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An introduction

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Using Mobile Phone Meta Data For National Statistics An introduction May Offermans, Martijn Tennekes, Alex Priem, Shirley Ortega en Nico Heerschap – PowerPoint PPT presentation

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Title: An introduction


1
  • Using Mobile Phone Meta Data For National
    Statistics
  • An introduction
  • May Offermans, Martijn Tennekes, Alex Priem,
    Shirley Ortega en Nico Heerschap

2
Content
  • 1 Data Sources
  • Event Data Records(EDR)
  • Customer databases
  • 2 Privacy and processing
  • 3Results
  • Applications in statistics
  • Daytime population
  • Tourism
  • 4 Conclusions

3
Source Call Detail Records/ Event Data Detail
Records
  • Call Detail records can contain many variables
    like
  • the phone number of the subscriber originating
    the call (calling party)
  • the phone number receiving the call (called
    party)
  • the starting time of the call (date and time)
  • the call duration
  • the billing phone number that is charged for the
    call
  • the identification of the telephone exchange or
    equipment writing the record
  • a unique sequence number identifying the record
  • the disposition or the results of the call,
    indicating, for example, whether or not the call
    was connected
  • call type (voice, SMS, etc.)
  • Each exchange manufacturer decides which
    information is emitted on the tickets and how it
    is formatted. Examples
  • Timestamp

4
Source Mobile Phone MetadataCall Detail
Records/ Event Data Detail Records
  • Monthly 4 Billion Event Data/Detail Records of
  • 6-7 million users contains information of
  • Antenna location
  • Time indicator
  • In- or outgoing
  • Technology information (data, sms, call
    ..dual/umts)
  • Roaming (foreign devices)
  • Customer database (unique number of foreign
    callers per months)

5
Applications under research
  • Daytime population
  • Mobility, of which tourism
  • Safety
  • Demographics
  • Border traffic
  • Economical activity
  • Disaster management or safety planning
  • Use of public services
  • Sociology (calling patterns)
  • Health

6
Population
Source Vodafone/SN
7
Privacy Process (1)
  • Problems big data
  • Dynamical data source that keeps on growing
  • Daily change of antenna locations (4G)
  • Software
  • Transporting data
  • Security issues
  • Privacy
  • Costs -gtgtgtgt

8
Privacy Process (2)
Validated output for mobility reporting
  • Anonymized aggregated data
  • Micro data from the mobile network will be
    transferred to a new server system.
  • During this process most sensitive variables
    become hashed or deleted.
  • Only Mezuro has access to the process to collect
    aggregated anonymized data

Mezuro
Aggregation validation (Anonymisation phase 2)
Automated blind analysis
Solution, controlled by Vodafone
Replace User-IDs (Anonymisation phase 1)
Traffic data (Events CDRs)
Vodafone
9
Privacy Process (3)
  • Advantages
  • Save, quick, fast, cheap, limits the risks and no
    personal data
  • Disadvantages
  • Does not fit current methodological practice
  • No personal data, so cannot be coupled to other
    personal data.
  • Persons are not followed directly
  • No direct weighing

10
Research
  • New statistics- gt Daytime population
  • Tourism statistics -gt Inbound tourism

11
Results (1) - Daytime Population
Source Vodafone/Mezuro, compiled by SN
12
Results (2) - Day time population
Municipal Personal Records Database
Almere commuter town?
Source Vodafone/Mezuro, compiled by SN
13
Tourism
Inbound tourism Roaming data
14
Results (1) Tourism
  • German tourists ( devices)

Source Vodafone/Mezuro, compiled by SN
15
Tourism (2) German tourists at the coast
Devices
Rainfall
Source Vodafone/Mezuro, compiled by SN
16
Tourism (3) Portugese roaming
Portugese roaming data during 2013 UEFA Cup
League final, Benfica (Portugal) - Chelsea
(England)
Source Vodafone/Mezuro, compiled by SN
17
Tourism (4)
Source Vodafone/Mezuro, compiled by SN
18
Tourism (5) Different type of communication
Source Vodafone/Mezuro, compiled by SN
19
Conclusions for tourism
  • Potential
  • Replace existing statistics and new statistics
  • Smaller area and smaller timeframes
  • Events
  • Also when 24 hour limit is dropped
  • Daytrips and number overnight stays
  • Flows of tourists
  • Tourist related areas
  • Rather trends then volumes (benchmarking)
  • Privacy issues, but also access (telecom
    providers)
  • New methodological issues/new framework
    (representativeness)
  • Role of national statistical offices?
  • Revolutionary or evolutionary?
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