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
2Content
- 1 Data Sources
- Event Data Records(EDR)
- Customer databases
- 2 Privacy and processing
- 3Results
- Applications in statistics
- Daytime population
- Tourism
-
- 4 Conclusions
3Source 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
4Source 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)
5Applications 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
6Population
Source Vodafone/SN
7Privacy 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
8Privacy 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
9Privacy 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
10Research
- New statistics- gt Daytime population
- Tourism statistics -gt Inbound tourism
-
11Results (1) - Daytime Population
Source Vodafone/Mezuro, compiled by SN
12Results (2) - Day time population
Municipal Personal Records Database
Almere commuter town?
Source Vodafone/Mezuro, compiled by SN
13Tourism
Inbound tourism Roaming data
14Results (1) Tourism
- German tourists ( devices)
Source Vodafone/Mezuro, compiled by SN
15Tourism (2) German tourists at the coast
Devices
Rainfall
Source Vodafone/Mezuro, compiled by SN
16Tourism (3) Portugese roaming
Portugese roaming data during 2013 UEFA Cup
League final, Benfica (Portugal) - Chelsea
(England)
Source Vodafone/Mezuro, compiled by SN
17Tourism (4)
Source Vodafone/Mezuro, compiled by SN
18Tourism (5) Different type of communication
Source Vodafone/Mezuro, compiled by SN
19Conclusions 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?