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What is CDR data (Call Detail Records)

CDR data are owned by Mobile Network Operators (MNOs) and are generated each time a mobile phone subscriber makes or receives a call/text or uses mobile data. Each record includes an anonymous identifier of the subscriber, a timestamp, and the cell tower that the transaction was routed through. CDRs can be useful mobility resources as they contain a record of each subscriber’s approximate location (the location of the cell tower) each time they use their phone.

How can I get access to mobility data?

The respective mobile operators are the owners of their mobile data. Which data can be shared and with whom will differ depending on country, operator and circumstances. Flowminder can support the coordination of this process and we will later add to this website a form enabling you to register your interest. In the meantime please email us with countries of interest (low-and middle-income countries only), type of indicators of interest and type of research or analyses you intend to do. Some indicators may be made public and if this is the case it will be posted here. No individual data or call detail records will ever be shared.

How do I get access to CDRs ?

The only way to obtain access to CDRs or other mobile phone data is by forming a partnership with a mobile network operator that will grant you access to their data. Flowminder does not have ownership of any mobile phone datasets.

How is the mobile phone data collected?

CDR data is produced as a byproduct of normal phone use. Each SIM card has a unique ID and a new record is created by their Mobile Network Operator (MNO) for billing purposes, each time it is used for a call, SMS or data. That record includes a timestamp and a location stamp. This is generated from the signal sent after each phone use to the nearest cell tower mast to process the call/SMS/data use. The record registers the location of the mast, not of the phone user themselves.

Can subscribers be identified / tracked with this type of analysis?

All of the outputs produced by Flowminder’s code are anonymised aggregated data, meaning that the data is presented as a grouped summary and does not contain any information about individual subscribers, ensuring that the personal privacy of all subscribers is maintained at all times. CDR data contain a record of each subscriber’s approximate location (the location of the cell tower) each time they use their phone, not their actual location.

Can I use CDR data for contact-tracing?

Identifying the personal contacts of individual subscribers is a privacy-invasive activity that requires access to data about individuals. This is not part of Flowminder’s offering. A direct discussion with the Mobile Network Operator is required. We would also recommend contacting an organisation such as the World Health Organisation or your relevant Centre for Disease Control to evaluate the effectiveness of the technique.

Can I use CDR data for contact-tracing?

Identifying the personal contacts of individual subscribers is a privacy-invasive activity that requires access to data about individuals. This is not part of Flowminder’s offering. A direct discussion with the Mobile Network Operator is required. We would also recommend contacting an organisation such as the World Health Organisation or your relevant Centre for Disease Control to evaluate the effectiveness of the technique.

CDR data provides estimates “near real time”. What does this mean?

A true ‘real-time’ estimate would mean that an estimate is available instantaneously (or with a few seconds’ delay) after an event. Due to the way that CDR data is processed and analysed, it is typically not possible to achieve this level of instantaneous response. It is reasonable to expect estimates to be available between one and a few days after an event. Another reason for delaying the dissemination of outputs is to avoid misuse of the data (see here.)

Not everyone uses a mobile phone, so how do you know that the analysis you produce from mobile phone data is representative of the full population?

A mobile phone dataset is unlikely to be perfectly representative of the entire population of a country, because not everyone uses a mobile phone, and not all mobile phone users are subscribed to the operator that is providing their data. In spite of these limitations, the dataset can still provide a good indicator of changes in a population’s movements because a significant proportion of the population are included in the dataset. For example, if the dataset shows that mobility has reduced by 50 percent in one region, then although it may not be the case that the mobility of the entire region’s population has also decreased by exactly 50 percent, we could be confident that mobility has decreased by a significant amount.

Whilst further work is needed to understand the extent to which analyses of telecommunications datasets result in biased estimates of population movements, the limited studies which exist have shown that such analyses have a high degree of validity. An illustrative research study on the subject showing a high correlation between mobile phone and population mobility at a national level in a humanitarian setting can be found here.