1. DSSG.UCHICAGO.EDU @datascifellows

2. Finding New Strategies to ReduceMaternal MortalityOffice of the President of MexicoThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 3. Lagging behind its goalsSeguro Popular* Target between 1990 and 2015 is projected100908070605040302010Progresa/OportunidadesThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014Actual, 2012:42Actual, 1990: 89Target, 2015:2301990 1995 2000 2005 2010 2015Maternal Mortality Ratio (MMR)Actual vs. Target Maternal Mortality RateActual MMR Target MMR* 4. Predictive modeling to inform policyDataCensus DataPatient RecordsHospitalInformationBirth & DeathRecordsRisk ModelThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 5. Key factors identifiedRisk Model Key FactorsHealth Care Hospital Type InsuranceThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014Poverty Marginalization EducationAccessibilityCesarean SectionsPrenatal Care 6. Detecting Collusion, Corruption, andFraudWorld Bank GroupThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 7. $$$Diagram: Francis Gagnon and the World Bank GroupThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 8. General Electric CompanyThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 9. The Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 10. Using Data to Target and AssessUrban RevitalizationCity of MemphisThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 11. Where are distressed properties?The Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 12. What is the impact of rehabilitation?The Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 13. Smarter Outreach for HealthInsurance EnrollmentEnroll America & Get Covered IllinoisThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 14. The Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 15. Optimizing the call list1009080706050403020100Effort for one conversionThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 16. Spanish advertising worksThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 17. Predicting Success in Mother-ChildInterventionsNurse-Family PartnershipThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 18. When and Why Do Moms Leave?The Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 19. Positive Outcomes for Moms Who StayThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 20. Targeted InterventionsThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 21. Targeted InterventionsThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 22. Predict Social Service OutcomesHealth LeadsThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 23. Types of Needs Utilities Food Transportation Employment Housing 40% of Clients DisconnectPROBLEMReduce DisconnectionsGOALThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 24. Need Complexity ResponsivenessData-InformedInterventionsThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 25. Need Complexity ResponsivenessData-InformedInterventionsNeeds:Food Stamps,Electricity,GasDay 1 Day 30Needs:Rental Assistance,Job Training, MedicalTransportThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014Day 50 26. Need ComplexityDay 1 Day 30Data-InformedInterventionsThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014Day 50Responsiveness 27. Need ComplexityDay 1 Day 30Data-InformedInterventionsThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014Day 50Responsiveness 28. Evaluating Pathways to Stable HousingChicago Alliance to End HomelessnessThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 29. Toward a Better System6,7155,9226,240The Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 20146,5462005 2007 2009 2011PersonsExperiencingHomelessnessYearSource: Point in Time Counts, 2005 - 2011 30. Program Type MattersProgramType OutcomePermanentShort TermEmergencyThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014StablyHousedUnstablyHoused 31. Program Type MattersProgramType OutcomePermanentShort TermEmergencyThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014StablyHousedUnstablyHoused 32. Other Things Matter Too66 Years OldHospitalVeteran$55038 Years OldLived w/ FriendsSNAPNo Earned IncomeThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 33. Mining Congressional Spending Bills forEarmarksHarris School of Public Policy & Sunlight FoundationThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 34. Machines Identifying EarmarksCongressionalBills andReportsIdentifyAppropriationsThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014ClassifyEarmarks 35. Office of Managementand BudgetTime: 3 Months / YearData Science forSocial GoodTime: 30 min / CongressThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 36. Predicting Back-to-SchoolEnrollment forBudget AllocationChicago Public SchoolsThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 37. The Budget Allocation ProblemBudget Is Set forNext Year20th Day ofSchool YearAllocationsBased onPredictionsApril SeptemberThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 38. If all 9th graders went to theirneighborhood schoolCatchmenthigh schoolsNSThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 39. Where 9th graders actually go to schoolN S N SCatchment high schools Non-Catchment high schoolsThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 40. Student-Level Model Female Hispanic Receives reducedpriced lunches High academicachievementThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 41. Schools in 2012The Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 42. School Closings in 2013The Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 43. School Openings in 2013The Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 44. Catchment SchoolThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 20140Student-Level Model 45. Student-Level ModelThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 20140Catchment School 46. Top Quality SchoolCatchment SchoolThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 20140Student-Level Model 47. Student-Level ModelTop Quality SchoolCatchment SchoolThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 48. Identifying Skill Gaps to ReduceUnemploymentSkills for Chicagolands FutureThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 49. The Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014Unemployment RateUnemployment 50. Hiring Potential in ChicagoThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 51. Skill Gap in Computer Software IndustryThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 52. The Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 53. Temporospatial TemperatureInterpolationThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 54. Making Smart Meters Work forConsumersPecan Street & Village of Oak ParkThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 55. Smart MetersDATAThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 56. Energy Usage DataThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 57. Heating and Cooling ConsumptionThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 58. Evaluating ConsumptionThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 59. 800 Energy(kWh)|September2012|January2013|May2013The Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014|January2014|September20130Evaluating Consumption 60. Appliance Signal DecompositionThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 61. Learn from your data!smartenergyactions.orgThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 62. Identifying Students at Risk Accuratelyand EarlyMontgomery County Public SchoolsThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 63. Student Paths Through MCPS12% of studentsdo not graduate on timeThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 64. Improving Accuracy of Risk Score Model807060504030Our Model6 7 8 9 10 11 12Model Accuracy (%)GradeThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014MCPS Model 65. Student DashboardThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 66. Data-Driven Strategies for LeadPoisoning PreventionChicago Department of Public HealthThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 67. Acting On Lead PoisoningReactive(Current)CHILDPOISONEDHAZARDIDENTIFIEDProactiveCHILDSTAYSHEALTHYThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014(Target)HAZARDREMOVED 68. Prediction Saves Time & MoneyNo Prediction Current Model Model ForecastBuildings: 197,157Time: 76 yearsMoney: $98 millionBuildings: 42,695Time: 16.4 yearsMoney: $21.3 millionThe Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014Buildings: 378Time: 2 monthsMoney: $189,000 69. Next Target: Prediction From Birth16141210864200 1 2 3 4 5 6 7Blood-Lead Level (-grams)Age of Child (years)Child 1Child 2Child 3Child 4Child 5Child 6Child 7Child 8The Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 70. Next Target: Prediction From Birth16141210864200 1 2 3 4 5 6 7Blood-Lead Level (-grams)Age of Child (years)Child 6Child 7Child 8The Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014 71. Project Takeaways1. Proactive, data-driven solutions to lead exposure2. Better data = better predictions = realistic targets3. Predictive models for BOTH homes and childrenThank You!The Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship 2014