (pp. 59-71). Routledge. 2 Opportunities for information visualization in risk communication Ángel Vizoso Universidade de Santiago de Compostela ange[email protected] Gabriela Coronel-Salas Universidad Técnica Particular de Loja glc[email protected] Carlos Toural-Bran Universidade de Santiago de Compostela ca[email protected] Abstract: Information visualization is a communicative discipline that has experienced a continuous growth and development through the centuries. Nonetheless, its main growth has happened over the last three decades, with the introduction and development of different technological developments. Among them, the emergence of the Internet opened a new path for this visual area, thanks to the democratization of the production of these visual products. This chapter highlights the role and potential of information visualization as a tool in risk communication, not only for the media, but also for many other institutions. By taking Nathan Shedroff’s Continuum of Understanding as a basis, the possibilities of this communicative form will be addressed in order to show the particularities of its construction and comprehension. And all of that by following the objective of reaching the ideal of wisdom, a point where the recipient is able to judge information or data itself. This constitutes the last stage of this continuum, and the highest level of utility for information visualization, especially when dealing with complexity. 3 Introduction Technological development has gradually introduced changes in practically all areas of communication, especially since the beginning of the 21st century (Pavlik, 2001). Thus, some everyday tasks have undergone an innovation that could be described as drastic, while in others adaptation has been progressive. Of all the revolutions that have taken place over the last thirty years, it is undoubtedly the development of the Internet and all the functionalities and tools associated with it — such as smartphones and social media — that have had the greatest influence on the communication landscape, for purposes both lawful and more harmful to society (Botha & Pieterse, 2020; Freelon et al., 2022; Nguyen & Catalán-Matamoros, 2022). This influence takes place at all levels, from interpersonal communication to mass communication, whatever its geographical, temporal or thematic scope. In this way, it is possible to appreciate how different areas try to make the most of the full potential of these spaces, both for journalistic and non-journalistic purposes. The Internet has become an essential tool, both internally for organisations and externally in the relationship with their audiences. Something similar is happening with mobile devices. The smartphone is not only an indispensable tool in our daily lives, but also humans’ most frequent travel companion (Lamsfus et al., 2013), something similar to what happens with social networks. These types of tools open the door to new narratives that seek to exploit the full potential of devices in new environments. This chapter explores the main features of the use of information visualisation as a tool for communication, both in general and more specifically when conveying information to the audience about health or safety risks, among others. Through a review of the potential of data as a raw material for communication, this chapter shows what makes this form of visual communication different from others. For that purpose, Nathan Shedroff's Continuum of Understanding (Shedroff, 1999), a process in which a transfer is executed from raw information elements to an ideal of wisdom or capacity for action and decision on the content is set as a basis. The authors try to display not only remarkable projects that are using information visualization as part of their narratives, but also some of its current and potential features for the communication of risk. 4 The power of data(viz) Big data is traditionally defined as a set of "data clusters" of such a voluminous and complex size that they cannot be processed by traditional standard analysis software. The challenges facing the computation of this massive data are associated with the capture of the information, its storage, analysis, search and query, transfer, visualization and sharing, updating, information privacy, and the sources of origin of the information, among others (Ortega Mohedano & Coronel Salas, 2019, p. 825). From Data to Wisdom Figure 1. "Data, Information, Knowledge, Wisdom (DIKW)" information pyramid. Own elaboration. To reach the wisdom stage, companies must seize the opportunities of a big data strategy, invest in technologies and training, leverage the investment, and use this "new wisdom" (gained through the process of collecting, cleansing, and visualizing data) to improve processes such as customer service and products. Data are valuable because access to them has the potential to clarify issues in a way that generates results. However, mishandling data can place facts in an opaque structure that communicates nothing. Data may be of limited value to the public if it does not promote discussion or provide an understanding in context. 