Data have now became present in every aspect of our lives. An unimaginable growing amount of data calls for developing new tools and solutions on how to disseminate data efficiently in a way that would facilitate users in their decision-making process. Data visualisation provides powerful answers to this challenge, allowing transformation of numbers into images in a way that is processed easily and efficiently by our vision system. In the historical overview of data visualization, we identify key milestones that contributed to the prominent role of visualization in today's society.
Data visualization is communicating to various publics, both general and specific expert publics, but we still do not fully understand the mechanisms of chart comprehension and understanding. Data visualization is a multi-disciplinary field that builds on the theoretical background form many fields as well as on the experiences shared by practitioners. In the literature review, we highlight the cognitive psychology findings. We believe that these findings can adequately describe and explain chart comprehension and messaging.
Official statistics data describe demographic, social, economic, environmental and other aspects of society. Despite their long tradition, official statistics have become significantly more visible when establishing their web presence. Statistical data are now used to a much greater extent than ever before, new tools and services are being developed, the variety and size of data is increasing, and the data quality is improving. However, the question arises to what extent official statistics tailors their products and services to meet the requests of different users as well as how can data visualization enhance official statistics dissemination. We review users of official statistics and we propose their classification into three major groups: the general public, analysts and decision-makers. The groups differ in their motivation for searching and using official statistics data as well as in statistical literacy, among others.
In the empirical part, we present results of three experimental studies we conducted on three different convenient samples. We tested how users understand charts and what messages they understand from them. We included both general (de-contextualized) charts as well as concrete examples of official statistics charts found on Eurostat social media. We applied charts that are common and widespread and hence they should be relatively easy to understand. However, our results suggest that several obstacles are posed to the understanding and interpretation of even simple charts. Although embellished charts do not follow data visualization guidelines, it seems that they are better memorized and recalled in comparison to plain charts. More attention should be paid to the titles wording since titles could in fact be the only messages that reach the users. We conclude with several proposals for further research and introduction of improvements in the field of data display, both on the side of users and on the side of the chart providers.
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