Figures are an essential part of scholarly publications. To ensure that your figures communicate your research effectively, there are a few considerations that you should keep in mind.
Your figures will form an integral part of your publication - people often read an abstract and then look at figures to get an idea of the main points of the paper, and to decide if the paper is worth reading further. Therefore your figures need to be carefully chosen to make sure that they tell as much of your story for you as possible.
Plan out your figures as part of the process of drafting an outline for your manuscript so that your figures and text complement each other without repeating information. Selecting effective figures can help to engage reader interest and increase comprehension (and therefore hopefully your citations!). It can also help to decrease word counts, as lengthy text explanations can be replaced with succinct figures. What makes a figure effective will vary between fields and disciplines, but overviews, trends, and spatial data are all good candidates for information that might be better displayed in a figure rather than described in the text.
As you plan your manuscript, you should have some idea of the publication you intend to submit to. The author guidelines on a publication's website will often contain information on requirements for figures, such as the number of figures allowed, minimum font size, required file formats and resolution, or the column width that the figure will need to fit into. Guidelines vary between publishers, so always make sure you know your publisher's requirements, and follow them throughout the process of creating your figures.
Plan for your figures to fit either a single column width or across the full page, and then make sure to create them at that size. A common mistake is to draft figures very large, and then shrink them down to fit the allotted space. This frequently results in features of your visualisation becoming minuscule and illegible at the new size, requiring you to redraw your figure and re-size all annotations.
All of the information necessary to understand your figure should be contained within it. Figures may end up being reproduced or presented separately from manuscript text, for instance if they are used in a presentation, in which case any explanation or context provided by the text would be lost. To make a figure self-contained ensure that:
Even though many journals can be accessed online and people tend to obtain electronic copies of articles, figures in papers stand a high likelihood of being reproduced in black and white at some point. This may be because the print version of a journal is only black and white, or charges extra for colour images, or could occur when readers print a hard copy of a paper. If colour was used to convey information in these cases, the resulting black and white figure could become useless. It's a good idea either to create greyscale versions of your figures for the print versions of journals, or, even better, to choose a colour palette that can be printed in black and white such that the colours are reproduced as distinguishable shades of grey. ColorBrewer is a good resource to help you create suitable colour palettes. Doing this will also help to ensure that your figures are accessible to people with vision impairments, such as colour blindness.
In a large presentation venue some members of your audience may be quite far away, and projectors may introduce some fuzziness into figures and text that looked crisp on a computer monitor. As your visualisation will likely be the primary way that you convey information on a given slide, it's important to ensure that all audience members can easily see it. To maximize the readability of your visualisation you should:
In presentations you have the option of using dynamic visualisations, such as animations or interactive visualisations, as well as static figures, offering further options for telling your data's story. Animations can be a useful way of showing how data change, or for flying-through a three dimensional visualisation. When using an animation in a presentation, in addition to the points above, ensure that:
There are many different kinds of charts out there, some very familiar from everyday use, while others can be highly unusual, complex, or rarely seen. It's important to use a chart that's appropriate to the data you have, and that allows you to explore the information you're interested in. Check out the Key tools links on the right side of this page to help select the best visualisation for your purpose.
You need to make sure that you include enough annotations for your chart to be understood: x- and y-axis labels indicating units, a legend, labels for highlighting important points or trends in the data can be essential to ensure that your chart succeeds in conveying the intended information. However, you should make sure that you remove any non-essential annotations that might be cluttering up your chart. Generally remove gridlines, any background fill, extra tick marks along the axes, busy pattern fills, any colour that doesn't represent information, and any extraneous text. It will be up to you to decide what is necessary to keep to make your chart usable, but keep in mind that having less detail to sort through means that your viewers will quickly see and focus in on the main messages of your visualisation.
Keep in mind that if you try to put too much on one chart then the relationships that you want to display can become lost. For instance, plotting a large number of lines on a line graph can mean that the trends of all lines become obscured and no information can be taken away from the resulting visualisation. In this case, it would be better to plot small subsets of the data on multiple charts, and compare the charts to each other. Using dual y-axes can also make your chart difficult to interpret, and potentially even imply relationships between variables that are merely artefacts of how the variables were plotted. Any time you feel the data are overwhelming the viewer, assess whether it would be possible to use multiple plots to make relationships and trends clearer. Note that this is not a licence to throw away data that doesn't fit your message! You always need to make sure that you are accurately representing your data, or the whole point of creating a visualisation is lost.
If you intend to compare multiple plots you must ensure that they have been plotted the same way, are the same size, have same scale axes, and employ the same conventions to enable your viewers to draw accurate comparisons between them. They should also be plotted next to each other, rather than on separate pages or slides.
If you use colour in your charts, make sure that a difference in colour provides the viewer with useful information, as extraneous colour changes can be distracting and make it more difficult to compare the data represented. For instance, don't colour all of your bars in a chart a different colour; the different categories are already indicated by the fact that they are separate bars! Either use the same colour for all of your bars, or colour them based on another variable, or to highlight a particular bar that you want to draw attention to. Remember to think about how colour in your chart will affect its usability for people with colour blindness or if the chart is printed in black and white. Use resources like ColorBrewer to choose colour palettes that are colour blind and black and white friendly.
Maps are used in a wide range of fields to display data with a geographic component. Population characteristics, land use, or geologic data could all be visualised on maps. Creating map visualisations requires that a few unique considerations be taken into account.
If possible, maps should be oriented with north pointing to the top of the visualisation. In some cases it may be necessary to create a map in a different orientation, for instance in order to fit a map on a page. In these cases it is essential to include an arrow indicating the direction of north on the map. It is good practice to include a north arrow on all maps, even those with north oriented to the top, as your viewers can then be certain of the map's orientation.
Future users of your map will potentially want to incorporate your data into their own maps. To make it easy for them to georeference and reuse your map, you should make sure that you include the map projection used (e.g. Mercator, Orthographic, Mollewide, etc.), as well as several latitude and longitude markers. Having only one latitude and longitude tie point is not enough to make your map reusable!
It's good practice to include a scale on all maps, although this may not be necessary for maps that are at a continent scale or larger, depending on the purpose of the map. Map scales can be written as ratios, e.g. 1:10,000 where 1 cm on the map would be 100 m, or as graphical scales. Using a graphical scale is recommended as it will remain accurate even if your map is resized, whereas a written scale will become completely meaningless and even misleading if someone reproduces your map at a different size to the original.
All maps must have legends; you need to give people the information necessary to interpret the visualisation! If your field has any symbols or patterns that are conventionally used to represent specific mapped features, then make sure to employ those conventions.
Patterns and fills are commonly used to present regional data on maps. If possible, try to limit the number of different patterns used on a map, as they increase visual clutter. Numerous different patterns on a single map will compete for attention and decrease the readability of a map. Using different colours for different categories, or different shades of the same colour for different ranges of the data can help keep your map easy to interpret. However, be aware that using colour to convey data can make your map unusable for people with vision impairments such as colour blindness, and try to pick a colour palette that is colour blind accessible using tools such as ColorBrewer.
The most important part of creating a three dimensional (3D) visualisation is making sure that the data and visualisation type are suitable for displaying in 3D. Incorporating 3D elements in a visualisation purely for aesthetic appeal usually results in a less effective visualisation. While there will be exceptions, it is generally only appropriate to employ a 3D visualisation when:
Do not add 3D effects to 2D visualisations, such as bar charts or pie charts! The 3D effects will distort your data and make it difficult for viewers to interpret, resulting in misleading or useless visualisations.