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Needs for Anonymized Mobile Data

Needs for Anonymized Mobile Data. Discussion Topic / Working Group Seminar 08471. What do we need to learn?. Applications Importance Societal Supportable Privacy constraints Knowledge What information must be present in the data? Structure

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Needs for Anonymized Mobile Data

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  1. Needs for Anonymized Mobile Data Discussion Topic / Working Group Seminar 08471

  2. What do we need to learn? • Applications • Importance • Societal • Supportable • Privacy constraints • Knowledge • What information must be present in the data? • Structure • How should the data be represented to make learning easy? Seminar 08471: Geographic Privacy-Aware Knowledge Discovery and Delivery

  3. The Killer App(s) for Anonymized Data • Context and Location Aware Services • When can we have expectation of privacy (sensors)? • Expectation “in a crowd” vs. “in the Wald” • Public Safety • Emergency response, evacuation • Public security / law enforcement • Lookup/location advertising • Business workflows – factory, logistics – real-time response • Traffic / transportation • Mixed-reality games • Enhanced tourism / Edutainment • Location Microdata • Public Safety • Planning • Investigation • Health research • Personal health-related data (e.g., exercise data, environmental sensors) • Epidemiology, pathology • Collaborative filtering / collaborative recommendation • Geomarketing • Business workflows – factory, logistics – real-time response • Urban planning Seminar 08471: Geographic Privacy-Aware Knowledge Discovery and Delivery

  4. Information Required • Frequent vs. outlier • Location vs. trajectory • Data quality • Exact? • Probabilistic? • Generalization of truth? Trajectory Patterns (Dino) example of learning that involves approximation Seminar 08471: Geographic Privacy-Aware Knowledge Discovery and Delivery

  5. Real-time traffic analysis and services(Infomobility): Information Required • Frequent vs. outlier • Outlier events • Frequent normality • Location vs. trajectory • Generally want trajectory, planned destination • Aggregate data largely sufficient • Sometimes point data sufficient (e.g., accident) • Service: Need to know current location, destination • Can this be provided anonymously? • Background information • Road network • Calendar / events • Data quality / Granularity • Granularity: road segment • Outlier events – exact • Frequency – probably want relatively close to exact, particularly when near capacity Seminar 08471: Geographic Privacy-Aware Knowledge Discovery and Delivery

  6. Research on anonymized (geo) Health Info.: Information Required • Geospatial information • Sensor-based / atmospheric conditions • Geography – relevant semantics • Telemedicine – magnifies geospatial variables • Ex: Continuous heart monitoring • Frequent vs. outlier • Outlier population / Adverse Drug Events • Sporadic events (e.g., heart conditions) • Location vs. trajectory • Location@time referenced with conditions • Conditions inferred from trajectory and georeferenced data • Correlation between individuals based on colocation (not necessarily in time) • Data quality • Exact? • Probabilistic? • Generalization of truth? (Don’t tell them what the real data is) • Define policy before technology hits the market Seminar 08471: Geographic Privacy-Aware Knowledge Discovery and Delivery

  7. Privacy and Web 2.0 • Change in sensitivity? • What does privacy mean when people volunteer/publish data? • (Particularly mobile/georeferenced data) • Interplay of privacy and trust • Do people know what they are giving up? • Inference • Archival • Psychological privacy vs. quantifiable risk • Context for privacy • How does integration of other data with location affect privacy? • Anonymity in the presence of external information? Seminar 08471: Geographic Privacy-Aware Knowledge Discovery and Delivery

  8. Seminar Proceedings Killer App • Traffic Data • Health Data Research Web 2.0 outline • Kinds of geospatial self-published data • Uses • Risks / (Mis)uses <above 1 axis, below 2nd axis> • What do we do about this? • Education • Regulation • Policy • Technology • Risk Assessment Research Agenda Seminar 08471: Geographic Privacy-Aware Knowledge Discovery and Delivery

  9. Other “next steps” Seminar 08471: Geographic Privacy-Aware Knowledge Discovery and Delivery

  10. Seminar Proceedings • Killer Apps. for anonymized data • Description • Data needs • Anonymity/privacy • Traffic Data • Health • Privacy in Web 2.0 • What is self-published geospatial data? • Uses/value? • Privacy concerns: • Risk • Perceptions • Recommendations Seminar 08471: Geographic Privacy-Aware Knowledge Discovery and Delivery

  11. Data RepresentationEnable use of existing tools? • Identical to real data • Reconstruct representative trajectories (Saygin, Nergiz, Atzori GIS’08) • Region bounds • Region distributions (PDF) Seminar 08471: Geographic Privacy-Aware Knowledge Discovery and Delivery

  12. Context for Privacy Discussion Topic / Working Group Seminar 08471

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