Dan Olner:
Programmer viz maker geographer amateur economist climate obsessive & seeker of the perfect planning / chaos balance.
Researcher at Sheffield University’s Methods Institute, formerly with the Urban Big Data Centre, now with the Understanding Inequalities project.
danolner at gmail dot com. Twitter.
Recent(ish) stuff:
- A tale of two countries: a data story tool for looking at the English index of multiple deprivation
- “Systems not Lightbulbs: building pathways to zero carbon in higher education”: a guide developed with the team at Sheffield CNU.
- Do windfarms affect house prices in Scotland? A project for ClimateXchange, with Gwilym Pryce, Stephan Heblich and Christopher Timmins. See some of the groovy graphics from that project here, including how the line of sight model was used to identify green space visibility, accounting for buildings.
- “The spatial economics of energy justice: modelling the trade impacts of increased transport costs in a low carbon transition and the implications for UK regional inequality” (Olner, Mitchell, Heppenstall, Pryce) in Energy Policy (2020). Submission to the UK2070 Commission here. Visualisation of trade/money flows here.
- “Estimating the Local Employment Impacts of Immigration: A Dynamic Spatial Panel Model” (Fingleton, Olner, Pryce) Urban Studies (2020). Somehow, that journal’s most downloaded article ever. Uses the now-open Harmonised UK country of birth Census data 1971-2011 I assembled. That page includes a map of non-UK change in London from 1971 to 2011.
- How are house price moves linked across space? Visualising the network of linked house price movements in Glasgow.
- Introduction to the principles of visualising data in R using English house price data.
- 3D geographical data prints – this one is violent crime in Rotherham. (Town centre Friday night peak…)
Other stuff:
- Currently working on social frontier analysis using amazing Dutch data with colleagues at TU Delft, as well as helping to work out what social frontiers look extreme in cities, what should be expected.
- PhD: “an agent-based modelling approach to spatial economic theory.” Had some lovely interactive economic models I should have caught on youtube.
- Did a national survey analysis project for Good Things Foundation, Sheffield.
- Sometimes do data for good things in Sheffield.
Extremely other stuff:
- Made a motion detection system for turning people into monsters. Example here, code here. Went down well at party.
- Pub crawl optimiser. Because the power of spatial analysis should be used for good. (Actually, was to illustrate the awesomeness of R spatial analysis to the Sheffield R Users’ group. It meets in the Red Deer pub, so seemed appropriate.)
- Random walking across a bridge (while drunk, so possibly after using the pub crawl optimiser). A visualisation for showing how certain we can be about uncertainty.
- Every London house price in 3D 1995-2016. Tracking up into the stratosphere of the highest prices.
- That time I accidentally made some kind of life form while trying to make a spatial economic model. The little wiggle it does at ~8 seconds is particularly organic and predatory.
- Correcting the Global Warming Policy Foundation’s front page temperature graph. Poor things, it’s almost as if they cherry-picked.
- Occasional maker of hallucinogenic maps.
Some things from the coverinbees archive:
- Three adaptive landscapes: how humans are natural distributed systems makers, why it’s all tangled up with magic and why it means Hayek was wrong.
- Can a Tralfamadorian make predictions?
- Economics: reform or revolution?
- What’s the difference between a box-plot and an x-ray?
Am dreaming of:
- How data and viz can help support institution / town / city / region level decarbonisation that meets the Tyndall targets adopted by Manchester and Sheffield. The slack community at climateaction.tech might be thinking about similar things.
- Building an online MONIAC2 that shows clearly how macro works and why austerity is not only morally bankrupt but illogical. (Bit late now, mind.)
- A white Christmas. (Obv.)