introduction to big datathousands hours of annotated data. 16 ... analytics regional data hub...

Introduction to Big Data: Harnessing the Benefits of Data Powered Governance

Board of Directors Item 10 | January 24, 2020

Data Science:Connecting the dots in

emerging science, society & living

Rajesh K. GuptaDirector

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Data have always been with us.

What has changed?

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1. Ubiquity and scale of data that can be collected

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2.Development of sophisticated analytics tools

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2. Development of sophisticated analytics tools

Use of data in ways not previously imagined

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http://firemap.sdsc.edu

Santa Rosa fire, October 2017

http://wifire.ucsd.edu

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New algorithms for locally sensitive hashing, approximate computing

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Similar structures have similar effects

Toxicology tested by matching against a massive DB of molecular structures and safety data

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Machine predictions that can reduce crime or amount of jailing

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New algorithms for locally sensitive hashing, approximate computing

Similar structures have similar effects

Toxicology tested by matching against a massive DB of molecular structures and safety data

Machine predictions that can reduce crime or amount of jailing

Materials Society

Biology

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Data being used everywhere in daily lives

[Faster R-CNN: Ren, He, Girshick, Sun 2015]

Detection Segmentation

[Farabet et al., 2012]

Lots of training data:• Vision systems trained on millions of images• Speech systems training on tens of

thousands hours of annotated data.

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FB data

Psychographic data

Tweets

Browsing data

Voter registration

Public databases

. . . and more

Personality traits Race &

ethnicity

Political views

Religious views

Sexuality

Profession

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HDSI: A Convergence of Multiple Long‐term Initiatives Launched in March 2018

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188 Faculty Drawn from All Areas of University

EnvironmentTechnologyHealth

MicrobiomeScienceBig Data

Understandingand Protecting the Planet

HDSI

Enriching Human Life and Society

Exploring the Basis of Human Knowledge,

Learning and Creativity

Understanding Cultures and Addressing

Disparities in Society

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Questions and Answers

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Role of Data at SANDAGSpeaker: Ray Major

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SANDAG is creating an environment where economic and social benefits are recognized and achieved using empirical information.

BigData

Regional Plan

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SANDAG’s evolution as a data driven organization

INRIX Travel Time Data Incorporated in ABM

Work begins on Activity Based Model

1999 2005 2006 2009 2010 2012 2013 2016 2017 2018 2019 2020

Intermodal Transportation Management System Integrated

Corridor Management

Data Governance (2018)

Grant to Develop Solution for Analytics

Regional Data Hub

Intelligent Transportation System Architecture Regional

Arterials Management System

Streetlight Origin-Destination Data Acquired for ABM

ATRI Data Commercial Vehicles

AirSage Data for Military Base Trip Validation

Data used to drive Regional Plan

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Where (BIG) data comes from

External Data

• Navigation apps• Google• Weather • Uber/Lyft• Bird/Lime• Construction• Inrix/streetlights• Telematics

Internal Data

• Sensors• Signals• Cameras• Public transit• Traffic incidents• Crime• Detectors

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BenefitsFuture

Opportunities

Why big data is essential in making policy decisions for the region

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Analytic Continuum

What happened

Why did it happen

.

What is happening

now

What may happen

Based on History

What possibly will happen

Based in Real Time

.

What actions should be

Reporting

High

Low High

Complexity

Value of Information

Analysis

Monitoring

Forecasting

Prescriptive

PredictiveDRAFT

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Anonymization/privacy of the economic, demographic, and transportation data

Anonymization

Data Governance

PrivacySecurity

Smart Cities & Open Data

01/24/20

Andrell Bower, Chief Data Officer

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01/24/20 29

Background

Open data – an initiative launched in 2015

Engaged with residents and increased transparency

Data is a valuable asset that helps us meet strategic goals

PUBLIC FACING … … WHILE SHIFTING CULTURE

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Inform policy

We can decide the next category to add to Get it Done by conducting content analysis and text mining on reports submitted to the ”Other” category.

