2022-11-16

1. Introduction

Learning Objectives

  • You should be able to critically analyse how data is visualised
  • You should be able to judge a figure’s clarity and potential for misunderstanding
  • You should be able to identify potential sources of bias
  • You should understand how to create effective figures for your own work

Background Reading

Exercise: Ten figures (three per student)

  • For your assigned figure, consider the following:
    • What type of data is being presented?
    • Are the data presented effectively? (why/why not?)
    • How can the data presentation be improved?
    • Use the DOI provided to find the paper the figure is from, if you need more information than the figure legend
  • Fill in the pro forma with your answers to the questions above (one sentence each)

2. Summary Results

Responses by figure

  • We received 104 ratings in total (at three per student, this is 34.7 students responding)

Overall effectiveness

  • How was effectiveness scored, distributed across all figures?

Overall understandability

  • How was understandability scored, distributed across all figures?

Overall appeal

  • How was appeal scored, distributed across all figures?

Time taken per figure

  • How long did you take, per figure?

3. Results By Figure

Effectiveness/Understandability/Appeal

  • How effective/understandable/appealing did you think each figure was?

Colours/Fonts/Labels

  • How well did each figure use colours, fonts, and labels?

Statistics/Whitespace/Data

  • How well did each figure use statistics, whitespace, and data?

Reproduction

  • How well did you think you could reproduce each figure?

4. Specific Figures

Figure 1 (doi:10.1016/j.cell.2021.08.029)

Figure 1 (doi:10.1016/j.cell.2021.08.029)

Figure 1 (doi:10.1016/j.cell.2021.08.029)

  • Suggested improvements:
    • Colour differences in phylogenic trees could have been clearer, maybe use colour other than red to make colour-blind friendly. Likewise the red dots to indicate expected protein size were difficult to see - an arrow or asterisk might have been clearer to read.
    • Improved layout of diagrams
    • Some other forms about data presentation can be used with the bar chart.

Figure 1 (doi:10.1016/j.cell.2021.08.029)

improvements
Spacing out
the colours used in data presentation don’t go together making it not aesthetically pleasing
In figure A and B, more contrary colours such as green or blue could be used to represent TF family members which do not interact with SAP05. In figure E and F, WB bands could have been separately revealed to make the results more readable.
I don’t think the classification in figures A and B is very clear. In fact, I have no idea what it means. It would be better if there was a more detailed explanation
Picture C and D may need to be started in a new line and enlarged for the reader to see
no idea
Add the bar chart and show the p-values
Have distinct sections for each part of the figure and not have them overlapping each other
This figure is quite overwhelming, breaking this figure up into more separated figures could be beneficial to avoid overload and confusion from the reader.
Use a different format for displaying phylogenies
The data should be evenly spaced, even if the SPL family is smaller than the GATA family, it would be nice to be able to comapre the 2 properly. Moreover, it looks overcrowded and as if they tried to stuff as many figures in there as possible. 1C and 1D should be larger
Perhaps more focus on less qualitative methods, and more of a quantitative support to the results
Less information, larger clearer diagrams and indicators to show the point of figures.
they can be more well-organized and use more data to present the result.
NA
Increase sizes of the figures and space them out where appropriate. Further introduction of quantitative numerical data accompanied with statistical analysis.
Graphs of western blot proteins

Figure 2 (doi:10.1016/j.cell.2021.08.028)

Figure 2 (doi:10.1016/j.cell.2021.08.028)

Figure 2 (doi:10.1016/j.cell.2021.08.028)

  • Suggested improvements:
    • The data presentation looks very crowded and it can be more simple by focusing on less things.
    • B shows the volume of myeloid cell clusters macroscopically. But maybe add a number to indicate volume of different myeloid cell clusters
    • C and F - May be a larger picture is better.

Figure 2 (doi:10.1016/j.cell.2021.08.028)

improvements
Separate figures for each section of this figure.
difficult to see data in part E
Choose less mice, replace dot plots with appropriate plots such as bar chart, or add approximately trend line.
I think the data could be simplified
In Fig.C maybe it can use two figure to present two gender results.
The figure in D can be improved to be a line chart.
F could be presented differently
Stacked histogram with male and female bars stacked and P* values on top of the bar.
Figure 2E is a little bit much and complicated, I think there is no need to show so many bioluminescence images of mice.Instead we can use different symbols for colors
figure f bigger to make more readable
Can use more contrasting color for the illustration.
more data can be used
Better Figure aesthetics
The scatterplot of figure D is messy, so using box plot may be improved.

