1.
Security and Legitimacy in a
Web Observatory
Kieron O’Hara, Alistair Sackley, Ian Brown,
Ramine Tinati, Thanassis Tiropanis & Xin Wang
presented at Workshop on Building Web Observatories,
WebSci14, Bloomington, Indiana, 23 June 2014

2.
Complex England & Wales Policing
Context
• 43 regional police forces
• Several specialised national bodies
• E.g. Serious Fraud Office
• Many multi-agency partnerships
• E.g. Integrated Offender Management
• Data only loosely standardised
• Some brought together in national open data
site police.uk
• Police data v performance data
• Extremely sensitive personal data

3.
Policing Requirements
• Highly data (intelligence) driven
• Need to retain legitimacy
• Policing by consent
• Greater scrutiny
• Cost constraints
• Control
• Data protection liability for personal data
• Big IT mindset
• Risk aversion

4.
Data Management Requirements
• Effective
• The right people get the data at the right time
• Safe
• Data subjects (victims, witnesses) not exposed
• Secure
• Investigations not compromised
• Transparent
• Open to democratic scrutiny

5.
Potential for Web Obs Contribution
to Data Management
• Control
• Security
• Privacy
• Discriminating
sharing

6.
Potential for Contribution to
Engagement Strategy
Leigh Park Twitter mention network
(High IMD [index of multiple
deprivation])
Eastleigh Twitter mention network
(Diverse area with pockets of deprivation)

7.
Potential for Contribution to Low-
Level Intelligence Gathering
• NOT surveillance, but understanding
• Only a small Twitter community in Leigh Park
• What are the appropriate sources of online data?
• Engagement means taking part (e.g.
retweeting)
• Placing police data in context of public and
open data
• Opening out some police data/analytics to
community groups, or even making it open

8.
Need to Demonstrate
• Security
• Data protection
• Preservation of data control
• Potential of “safe haven”
• Utility
• Legitimacy
• Low/justified cost
• Compatibility with more traditional data
• Compatibility with workflow