A2
Further explanations of the brief and rubric
Criteria A: Data Storytelling
Narrative
Criteria A (the story itself):
● The story is Compelling (motivates people to act/believe/empathise)
● The story is Clear (simple and simply stated)
● The story is Original (novel or surprising)
● The story is built around the main insight (or has a main point to get across)
Documenting the Narrative
Criteria A (stuff in your documentation):
● Justification clearly explains the intended story (draw attention to what makes it compelling, clear, interesting, and built around a main
insight/point)
● The justification that clearly explains the data mapping (In this case ‘data mapping’ means the data chosen to make the point [minor or main])
● Justification for decisions made to tell the story
↑ Why did you choose that order of insights?
↑ What are you trying to make the reader think/understand at each point in the story and how does it relate to the story as a whole?
↑ Any other decisions that show that you have carefully developed the story. E.g. Did you throw out any points that weren't working? Did you feel the
need to find some data to make a point that was missing?
↑ Any other decisions you made to help tell the story. For E.g. did you accompany any parts of the story with emotional images or emotive language
to help that section have an emotional impact?
↑ At the end of this document, I have some notes on how to write a good justification.
Documenting the Narrative
This is my key insight. This is why it's interesting. This is why it's compelling.
This is my first supporting insight. This is how it relates to the key insight. The data communicated in this
insight is… my motivation to use this visualisation to show the insight is... and this is the rationale
(justification).
This is my next insight. This is how it relates to the key insight. This is how it fits into the flow of the narrative
(how does it relate to previous insight and next insight). The data communicated in this insight is... my
motivation to use this visualisation to show the insight is... and this is the rationale (justification).
..repeat for each insight…
And this brings me to the key insight. This is how it clearly builds upon the previous insight. The narrative was
supported by these features. The narrative satisfies the assignment brief because...
Criteria B: Design Quality
And a little bit of Criteria C: Design Rationale
Design
Criteria B (chart specific):
● Charts are Clean
● Charts are Clear
● Charts are Communicative
● Insights are front and centre
Criteria B (aesthetics of everything, charts as well):
● Aesthetic must be appropriate
● Not obscure from the message
Documenting the Design
Criteria B (chart specific):
● Charts are Clean - How do you justify this?
● Charts are Clear - How do you justify this?
● Charts are Communicative - How do you justify this?
● Insights are front and centre - How do you justify this?
Criteria B (aesthetics of everything, charts as well):
● Aesthetic must be appropriate - How do you justify this?
● Not obscure from the message - How do you justify this?
Documenting the Design
Criteria C (in your documentation):
● Justification explains aesthetic and HCD choices
○ Detail the process of any choice that demonstrates you have a good design process.
○ E.g. Why pick those colours? Why change the line weights/styles? Why add custom annotations? Why
turn off annotations? Why turn off interaction? etc...
● Justification explains data and chart choices (mappings)
○ Why map this data to the insight/narrative?
○ Why is this chart the best choice for this data?
○ Was there other data you considered to explain this insight?
○ Were there other chart types you considered?
○ Useful link to every chart you can think of https://datavizproject.com/
Documenting the Design
The design satisfies the brief in these ways...
I made this aesthetic choice when designing my website. motivation. rationale.
I made this aesthetic choice when designing my website. motivation. rationale.
...etc
I made these human-centred design choices when creating the first chart. And this was my motivation. And this is my rationale (justification).
I made these human-centred design choices when creating the second chart. And this was my motivation. And this is my rationale (justification).
...etc
I made this aesthetic choice when designing my charts. motivation. rationale.
I made this aesthetic choice when designing my charts. motivation. rationale.
...etc
Criteria D: Data Science
Documenting the Data Science
Criteria D:
We need to see evidence OR at the very least an explanation of the process of preparing
your data. And the same for transforming your data.
Criteria D:
With regards to code comments, we want to see comments explaining data
prep/transforming. We also want to see how plotly was utilised.
Of less importance is the html layout code. But if you did something cool in html that you
want to point out, use comments to bring attention to it. But otherwise, standard comments to
explain it is fine.
Documenting the Data Science
Data Science:(the explanations of preparing/transforming data can go in the text submission, in a code comment or in the
assignment medium proper. Whichever place is the most appropriate.)
This is how I sourced and prepared this dataset. And this is how I transformed it.
This is how I sourced and prepared this other dataset. And this is how I transformed it.
...etc
[before pasted code snippet] //i copied this snippet of code from and it does this
[before modified code from another source] //i modified this code from and it does this
[before code you authored] //i wrote this section myself and it does this
[in code before a function] //this part of the code does this for this reason
[after important/complicated line of code] // this line of code does this
Criteria E: Human-Centred Evaluation
Usability Evaluation
This section will help you design your test. This is not necessarily all of the information that
we need to read about in your ‘Evaluation’ section. The information you should provide
should summarily explain the rigour of your testing process, the interpretation of your results
and the improvements that came about through this testing process.
