Mark Birkin Professor of Spatial Analysis and Policy, School of Geography, University of Leeds Director, ESRC Consumer Data Research Centre Director, Leeds Institute for Data Analytics

Microsimulation, Big Data and Predictive Analytics

•  National statistical authorities •  UK Government departments •  Research Institutes •  World-wide data archives

•  Identifying suitable data •  Negotiating access •  Identifying a safe data

access setting

Administrative Data Research Network

Phase1 Phase2 Phase3

Social Media Data & Third Sector Data

Further

announcements soon

ESRCBigDataNetwork

Multilateral data

sharing

Case studies & academic publications

Metadata & provenance

Business engagement & awareness

raising

Providers

Partners

Prospects

Participants

CDRCDataPartners

CDRCDataPartners

HealthSimula=on

Spa$alMicrosimula$on(2011)

GenderxAgexEthnicity

GenderxAgexIllness

GenderxAgexNSSEC

GenderxAgexCarownership

ELSAWave5

HybridMicrosimula$on(2011to2031)

AdjustedProjec$ons

GenderxAgexEthnicity

ETHPOP2011to2031Projec$ons

CHD;stroke;diabetes;cancer;respiratoryillness;

arthri$sanddepression

HazardModel

2011Census

ELSAWaves1to6

Takeaccountoffutureethniccomposi=onofthelocalauthoritypopula=on

ClarkS.,BirkinM.,HeppenstallA.(2014)Subregionales$matesofmorbidi$esintheEnglishelderlypopula$on,Health&Place.

Health(2)

Health(3)

Health (4): App Data

Clockschange Clockschange

Weeklyac$vityreadingsfromtheBountsapp:

Key:

Transport: Cycling

Blue = commuter cycling potential Green = travel to school cycling potential

Source:hZp://rpubs.com/RobinLovelace/245696

Transport: Trains

Transport: Trains

Journeytowork

Transport: Journey Planning

Infrastructure

Infrastructure

Zuoetal(2014)Geospa$alInforma$onScience,17,3,153-169.

Energy

Retailing/Consump=on

Retailing/Consump=on

RecaponExamples

“anewmethodofpushingforwardthefron$ersofknowledge,enabledbynewtechnologiesforgathering,manipula$ng,analyzinganddisplayingdata”

TheFourthParadigm…

Thousand years ago, science was empirical, describing natural phenomena

Last few hundred years, theoretical branch, using models, generalizations

Last few decades, a computational branch, simulating complex phenomena Today, data exploration (eScience)

synthesizing theory, experiment and computation with advanced data management and statistics à new algorithms!

(Alex Szalay)

Predic=veAnaly=cs

•  Dataisgrowing,butwhataboutyourabilitytomakedecisionsbasedonthosehugevolumesofdata?

•  SuccesswilldependonhowquicklyyoucandiscoverinsightsfromallthatdataandusethoseinsightstodrivebeZerac$onsacrossyouren$reorganiza$on

•  That’swherepredic$veanaly$cs,datamining,machinelearninganddecisionmanagementcomeintoplay.

–  Predic$veanaly$cshelpsassesswhatwillhappeninthefuture.–  DatamininglooksforhiddenpaZernsindatathatcanbeusedtopredictfuture

behaviour.Businesses,scien$stsandgovernmentshaveusedthisapproachforyearstotransformdataintoproac$veinsights.

–  Decisionmanagementturnsthoseinsightsintoac$onsthatareusedinyouropera$onalprocesses.

–  (sas.com)

A Note on Synthesis

•  Twodefini$onsofSynthe.c:– devised,arranged,orfabricatedforspecialsitua$onstoimitateorreplaceusualreali$es

– madebycombiningdifferentsubstances:notnatural

•  Thesecondisrelevantaswellasthefirst!

Three problems for MSM

•  Calibra$on– andvalida$on?– especiallyinreal-$me

•  Behaviour– Fromdemographicstructuretoac$vi$esandimpacts

•  Predic$veanaly$cs–  robustnessandrelevance

•  Microsimula=onneedsBigData!

Three problems for Big Data •  Representa$onbias

–  Inferencesforthepopula$on,notthesample

•  Synthesis– Contextisalwayscrucial

•  Privacy,confiden$ality,ownershipandtrust– Conflictbetweengranularityanddisclosure

•  BigDataneedsMicrosimula=on!!

Conclusions

•  StrongsynergybetweenMSMandBigData•  Dynamicsovermul$plescalesincreasinglyimportant

•  Considersynthe$cpopula$onsassynthesisingaswellassynthesised