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01/24/20 31

Improve service

We used 911 call volumes andambulance time on task to

calculate the optimal number of ambulances for each of our

response zones.

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Evaluate programs

A tool that calculates parking meter utilization by block using daily transaction data will help program managers pilot changes and make timely adjustments.

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01/24/20 33

Thank you

Andrell Bower, [email protected] our Open Data PortalView our open-source data projects on Github

Central Ohio Case Studies inCivic Data Privacy & Governance

Christina Drummond, M.A. ISTPProgram Manager and Senior Analyst

Moritz College of Law, The Ohio State [email protected]

Presentation to SANDAGJanuary 24th, 202034

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Professional Networks

Efforts

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Regional EffortsDRAFT

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Regional Data Advisory Committee (RDAC)

https://www.morpc.org/committees/regional-data-advisory-committee/Contact Aaron Schill, Director, Data & Mapping. [email protected]

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MORPC Regional Data Agenda

https://www.morpc.org/wordpress/wp-content/uploads/2019/03/DATA-POLICY-AGENDA_FINAL_WEB.pdf

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Active Working Groups

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MORPC RDAC Data Policy Needs Survey & Toolkit WGSurveying and resourcing civic data governance needs

Data topics: e.g. cybersecurity, open data, privacy & ethics, contracting, sourcing and provisioning

Operations: Policy, procedures, staffing and training

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MORPC Data User Personas

Guiding data delivery & engagement

Personas span:

• Mid-sized City Planner

• Township Administrator

• Engaged Resident

• Elected Village Council Member

• Nonprofit Employee

• Consultancy Project Manager

• Civic Tech Enthusiast

https://www.morpc.org/tool-resource/data-user-personas/

$40 MILLION

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To empower our residents to live their best lives through responsive, innovative and safe mobility solutions.

VISION MISSIONTo demonstrate how an

intelligent transportation system and equitable access to transportation can have

positive impacts on every day challenges

faced by cities.

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USDOT PORTFOLIO

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TECHNICAL WORKING GROUP (TWG)

Data

• Identify use cases for data to solve community challenges & continue to make the city smarter

Technical

• Architecture & Design Recommendations

• Best Practices

• Tech Strategies

• Licensing / IP

Policy

• Data Management

• Data Privacy

• Policy Roadmap

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Data: Privacy, Management and Policies

SMART COLUMBUS DATA PRIVACY AND MANAGEMENT PLANS

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WHAT IS THE SMART COLUMBUS DMP?

Data Management Plan

• Governs data within Smart Columbus OS

• Addresses metadata management, data size, data acquisition, data access and data use.

https://smart.columbus.gov/programs/smart‐city‐demonstration

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DATA INVENTORY

• Description of Data• Data Type• Dataset• Source of the Data• Responsible Party• Collection Approach• Frequency• Needed for Performance

Management

• Period of Collection• Users of the Data• Value of the Data to the

Users• Does it Contain PII• Relevant Data Standards• Access Policies for the Data• Where is the data located?

Data Inventory for each dataset:

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SMART COLUMBUS DATA PRIVACY PLAN

• High-level plan to protect privacy and secure data

• Privacy controls• Security controls• De-identification• Ongoing governance

• A commitment to respect and to be a good steward of personal information

https://smart.columbus.gov/programs/smart‐city‐demonstration

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HOW WERE THEY DEVELOPED?

