Work Package on Mobile Phone Data

Transcription

1 Work Package on Mobile Phone Data Coordination Group Meeting WP5 ESSnet on Big Data Brussels, October, 2017

2 Raw Telco Data Preprocessing Statistical MicroData Aggregation Aggregated Data Inference Product Data availability Mostly, aggregated data (FI, UK, DE, NE) Highly restricted access to microdata (IT, BE, FR) No access at all (RO, ES) Work in Unattainable phases Positium Report Attainable phase Research on ecological-like models on species abundance WP5 (ESSnet on Big Data) Work Package on Mobile Phone Data October 2 / 13

3 Premises for the approach and its undergoing implementation: To integrate official data into the estimation process to avoid duplicated official figures making territorial and time scopes compatible in published figures. Proof of concept Methodology IT. Quality aspects integrated by design inference (not just estimation). Specific high-level goals: To propose elements for a standard description of mobile phone data sets (micro and aggregated). To propose a methodological framework to infer (general, tourist, commuters,... ) population counts from aggregated mobile phone data and official data. WP5 (ESSnet on Big Data) Work Package on Mobile Phone Data October 3 / 13

4 Description of mobile phone data sets: Description of data sets from each WP member. Attendance to Joint UNECE/UN-GGIM Workshop on Integrating Geospatial and Statistical Standards, November 6-8 in Stockholm, Sweden. WP5 (ESSnet on Big Data) Work Package on Mobile Phone Data October 4 / 13

5 Inference: (N MNO, N REG ) 1 1 (N MNO, N REG ) 2 2 (N MNO, N REG ) I I. Computer Tool P ( N N MNO ; N REG) P ( N i N N MNO ; N REG) =E [ N i N MNO ; N REG],... P(N i I i ) (credible intervals) V [ N i N MNO ; N REG],... WP5 (ESSnet on Big Data) Work Package on Mobile Phone Data October 5 / 13

6 At a given time instant: N MNO i Bin(N i, p i ), N MNO i N MNO j, i j = 1,, I N i Po ( ) β λ N REG i, Ni N j, i j = 1,, I p i Beta(α i,β i ), p i p j i j = 1,, I f N REG(α i +β i ) i (α i,β i ), (α i,β i ) (α j,β j ), i j = 1,, I α i +β i β λ uninformative (β λ > 0), For a sequence of time instants: use of transition probabilities (to be formulated). WP5 (ESSnet on Big Data) Work Package on Mobile Phone Data October 6 / 13

7 Internal meetings: Madrid, 7-8 June. Minutes uploaded. agreements on the plan presented here. Sofia, during dissemination workshop in Feb WP5 (ESSnet on Big Data) Work Package on Mobile Phone Data October 7 / 13

8 Achievements, ongoing and remaining tasks: Description of mobile phone data sets: Description from each WP member Elements for a standard Inference: Preliminary analytical results Prototype functions in R to conduct a simulation study using Spanish population register data From prototype to scalable and robust tool Application to real mobile phone data sets Analysis of results WP5 (ESSnet on Big Data) Work Package on Mobile Phone Data October 8 / 13

9 Planning (still to be internally discussed when prototype functions are ready): Deliverables 1.3 and 1.4 on methodology and IT needs by Jan 31 (application to real data sets conducted). Deliverable 1.5 on quality and possible future trends by April 30. May for catching up with potential delays and general improvements of dissemination documents. WP5 (ESSnet on Big Data) Work Package on Mobile Phone Data October 9 / 13

10 Use of sandbox From prototype to scalable tool. Strong issue in data shareability. WP5 (ESSnet on Big Data) Work Package on Mobile Phone Data October 10 / 13

11 Access as well as methodology must be considered in the long term. New methodology at NSIs (at least in Spain) collaboration with universities and research centres. formation of statistical staff. change of inference paradigm. Flexible methodological framework (more aux info,... ) scope of results: how far do we go in this ESSnet? Shareability of computer tool (in spirit of ESS VIP SERV) more time needed to develop. WP5 (ESSnet on Big Data) Work Package on Mobile Phone Data October 11 / 13

12 Is it possible to adjust the framework for similar situations with other data sources? Is it possible to adjust the framework to combine diverse data sources (indeed we are combining administrative and mobile phone data)? WP5 (ESSnet on Big Data) Work Package on Mobile Phone Data October 12 / 13

13 No budget detected. WP5 (ESSnet on Big Data) Work Package on Mobile Phone Data October 13 / 13