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An introduction

Using Mobile Phone Meta Data For National Statistics. An introduction May Offermans , Martijn Tennekes , Alex Priem , Shirley Ortega en Nico Heerschap. Content. 1 Data Sources Event Data Records(EDR) Customer databases 2 Privacy and processing 3Results Applications in statistics

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An introduction

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  1. Using Mobile Phone Meta Data For National Statistics An introduction May Offermans, MartijnTennekes, 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 Titel van de presentatie 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 ->>>>

  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 = CDR’s) Vodafone

  9. Privacy & Process (3) • Advantages • Save, quick, fast, cheap, limits the risksand no personal data • Disadvantages • Does not fit currentmethodologicalpractice • No personal data, socannotbecoupledtoother personal data. • Persons are notfolloweddirectly • No direct weighing

  10. Research • ‘New’ statistics- > Daytime population • Tourism statistics -> Inbound tourism Titel van de presentatie

  11. Results (1) - Daytime Population Source: Vodafone/Mezuro, compiled by SN

  12. Results (2) - Day time population Municipal Personal Records Database Almere: commutertown? 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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