• Guiding Light Documents

• Iterative Drafts with Special Reviews

• Diverse Drafting Team

https://www.smartcolumbusos.com/share‐your‐data

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Types of Guiding Documents

Laws, including:• ORC: Personal Information Systems, Public Records• Federal: Privacy Act 1974• International: GDPR

NIST Standards/Guides• Security categorization standards, defining breach impacts

(FIPS 199)• Minimum security requirement specs, risk-based process

control selection (FIPS 200)• Information type to security category mapping (800-60v1)• Protection of PII confidentiality (800-122)• Security and privacy controls (800-53) *Control defining

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Guiding documents continued…

Policy Reports/Playbooks

• Open Data Privacy Playbook (Green et al/Berkman)

• De-identification protocol for Open Data (IAPP)

Policy from other cities

• Open Data Release Toolkit – Data SF/San Francisco

• Open Data Risk Assessment - Seattle

• Data Privacy Plan – Connected Vehicle Pilot / Tampa

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Iterative Plan Development Process

Guiding Documents

Technical

LegalPrivacy

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Drafting Dream Team

• Over two years• 38 people from across 22 organizations• Facilitated by Moritz Program on Data and Governance • Diverse perspectives:

• Public Sector IT• Lawyers• Information Privacy Professionals• Corporate Chief Privacy Officers• Unaffiliated national privacy experts• OSU students

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Transparency

User Notice/Consent

PII Use Limitations

Data Minimization

Secure Environment

Identity Shielding

Accountability

PRINCIPLES | SMART COLUMBUS DPP

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Data Privacy Plan Elements

Principles and

Legal Protections

for

Projects using PII

• Data Stewardship

• Applicable Law Compliance

• PII Definitions

• Administrative/Legal Safeguards

• Scope of plan related demonstration data

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Specified

Privacy Controls

1. Notice and Consent

2. Data minimization

3. PII Use/Sharing

4. Data retention

5. Access, correction, deletion

6. Transparency

7. Accountability

8. De-identification

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Specified

Privacy Controls

9. Data Curation, incl. Data Inventory spec.Benefit/Risk Analysis process

10.Privacy Testing

11.Data compartmentalization

12.IRB

13.Privacy and Security Board

14.Independent Evaluator Access

15.Contractor / 3rd party compliance

16.Privacy Impact Assessments

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Specified

Security Controls

1. Encryption

2. Physical controls

3. Access controls, with logs

4. Role/ID-based authorization

5. Penetration Testing

6. Secure software development

7. System monitoring

8. Data loss prevention

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Specified

Security Controls

9. Patching, Antivirus, Malware Checks

10.DPP training

11.Accountability and event review• Incident response plan spec.

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Privacy Impact

Assessment

• PIA question prompts• Data description, use, retention• Internal and external sharing/disclosure• Data collection notice, consent• Data access, redress, correction• Project security controls

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Additional Resources

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Civic Data Privacy Leaders Network

Contact: Kelsey Finch, Senior Counsel, Future of Privacy Forum. [email protected]

Future of Privacy Forum

• Resources and reports related to civic data privacy and governance

https://fpf.org/2018/10/31/nothing-to-hide-tools-for-talking-and-listening-about-data-privacy-for-integrated-data-systems/

https://fpf.org/2016/04/25/a-visual-guide-to-practical-data-de-identification/DRAFT

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MetroLab

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Next OS: Clearinghouse for Transportation DataSpeaker: Sanjiv Nanda

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What is Next OS

Who…

What… access transportation services that are cheaper, faster, and safer

Resident and Visitors, Goods and Freight

Transportation Operators & Transportation Service Providers

manage services or assets as efficiently as possible

Planners and Policymakers

make informed decisions to promote economic growth and quality of life

How…

A suite of integrated applications to browse, book, and pay for services

A suite of dashboards with advanced analytics and dynamic control tools

A platform with public and private data that better informs decisions

Next OS: Data Clearinghouse, Suite of Data Driven Tools and Applications

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Next OS In Operation

Flexible Fleets• Shared Mobility• Microtransit• Micromobility

Mobility Hubs• Trip Planning Kiosks• Curb Access Management

Transit Leap• Real Time Tracking• Dynamic Scheduling

Complete Corridors• Managed Lanes• Signal Priorities• Dynamic Pricing

Next OS: Data Clearinghouse, Suite of Data Driven Tools and Applications

• Operational EfficiencyCoordination, Scheduling and Pricing of Resources and Assets

• Transportation User EngagementTrip Planning and Payments at your fingertips

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