1. Visualising domestic abuse migration in london
Women's journeys to seek refuge in London, April March 2016

2. Goals
This project visualises the 1165 journeys women made to seek refuge in London between 1st April 2015 and 31st March 2016.
It has been designed to illustrate how far and wide women migrate across London boroughs when seeking safety from an abusive partner.

3. Starting point Working with Women’s Aid
Can we develop an interactive map which builds on this GIS analysis by making these journeys engaging and intelligible?

4. Questions
Can an online data visualisation, in the form of an interactive map, improve engagement with the issue of domestic abuse migration amongst commissioners?
What is the most effective way to visualise journeys spatially in order to both communicate their complexity and yet ensure they remain intelligible and preserving anonymity of women/refuges?
How can interactive and animated features of geographic visualisations be employed to invite the audience to explore data and in doing so, interpret specific messages?
A technical dissertation using D3.js, an open-source javascript coding library for data visualisation and using data in .csv files to ensure we could update it or replicate it in other parts of the UK

5. prototypes

6. user testing and feedback from 25 professionals
The routes are confusing - I don’t know what to make of them
I really like all the information about one borough in the box but I would like to see the boroughs side by side to compare
This is so interesting, so Lambeth has 52 spaces and only 1 person from Lambeth stayed there. It’s the same in every borough. There must be something in this - it could show why funding has to follow the women and not the location.
I don’t know if this is good or bad, are there more people coming to Hackney because there are more spaces? How do you compare the different boroughs?
Questions: What was most interesting? Confusing? Questions as a result? Keep? Change?
Observations: number of boroughs looked at, order, awkward interactions, missed click buttons

7. case creation
As a… [Job Title/Role ] London Councillor who is sceptical about the value of funding pan-London services and the benefit to women in my borough
I want to… [What you need to do/learn from the map] see where women in my borough access refuge and which other boroughs are benefiting from women accessing refuge in my borough
So that I can… [The personal motivation] reassure myself the borough's money is well spent
And as a result…[What would change, metric of success] I’ll continue supporting London Councils pan-London funding

8. the result: All journeys
Key features: mouseover interaction, clear colour differentiation for routes in and out, arrows animated to show movement direction, journeys which are unknown, outside of London or unspecified in London clearly indicated

9. the result: journeys arriving
key features: More detail on borough names and a summary of the numbers of women from the borough, London, outside London and unspecified locations

10. the result: journeys leaving
Key features: As before but also emphasising the potential demand for refuge spaces alongside the placements in a refuge which were possible within the year

11. the result: site and context
Key features: Exit button, helpline number, direct interpretation, about page (not shown)

12. key Findings Women rarely stay in their own borough to seek refuge
Of the 746 women from London who were placed in a refuge in London in , only 51 stayed in their home borough
For each London borough, on average, women travel to 12 others. They made a total of 412 different journeys
Women’s diverse migration patterns extend across the UK
248 women travelled to London from across the UK to access a refuge, most were not from immediate neighbouring boroughs
Demand for refuge exceeds provision across London
There were 5399 calls to the National Domestic Violence helpline and 812 refuge spaces available (854 spaces are required to meet the Council of Europe minimum standard of 1 family space per 10,000 population)

13. What I learnt
Understanding of the issue by engaging with data and finding ways to communicate this visually
What makes a ‘good’ digital story and how interactive visualisations help
Data always has implications for those it is about and for us
We have a duty of care to use the data we ask for, wisely
Other areas we covered
Using twitter data for social research, open-source tools in social change, digital journalism

14. back to work We now publish to 360giving
Tech Vs Abuse project culminates Nov 2016
Tech for Good Funding with Paul Hamlyn Foundation

15. Website link coming really really soon…
Nissa Ramsay
@nissaramsay
Website link coming really really soon…