Figure 3 (doi:10.1016/j.cell.2021.07.030)

Figure 3 (doi:10.1016/j.cell.2021.07.030)

Figure 3 (doi:10.1016/j.cell.2021.07.030)

  • Suggested improvements:
    • Mark specific values on the chart to increase readability.
    • Use colour intensity to describe the number of people infected. Greater intensity -> more people.
    • Change circular tree to a rectangular cladogram to improve readability? But is the choice made for space rather than legibility (and does it always matter?).

Figure 3 (doi:10.1016/j.cell.2021.07.030)

improvements
More explanation of the findings in the data figure.
I think this figure is good apart from maybe figure D where the colours are not distinct enough
Selecting important information and enlarging the size of the graphs.
Figure legends could be a bit more detailed
It is a tiny but too ‘busy’, which distracts from what the data is showing
Some of the images (Fig.B, C) can be reduced in size to leave enough space for analysis in the bar and scatter charts
Maybe some national data on disease epidemiology, to compare
More detailed descriptions
more comparisons can be added
The genome trees may be presented in a more proper way.

Figure 4 (doi:10.1016/j.cell.2021.08.016)

Figure 4 (doi:10.1016/j.cell.2021.08.016)

Figure 4 (doi:10.1016/j.cell.2021.08.016)

  • Suggested improvements:
    • Be more selective with the data, only include what’s necessary and/or use colour.
    • Maybe using combining plots is better. Jittered scatterplot can make the figure more vivid.
    • Separate them into several figures and make them bigger
    • In these figures, especially G to R, the Y-axis scale can be enlarged to amplify the negative space, otherwise the data will look crowded and unclear, and the numerical order of the X axis can be changed from small to large to prevent readers from misunderstanding.

Figure 4 (doi:10.1016/j.cell.2021.08.016)

improvements
It may help to split the figures up as it was hard to distinguish results of each.
I think the figure is quite excellent and no need to be improved.
Too much information in one figure
Expanded description on what type of specific ligand they used.
i do not know

Figure 5 (doi:10.1016/j.cell.2021.07.029)

Figure 5 (doi:10.1016/j.cell.2021.07.029)

Figure 5 (doi:10.1016/j.cell.2021.07.029)

  • Suggested improvements:
    • Can make use of graphs to represent the box-plot data and use colour-blind friendly colours to represent the immunoflorecence data.
    • More ticks could be added into the percentage graphs to more accurately show percentage increase or decrease and graphs A and E could be converted into another type of graph to present clearly.
    • It can be improved by fixing figure 1.(A), as it is difficult to understand what they were trying to achieve.

Figure 5 (doi:10.1016/j.cell.2021.07.029)

improvements
The red and green stained used in the immunofluorescence images could have been changed to more colourblind-friendly ones.
I don’t know.
there is no need to improve
Colour code graphs
put less information in one page
some quantitative analysis can be done to analysis the (G) gragh.
Good figure overall

Figure 6 (doi:10.1016/j.cell.2021.07.022)

Figure 6 (doi:10.1016/j.cell.2021.07.022)

Figure 6 (doi:10.1016/j.cell.2021.07.022)

  • Suggested improvements:
    • There is too much data in this one figure. It would be easier to interpret if there wasn’t so much to look at in the one figure.
    • We can add more figures of showing relationships between numerical data.
    • On each figure it is difficult to distinguish each individual dot (which represents a patient) which can make it difficult to read the data and so perhaps another type of graph may better represent this data or different colours/shapes for the dots could be used.

Figure 6 (doi:10.1016/j.cell.2021.07.022)

improvements
Separate figures for each section but i appreciate this might not be possible.
I will use other bright colors in charts B,D,E,F,G,H ,the colors are too annoying.
There are too many box plots, i think it is better to convert some graphs to other forms like histogram.
maybe increase the N number/ would maybe help with the error bars

Figure 7 (doi:10.1016/j.cell.2021.07.023)

Figure 7 (doi:10.1016/j.cell.2021.07.023)

Figure 7 (doi:10.1016/j.cell.2021.07.023)

  • Suggested improvements:
    • Increased size of graphs and bolder lettering.
    • UMAP could be described more thoroughly, overall data is very dense, especially figure G, could do with being processed in a way that’s more understandable.
    • Combine the plot with other kinds of plot(such as combining violin plot with scatterplot or combining scatterplot with boxplot) and use color gradients.