Usability Evaluation
1. Product and Experience goals
Provide a short overview of why you are evaluating your experience/data journalism
article
● What is the intention of this evaluation
● What are your experience goals for this product
Usability Evaluation
2. Test objectives
Write a few sentences establishing clear test and evaluation objectives. This is integral to
ensure that your evaluation is structured and has a purpose. Be sure to include:
● Goals of the usability test
● Questions you want to be answered - what hypothesis will be tested? (Focus on the
important insights and features)
● Metrics you used to measure success
○ Eg. >90% of participants understanding the main insight without explanation, all participants being able
to easily read and explain the data being shown in graph 1, >75% of users zooming in on a graph,
<5% of users not seeing a button, an average rating of 7.5/10 from user feedback to the question “how
likely are you to recommend this article to a friend” etc.
Usability Evaluation
3. Participants
Describe your participants and test conditions in a few sentences.
● How many participants
● Who are they? Do they represent your target demographic? Do they represent a
diverse sample (age/technological skill/background/political ideology/etc.)?
● How will you collect your answers? (questionnaire/interview/etc.)
● Under what conditions are you conducting the test? (live/remote/timed/etc.)
Usability Evaluation
4. Setting Your Tasks
In your testing protocol, write a list of tasks you are asking your participants to complete.
What are the tasks that will help answer your test objectives?
● List of tasks they are to complete
● Eg. The user is to explain what they believe the key insight to be. The user is to explain
what they believe graph 1 is showing them and read aloud the title, x, and y axis…
Usability Evaluation
5. Results
In a short paragraph, give an overview of your testing and results. Describe the results that
align with the test objectives you have defined. How successfully were metrics achieved?
Critically analyse the results. Remember to include:
● Did the user succeed in achieving key metrics
● Eg. were they able to understand the main insight without needing explanation, were
they able to easily read and explain the data being shown in graph 1
● What were the strengths or weaknesses of your work?
Usability Evaluation
6. Response
Write a short paragraph explaining how you used the results. What are the implications of
the evaluation results and how did they help you?
● What have you drastically improved or changed?
● Justify the improvements.
Documenting the Usability Evaluation
This section is what you submit in your assignments. The writing here should be integrated
and touch on most/all the points that you have in your protocol. While having sections
separated by headings is great for creating testing protocols, it’s better to combine your
efforts in the evaluation itself. Try to tie together some aspects with a common thread.
Documenting the Usability Evaluation
Remember to include:
- A few sentences giving an overview of why you evaluated your data vis. You can
probably link this with your test objectives (i.e. combine points 1 and 2)
- A few sentences about your target demographic. Here is where you should empathize
with your users, and maybe bring up anything specific that you did to tailor testing.
(e.g. as the visualization targeted young adults, testing was conducted with a similar
user group, and focused on XYZ)
- User testing tasks and results by combining a few categories (e.g. you could talk about
the tasks along with their results and response in a sentence)
- when asked about the y-axis, participants mentioned X which resulted in X, In response to X feedback,
the X motif was strengthened, participants found X extremely effective for communicating X
- Strengths AND weaknesses about your design
Documenting the Usability Evaluation
Criteria E :
● Rigorous. (critical analysis of the sample (participants) and test tasks)
● Predefined metrics (you have initial conditions for success/failure of the thing you are
testing)
● Tasks identified (goal-oriented)
● Each task/goal links to an insight or chart (something to do with the communication of
the story)
● Analysis of BOTH strengths and weaknesses
● Some evidence of improvement based on feedback
Justifications
A little bit more of Criteria C: Design Rationale
Justifications
Here is an example of a general justification:
● Explain: I chose a line graph to display this data.
● Motivation: I wanted the user to recognise the change over time.
● Rationale: As stated on https://datavizproject.com/data-type/line-chart/ one of the
functions of a line graph is to show a "trend over time" and so it is perfect for this
application.
That example is very simple and boring, but demonstrates the components of a
‘complete’ justification.
Justifications
We are marking the process as much as, if not more than, the result. You could luck out on the result
by stumbling into a good design, but a good process is yours forever and that's why it is so
important. Justification is proof of your process.
If you rationalise with your own reasoning then your arguments should be persuasive. If you
rationalise use academic sources, then the sources should be reputable and well researched.
For every ‘decision’ you justify, make sure the justification is complete. I know it should be obvious
that blue is the colour of the sky, but if a justification said "I wanted it to be the colour of the sky so
I picked blue" then it isn't complete. I don't expect you to write any boring justifications about the
colour of the sky, but my point is that you shouldn't leave anything open to interpretation or leave
me to guess what the thought behind the process was. I need proof of the process.
Justifications
Another justification example. This one is a bit more natural and is explaining a decision less
related to communicating data:
"The goal of this section of the story is to instil a sense of dread about a dark future where
climate change is out of control. To complement this section I needed the imagery that
instilled the same emotion. Dystopian wastelands films like "Blade Runner 2049" (2017)
frequently use monotone palettes to achieve this so I processed my images in photoshop to
achieve the same effect.”
Explanation, Motivation, Rationale.