• An example: the propensity to cycle tool
• Using spatial modelling for social benefit

Many ways of saying the same thing:

• 'Policy-led research'
• 'Impact'
• 'Socially beneficial research'
• Don't be evil (Google)

My definition: building an evidence-base for sustainable systems.

• In the context of climate change that means:

• Building an evidence-base to transition away from fossil fuels

• But could also be interpretted in terms of other (quantifiable) social/economic/environmental indicators

• From Lovelace et al. (2011) - how to reduce transport-related emissions?
  • Source: https://doi.org/10.1016/j.enpol.2011.01.051

• And how does it differ from spatial modelling?

• How does it differ from good old 'GIS'?
• What does the science in the title mean?
• Why the focus on data rather than information

Code example:

d = frame_data(
  ~Attribute, ~GIS, ~GDS,
  "Home disciplines", "Geography", "Geography, Computing, Statistics",
  "Software focus", "Graphic User Interface", "Code",
  "Reproduciblility", "Minimal", "Maximal"
)

knitr::kable(d)

Reasoning:

• Evidence inevitably gets skewed by political aims

• If the people doing the research are influenced by dominant political forces, findings will be biases for political gain (solved by independent well-funded public research).

• People doing policy relevant research watch out (regarding politicians):

“Their very spirit undergoes a pervasive transformation,” and they finally end up as “experts at exchanging smiles, handshakes, and favors.” (Reclus 2013, original: 1898)

• If the data underlying policy is hidden, it can be represented to push certain aims (solved by open data)

• If the data is 'open' but the tools are closed, results open to political influence

• Which brings us onto our next topic…

Included in Cycling and Walking Infrastructure Strategy (CWIS) and the Local Cycling and Walking Infrastructure Plan (LCWIP)

Shows on the map where there is high cycling potential, for 4 scenarios of change

• Government Target
• Gender Equality
• Go Dutch
• Ebikes

• Origin-destination data shows 'desire lines'
• How will these shift with cycling uptake

• See www.pct.bike

Live demo of the Cycling Infrastructure Prioritisation Toolkit (CyIPT): https://www.cyipt.bike

• If it can work in Sheffield, it can work anywhere.

As a prominent Sheffield-based cycling advocate put it: ‘‘if cycling can work here, it can work anywhere in the world’’ (Bocking, 2010, personal communication) (Lovelace et al. 2011) - see https://doi.org/10.1016/j.enpol.2011.01.051

• Feasibility study on generalising PCT/CyIPT methods: https://github.com/ATFutures/who

It is clear that geographical research can have large policy impacts.

• That researchers can act to maximise the social benefit of the research
• That involves getting the evidence out to as many people as possible
• And using open source, accessible tools - the 'science' in GDS?

But many questions remain:

• Where to draw the line between impartial research and advocacy?
• To what extent should researchers open-sourcing their work defend against commercial exploitation?

• What can you do to maximise the social benefits arising from your work?

• Thanks for listening - get in touch via r.lovelace@leeds.ac.uk or @robinlovelace

• Check-out our open source book, Geocomputation with R
• Available on-line at:

• Source code:

• Collaboration - be in touch if you want to work on these methods/applications:
• PhD opportunities and more at https://www.its.leeds.ac.uk/

• Contribute to existing projects rather than 're-inventing the wheel'

• Upcoming course: R for Transport Applications - 26^th to 27^th April
• Learn cutting-edge methods underlying the PCT and more

• Leeds Institute for Data Analytics (LIDA)