A provocation for the 'Network analysis and the cultural heritage sector' workshop in Luxembourg, 8 June 2016. Talk notes are available at http://www.openobjects.org.uk/2016/06/network-visualisations-problem/
1. Network visualisations and the
"so what?" problem
Mia Ridge, @mia_out
Digital Curator, British Library
digitalresearch@bl.uk #BLdigital
Expert Workshop Network Visualisation in the Cultural Heritage Sector
8 June 2016, Belval campus , University of Luxembourg
24. Sometimes a network visualisation
isn't the answer ... even if it was
part of the question.
25. No more untethered images
• Include an extended caption?
– Data source, tools and algorithms used
• Link to find out more?
– Why this data, this form?
– What was interesting but not easily visualised?
– Download the dataset to explore yoursel?
27. Talk about data that couldn't exist
'because we're only looking on one axis (letters), we
get an inflated sense of the importance of spatial
distance in early modern intellectual networks. Best
friends never wrote to each other; they lived in the
same city and drank in the same pubs; they could
just meet on a sunny afternoon if they had anything
important to say. Distant letters were important,
but our networks obscure the equally important
local scholarly communities.'
Scott Weingart, 'Networks Demystified 8: When
Networks are Inappropriate'
28. Help users learn the skills and
knowledge they need to interpret
network visualisations in context.
How? Good question!
29. Over to you!
Mia Ridge @mia_out
Digital Curator, British Library
digitalresearch@bl.uk #BLdigital
Notes de l'éditeur
Among the questions we seek to discuss during the workshop are for example:
How do users benefit from graphs and their visualisation?
Which skills do we expect from our users? What can we teach them?
Are SNA theories and methods relevant for public-facing applications?
How do graph-based applications shape a user's perception of the documents/objects which constitute the data?
How can applications benefit from user engagement?
How can applications expand and tap into other resources?
While I may show examples of individual network visualisations, this talk isn't a critique of any of them in particular. There's lots of good practice, and these lessons probably aren't needed for people in the room...
Network visualisations might be great for research, but there are challenges to address to make them more effective tools for outreach.
I'm a Digital Curator at the British Library, mostly working with Western Heritage collections. Part of my job is to help people get access to our digital collections, and visualisations are a great way to firstly help people get a sense of what's available, and then to understand the collections in more depth.
I've been teaching versions of an 'information visualisation 101' course at the BL and digital humanities workshops since 2013... much of what I'm saying now is based on comments/feedback when presenting to academics, cultural heritage staff... As people new to SNA, they sorta stand in for public.
My fundamental premise is that..
And this is a problem. We're not conveying what we're hoping to convey.
When teaching datavis, I show examples like this and give people time to explore them. I prompt discussion with questions like 'Can you tell what is being measured, described? What do the relationships mean?'
After exploring them, discussion often reaches a 'so what' moment. Here are some examples of problems my classes have with network visualisations…
Credit: fredbenenson_com_2012_12_05_the-data-behind-my-ideal-bookshelf
Spatial layout being based on pragmatics of fitting something on the screen using physics, rules of attraction and repulsion doesn't match what people expect to see. It's really hard for some to let go of the idea that spatial layout has meaning.
To some, the idea that location on a page has meaning of some kind is very deeply linked to their sense of what a visualisation is.
People sometimes like the sproinginess when a network visualisation resettles after a node has been dragged, but it can also be slow and irritating. Does it convey meaning? If not, why is it there?
The relationship between size, colour, weight isn't always intuitive - people add meaning where there might be none.
Another way of thinking about it - network visualisations are more abstracted than people expect.
Scroll down the page and you get graphs - sometimes they're much more positively received.
It's hard for novices to know which algorithmic and data-cleaning choices are significant, and which have a more superficial impact.
Credit: Mike Bostock's force-directed and curved line versions of character co-occurence in Les Misérables
Images travel extremely well on social media. When they do so, they often leave information behind and end up floating in space. Who created this, what does it represent? Can I trust it?
Also no sense of the source material represented by dots and lines. But here at least
When I showed this to a class recently, someone was frustrated that they couldn't 'see the wood for the trees'. General impression of density, no ability to dive deeper into detail.
(At least a hairball gives a sense of the density of the original dataset - sometimes that's masked by the simplicity of the final rendering.)
But when I started to explain what was being represented - the ways in which stories travelled from one newspaper to another - they were fascinated. They might have found their way there if they'd read the text but again, the visualisation is so abstract that it didn't hint at what lay underneath.
This matters more for historical networks than for literary ones, but even so, you might want to compare relationships between sections of a literary work
This matters more for historical networks than for literary ones, but even so, you might want to compare relationships between sections of a literary work
People find the interactive movement, ability to zoom and highlight links engaging, even if they have no idea what's being expressed. What's going on, what do the relationships mean? In class, people started to come up with questions about the data as I told them more about what was represented.
That moment of curiosity is an opportunity.
Frustration that 'Can't get to see a particular tree' [ref to earlier comment re wood for trees]
But - dots and lines might need to be recast to create an experience closer to public expectations - e.g. connect relationships to detail, more information when filtering - display more information about what's expressed, what the relationship means, quantification of info. Harder, but more interesting - hint at the texture or detail of that relationships. E.g. people wanted to see news stories (but obv hard with so much data)
One of the workshop questions was 'Are SNA theories and methods relevant for public-facing applications? ' - and maybe the answer is a qualified yes. As a working tool, they're great for generating hypotheses, but they need a lot more care before exposing them to the public.
During this workshop, at different points we may be talking about different 'users' - useful to scope who we mean at any given point. In this presentation, I'm was talking about end users who encounter visualisations, not scholars who may be organising and visualising networks for analysis.
As an outcome of the process, they're not necessarily the best way to present the final product.
Make yourself justify the choice to use network visualisations.
