Presentation by Alan Renwick of Urbs Media at the Data Journalism UK conference, Birmingham in December 2017

1. Urbs Media is a tech-driven editorial agency aiming to scale news
production. We organise open data to uncover news stories then
write them using technologies that enable automated production &
distribution of multiple, localised versions.
Global Editors Network named
us ‘Runners-Up’ in this year’s
Start Up programme
Our RADAR project with PA
received €706,000 funding
from Google DNI
Summer 2017

2. Social Problem
An ocean of important open
data unseen by citizens.
Democratic bodies not held to
account.
Industry Problem
A local media ecosystem
facing growing demand for
content but shrinking
resource.
Solution
Systematically mine open data
to find important, fact-based
stories; harness automation to
make this economic.
Empower reporters Empower citizens

3. Scalable input – stories from data to empower local
communities
“Our local news site? Today, a random series of events.
Tomorrow, another series of random events, unrelated to
what happened today. No attempt to make sense of how the
city works, or why.”
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Building a news service from data as the
input means:
‒ Stories are factual and verifiable
‒ Data points link over time to develop a
narrative arc
‒ Different data points combine to explain
what and why
‒ Scalability of data drives coverage and
comparability (do it once for everywhere)

4. Proof of concept - London data to test a city-wide site
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“Urbs.London is a
good example of
where we envisage
journalism needs to
go: Investigating
the much richer
data hubs that have
become available –
in transport, health,
public policies,
crime, jobs, and so
on – and
structuring relevant
narrative, not just
one-off stories to
inform local
audiences.”
Enders Analysis,
November 2015

5. Production scale: an editorial driven use of NLG –
writing stories (leverage), not reports (velocity)
‒ Identify newsworthy
localised datasets
‒ Mine data for story
lines
‒ Structure data to enable
automation
‒ Load data into Natural
Language Generation
tool
‒ Write story templates to
cover all eventualities of
story
‒ Template branching to
cover different
angles/emphasis
‒ Feed data through
template to produce
multiple local stories
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Scaled production needs an open market

7. Distribution scale - RADAR
‒ In September 2017 we started
RADAR in partnership with the
Press Association.
‒ Mass localisation service rolled out
to the news ecosystem, with the
build of a full end-to-end workflow
from source data to distribution.
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‒ Launch market UK - RADAR will
supply a daily diet of stories for each
local market, distributed via a new
channel.
‒ Full production capacity by February
2018; full distribution by May 2018.

8. Data tools to
organise and
find meaning
in data
Data Sources
Data Sources
Data Sources
Data Sources
Data Sources
Data Sources
NLG
Multiple
Story
Production
(Text)
Visuals
Story
Ingestion,
Targeting &
Distribution
Media Outlets
Media Outlets
Media Outlets
Media Outlets
Media Outlets
Media Outlets
Media Outlets
Media Outlets
Collection of inputs Content Package Production Deliver Content
Findkeydatasources
Identify,write&templatestory
Video
Samplecheckingfinishedpackage
RADAR builds the Urbs journalists’ workbench out into a
full-end-to end market service
Core Human Editorial Tasks Key Automation/AI Developments

9. Data Driven News – Market Readiness 2017
(Top 20)
Source: https://index.okfn.org/dataset/
Note: Chart shows top 20 markets (combined score)
Global Open Data Index – Markets Ranked by Overall Score (Bubble Size),
National Statistics and Administrative Boundaries
(2016-17, All Ranked 0 to 100)
10 markets have mature open data supply – with
more close behind

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