Figure 7 (doi:10.1016/j.cell.2021.07.023)

improvements
Selecting only necessary data to visualise
Reduce meaningless colors. Divide Figure F into separate violin plots. Replace figure G with pie charts.
needs to be simplified
I believe B,C,D,E are not effective at all, they are too complex to make sense, those data can be presented by line chart or histogram.
For Figure. G. Instead of squeezing them into a single image, you can split them into multiple images for comparison
focus on less cells so its clearer and easier to digest. use more simplistic graphs
Use less colour, change the kind of graphs used for f,g,h,i
The most confusing parts were B-E, as I found the way the cells were clustered to be confusing, couldn’t this have been better represented in a table/scatter plot? It feels like you’re looking at a map.
Categorise and break down larger figures into more digestible parts to complement the wider picture given by the seen data sets.
A more varied colour scheme could have been used in some of the graphs as they looked too similar
data presented in a more concise or easier to understand, more descriptive legend and title.
The labels of the figure are too many and the colors used are also too comlicated.
X axis labels for b and e

Figure 8 (doi:10.1016/j.cell.2021.08.003)

Figure 8 (doi:10.1016/j.cell.2021.08.003)

Figure 8 (doi:10.1016/j.cell.2021.08.003)

  • Suggested improvements:
    • The data can be improved by separating some of the figures into another figure so that there is not too much in one figure.
    • Scatterplots (C, F,G) should be bigger, the colour schemes in (B,D) should use sequential palettes and place similar graphs/diagrams near each other
    • Use more clear indicators besides coloured circles? perhaps use numerical measurements instead of purely visual indicators

Figure 8 (doi:10.1016/j.cell.2021.08.003)

improvements
not reproducible
Better explanation of findings in figure legend.
use of brighter colours could help retain attention
I have no idea to this question I think it is really good
Less cramped data - hard to distinguish. a lot going on
Better arrangement
The figure is quite crowded, especially part 8C.
I think it is quite excellent.
figures need to be made bigger to be made more readable, need a better title for the figure as it doesn’t tell you anything, needs more explanations of thats going on and the methods used
use more mathematical data
More concise
Unsure
More detailed legend

Figure 9 (doi:10.1016/j.cell.2021.07.024)

Figure 9 (doi:10.1016/j.cell.2021.07.024)

Figure 9 (doi:10.1016/j.cell.2021.07.024)

  • Suggested improvements:
    • Change the colours in the bar chart because it is difficult to see
    • Graph E should be split into several graphs so that you can see each of the data marks clearer
    • The different circles in F and G could be better shown in bars in my opinion.
    • Personally, I think the comparison between blood and sperm in Figure F should be made by the same Rank plot. It is not easy to compare blood samples with sperm samples using the dot plot, so it cannot show the comparison of trends.

Figure 9 (doi:10.1016/j.cell.2021.07.024)

improvements
Mention significant differences
I have no suggestions
Figure E is too small for me to separate any of the data sets on the graph
Explain bottom two figures for those not trained in this field maybe
Bigger figure!
More colour
Better colour coding
no significance stated on b or d or e especially- lack of statistics and analysis
Expand upon acronyms during the first use in the legend for better understanding of the figure.
Add statistical analysis, use different graph types
Unsure

Figure 10 (doi:10.1016/j.cell.2021.07.006)

Figure 10 (doi:10.1016/j.cell.2021.07.006)

Figure 10 (doi:10.1016/j.cell.2021.07.006)

  • Suggested improvements:
    • For figure B, less harsh colours could be use and maybe a dotted line so you can see both lines in equal amounts.
    • Figure C is difficult to read on a black table; less extreme colours should be used to grade results.
    • The relative binding data could have been presented on a bigger cleaner graph

Figure 10 (doi:10.1016/j.cell.2021.07.006)

improvements
Trying to condense the figure legend down.
More white space
use more colour. use clearer data points
Nothing
The figures could be partitioned to give a better step-by-step breakdown of the results, with each figure letter having its legend more directly associated with it, rather than being in one messy paragraph.
no improvements
possibly use different ways of presenting the data to not seem like the same thing over and over
less words
no
More statistical analysis?

5. Summing Up

General Comments

  • Colour choices
  • Larger figures/graphs, more space between figures/graphs
  • Too much data per figure
  • Split into multiple figures
  • Remove unnecessary data (how do we define this?)
  • “The data is presented in a manner that would likely be inaccessible for people without prior experience. A move toward a more palatable/digestible format will facilitate better science communication in the future.”

Visualising Data About Data Visualisation

  • What did you say about figure effectiveness?

Visualising Data About Data Visualisation

  • What words did you use to describe figure improvements?

Data Visualisation is Not Neutral