5 Display Data visualization (dataviz) translates large data sets and metrics into charts, graphs, pictograms and other visual elements. Data visualization results facilitate identifying and sharing real-time trends, outliers, and new insights into the information represented in the data. As the volume of big data increases, more people use visualization tools to access information on their computers and mobile devices. Businesspeople, data analysts, data scientists, data communicators, and data journalists use it to make decisions and deliver visually digestible and understandable information to the user. Publishing an Excel table with hundreds of cells is different from publishing an infographic contextualizing the information in that file. Taking into account these circumstances, it is possible to highlight the importance of data visualization thanks to elements like: - It allows decisions to be made and acted upon quickly. - It facilitates seeing a complete picture, uncover insights, and notice patterns within complex data without relying on a data scientist. - Presents meaningful data and shares knowledge with others in a way that is easy to understand. - Democratizes data by providing a source of truth and transparency to users. - When it comes to knowing the audiences’ segmenting audiences/audiences, it is necessary to "draw" their profile through data visualization. - Contributes to and helps visualize trends in data sets. - It helps to absorb information faster at different levels. - It uses the visual language to which society (users) is accustomed. - Patterns and relationships are identified more quickly using visualizations. Chart categories Graphics are divided into categories according to their objectives, aesthetics, or visual characteristics (IBM, 2021) and can be versatile and used in different ways, such as: 6 - Trends - Comparisons - Part of a whole - Correlations - Relationships and connections - Maps Display Catalog Among the best-known catalogs are: - The Data Visualisation Catalogue: https://datavizcatalogue.com/ - Depic Data Studio: https://depictdatastudio.com/charts/ - Data Viz Project: https://datavizproject.com/ Tools Thanks to the Social Web, these types of tools are entirely intuitive, where what is needed is to standardize the database and couple them to the various structures. For this reason, they can be adapted, initially to the work of data visualization, but will become more technical as the effective management of big data progresses. Some of the main tools are: - Datawrapper: https://app.datawrapper.de/ - Onodo: https://onodo.org/ - Infogram: https://infogram.com/ - Flourish: https://app.flourish.studio/ - Tableau Public: https://public.tableau.com/ - Power Bi: https://powerbi.microsoft.com/ - Google Charts: https://developers.google.com/ - Zoho Analytics: https://www.zoho.com/es-xl/analytics/ - Qlik Sense: https://www.qlik.com/es-es/products/qlik-sense - FusionCharts: https://www.fusioncharts.com/ 7 - Dome: https://www.domo.com/ - Visme: https://www.visme.co/ Data-driven Products Four products are used to tell stories with a large amount of data: articles, visualizations, datasets and News Apps. Articles They are born from a considerable volume of data and allow us to build stories; above all, they are short articles, and most use text detailing figures, values, numbers, and percentages, among others. - La Nación (Jastreblansky, 2012): “Los millones de la APE: cómo se repartió en 2011 la caja que era de Moyano” - La Nación (Alconada Mon et al., 2021): “Pandora Papers: an offshore adds mystery to the disappearance of US$7 million in the Baggio juice company” Visualizations Data visualization (dataviz) allows to show information obtained through large volumes of data through images, graphics, infographics, pictograms, and other elements. Short or long articles can complement them and, in some cases, be accompanied only by a headline and an explanation so that users can analyze and read them. - La Nación (2021): “The evolution of the pandemic in Argentina” - Primicias.ec: “More than 159,000 people ceased to have adequate employment in October” Datasets As its name suggests, it is a collection of data or a set of data that allows us to access information for processing. In a certain sense, it is usually linked to the transparency of organizations. We can access databases on the Internet according to the subject we are 8 looking for, but this will depend on who provides them and their transparency to the community, which is considered "open data." - Google Dataset Search: https://datasetsearch.research.google.com/ - Tableau: https://www.tableau.com/es-es/learn/articles/free-public-data- sets News Apps News applications are known as "news apps" and allow you to concentrate and focus a story in a single space to tell it far beyond a single article. According to Sandra Crucianelli (2013), "many times, the volume of data is so large that it is impossible to find a news story if an application is not designed to group and analyze variables, for example, by geolocation, by date, by company name, etc." - The Texas Tribune: https://salaries.texastribune.org/ - Propublica: https://projects.propublica.org/docdollars/ Work Phases Some media outlets have created innovation laboratories (Labs), including developing new products focused on a hypermedia narrative. As seen in the figure, it is essential to work together with several professional profiles of the media and, above all, to comply with the basic precepts of journalism: verify and contrast information. Among the work phases to implement a product with data, there are the six shown in Figure 2. 9 Figure 2. Phases of work with data. Source: Ideas of authors specialized in data and authors' contributions. Own elaboration Telling stories with data For John Bones of the Verdens Gang, many times it is not necessary to visualize a story, but the media often do so for readers or users to size up a fact. While stories containing large data often need visualization, we must be critical in choosing the data we will present. When we report on something, we know all sorts of things, but what does the reader need to know about the story? A table or a simple graph showing a process going from year A to year C will suffice. When working with data journalism, the goal is to present a manageable amount of data. It is about journalism. A good visualization is like a good picture. You understand what it is all about just by looking at it for a moment or two. The more you look at the visualization, the more you see. Visualization is better when the reader needs to know where to start or where it ends, and when the visualization is overloaded with detail. 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