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New Article in “Demographic Research” | 28.04.2021The Importance of Data Visualisation in Demography
Visual representations can be a valuable aid to understanding population science findings and developments. But in many cases, visualisations are not readily understood by readers – or present the findings in a distorted way. This raises the question of what actually constitutes a good visual representation and what are the preconditions for good visual scientific communication.
Answers to this question are provided in a special issue of the Demographic Research journal. It contains seven articles dedicated to the many different facets of data visualisation. The issue’s editorial was written by Dr. Tim Riffe from the Max Planck Institute for Demographic Research (Rostock) together with Dr. Nikola Sander and Dr. Sebastian Klüsener from BiB, who also guest-edited the issue.
In their editorial, they discuss what constitutes good data visualisation and why it is worthwhile aiming for high standards. To this end, they present their own guidelines for creating effective data visualisations.
Different forms of demographic data visualisation
What Characterises Good Data Visualisation?
Why is the visualisation of demographic data important? “In a scientific context, good visualizations enhance our understanding of the underlying data and grab the reader’s attention without sacrificing truth for beauty,” emphasises co-author Dr. Nikola Sander. The decisive factor here is that the brain can process visual information much faster than text. This is particularly true in the field of demography, in which researchers often need to understand and summarize large datasets. “Visualizations can thus be employed to efficiently explore and discover patterns in demographic data, to help viewers gain a better understanding of magnitudes, intensities, durations, changes, and differences, and to communicate these to large audiences,” explains Dr. Sander.
Explanatory and Exploratory Visualisations
The authors show that visualisations can be used for two different purposes: on the one hand as a research tool for explorative analysis of large, multidimensional datasets, and on the other hand as explanatory graphics which transport information that is difficult to convey to readers only through the medium of language. The crucial point here is that explorative analysis graphics are not necessarily suitable as explanatory graphics in publications. This is because the latter have to meet much higher demands in terms of their design and their comprehensibility than explorative visualisations, which are often only seen by the researchers themselves.
10 Guidelines for Creating Data Visualisations in Demography
What exactly do I need to consider if I want to present demographic data in an accessible way? The article provides valuable tips in response to this question – one which the authors hope more and more researchers will ask themselves in the future. 10 Guidelines for Creating Great Data Visualisations in Demographic Research explain how to create effective visualisations.
Riffe, Tim; Sander, Nikola; Klüsener, Sebastian (2021): Editorial to the Special Issue on Demographic Data Visualization: Getting the point across – Reaching the potential of demographic data visualization. Demographic Research 44(36): 865-878.