Anonymized Call Detail Records
Buy and sell anonymized call detail records data. Aggregated call/text patterns (no PII) reveal communication network structures. Social graph AI needs CDR-derived datasets.
No listings currently in the marketplace for Anonymized Call Detail Records.
Find Me This Data →Overview
What Is Anonymized Call Detail Records?
Anonymized Call Detail Records (CDR) are aggregated telecommunications datasets that capture call, SMS, and internet activity patterns without personally identifiable information. These records are organized by geographic location and time interval, revealing communication network structures and mobility dynamics across regions. CDR datasets have been widely used in academic research, humanitarian applications, and data science projects to understand human behavior, mobility patterns, and network connectivity while maintaining user privacy through anonymization techniques.
Market Data
10,000 grid cells per city (~200m per side)
Typical Geographic Granularity
Source: arXiv
10-minute intervals (144 samples per day)
Temporal Resolution
Source: arXiv
55% success rate for active users (3-4 trips/day)
De-anonymization Risk (4-week observation)
Source: ResearchGate
Call activity, SMS patterns, internet usage
Primary Data Components
Source: arXiv
Who Uses This Data
What AI models do with it.do with it.
Traffic Prediction & Network Planning
Telecom operators use internet activity CDR data to forecast load and optimize network capacity across geographic grids.
Emergency Management & Humanitarian Response
UN agencies, governments, and NGOs analyze aggregated CDR to improve early warning systems, flooding response, and disaster management.
Mobility & Urban Research
Academic researchers leverage CDR to study human movement patterns, communication networks, and spatial-temporal dynamics in urban environments.
Social Graph & Network Analysis
AI systems and data scientists use CDR-derived communication patterns to map social networks and identify community structures.
What Can You Earn?
What it's worth.worth.
Academic/Research License
Varies
Pricing depends on dataset size, geographic coverage, and temporal span.
Commercial Deployment
Pricing varies based on volume, exclusivity, and licensing terms
Note: Market research reports about this category typically run several thousand dollars, but actual data licensing prices are negotiated case-by-case based on volume, freshness, and exclusivity.
Government/Public Sector
Varies
Specialized pricing for humanitarian organizations and official statistics agencies.
What Buyers Expect
What makes it valuable.valuable.
Robust Anonymization
Data must employ strong privacy-preserving techniques (k-anonymity or equivalent) to prevent re-identification attacks using social network or geo-referenced external data.
Consistent Temporal Granularity
Buyers require regular sampling intervals (e.g., 10-minute or 15-minute) over extended periods to enable reliable traffic modeling and pattern analysis.
High-Resolution Geographic Coverage
Datasets should provide fine-grained spatial organization (grid-based cells ~200m per side) to support location-aware applications and emergency response systems.
Multi-Modal Data Components
Quality datasets include call, SMS, and internet activity metrics to provide comprehensive communication and traffic patterns.
Companies Active Here
Who's buying.buying.
Network optimization, traffic prediction, and capacity planning using internal and collaborative CDR datasets.
Mobility research, social network analysis, and privacy-preserving data publishing using open-source CDR datasets.
Humanitarian aid, emergency management, and official statistics generation via data collaboratives.
FAQ
Common questions.questions.
What is the difference between CDR and raw location data?
CDR captures aggregated communication patterns (calls, SMS, internet usage) organized by geography and time, while raw location data tracks individual movements. CDR is anonymized at the aggregate level, making re-identification more difficult than individual location traces, though re-identification risks still exist when combined with external datasets like social networks.
Can anonymized CDR be de-anonymized?
Yes. Research shows that anonymized CDR can be re-identified by linking it with external information such as social network check-ins or other geo-referenced datasets. Success rates depend on observation period (55% after 4 weeks for active users) and the richness of external data available to attackers.
What privacy protections are used for CDR datasets?
Common techniques include k-anonymity, data aggregation by grid cell and time interval, and removal of direct identifiers. However, these protections have known limitations—research demonstrates that temporal and spatial co-occurrence patterns can still enable re-identification when combined with side information.
Who typically buys and sells CDR data?
Buyers include telecom operators, academic researchers, government agencies, and humanitarian organizations. Data is often shared through data collaboratives or research partnerships rather than traditional commercial marketplaces, reflecting privacy and regulatory sensitivities.
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