jason dykes

OK - good, the more you can use the reflection to address this story the better.

You may find it helpful to make the "I would like to" side of this closer to a visualization contribution, so that ... the epidemiologists can do the epidemiological thing!

It may work best as :
I would like to develop interfaces that enable epidemiological model builders(EMB) to
compare models with different input, output and configurations
So that they can understand and adjust their models!

I think that is probably the intention with user stories.

Page not found!
Are the data not open?
Do try to get access to the actual data if possible!

It's a private repo at the moment, I've invited you to the repo.

OK - this is quite a broad idiom, but let's hope it allows you to reflect on the pros and cons of MLVs.

This section has lots of typos - please check through and correct.

Can you say something about types of coordination here?
Stuetzle's Plot Windows is pretty seminal here:
Stuetzle, W. (1987). Plot windows. Journal of the American Statistical Association, 82(398), 466-475.
https://www.jstor.org/stable/pdf/2289448.pdf

Or is there something in the Roberts paper that you could use to explain some of what is achievable - e.g. the Exploration Techniques?

OK - nicely clarified - much clearer, thanks! I still think it's a pretty broad idiom 'multiple windows, somehow coordinated' but you have made it clear that this is the intention.
RobertS!

Incomplete, although you should be able to use some of the above to populate this section .. and perhaps say a little more about types of MLV in the above.

So please add the link to the Roberts paper here and VERY BRIEFLY summarise toe context.

Check for spelling mistakes please.
These are nice examples, the more you can say about what they show and what they are used for, the better.

This is a good description of what you implemented - but what did it enable you to do in terms of the user story?
More spelling mistakes and typos - please fix.

This is great. See my comments on the user story and can you describe this using some of the language and terminology of the user story?

It's hard to figure out how these recommendations follow from the information provided so far.
Can you link them to the experience, the Description & Use and the Reflection more clearly?

This seem important. Can you be a little clearer. Is bullet 1. saying that MLV is too challenging in this context?

Nice - do you have any examples or evidence of the important "unusual patterns in the visualizations".
It would be compelling and convincing to show these.

This is GREAT, but you know what I am going to say next ....
How did the idiom **MULTIPLE LINKED VIEWS** help with this ... because in your example you can see this with one view! To be convincing we either need to day :
  - we needed these multiple linked views for these reasons to get to this finding, or
 - actually, we only needed single views for this so it's probably more important to find the right single view than to produce multiple linked views, or
 - this only shows up in some views, so producing multiple linked views enables us to find an effect and check for its occurrence quickly and reliably

Nice point about time and optimization - when should we optimize?!

Did the "balanced representation strategy" work?
This could be an idiom - it's a thing you tried that exists in the literature - did it work?

Why did you think it would work?
If it didn't why not - and so what else do we now know about it?

This is quite nice, but I do wonder whether MLKV is particularly inappropriate when you have more points than pixels! Surely the more data items you have the more important it is to not use screen pixels in ways that are redundant? Or is there a counter-argument informed by your experiences?! 😉🤔

We need names please, including modelling collaborators.
BibTex format if possible!
Dykes, Jason and Wang, Qiru and Vardy, Jamie 
Like that!