improving the rider's transit experience with big data...big data coming of age, the standards...

Improving the Rider's Transit Experience with Big Data

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The “Hype Cycle” tells us that we must consider applying Big Data to improve our ridership of which, none of us appears to have the slightest idea as to what it is or what to do with

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What is Big Data?

Big Data refers to the inability of traditional data architectures to efficiently handle the new datasets. Characteristics of Big Data that force new architectures according to NIST are:

Volume (i.e., the size of the dataset);

Variety (i.e., data from multiple repositories, domains, or types);

Velocity (i.e., rate of flow); and

Variability (i.e., the change in other characteristics)

All of the above define the concept of Big Data but Variety is a super component.

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NIST: The US National Institute of Standards and Technology

Big Data Coming of Age

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2016 was considered a landmark year for Big Data:, moreand more organizations are: Storing

Processing Analyzing Extracting value


The year 2017 is already seeing systems who are supportinglarge volumes of structured and unstructured data that will only continue to expand into 2018…

The market place is already demanding platforms that helporganizations to: Manage Govern (How and when data is used, privacy issues) Securing of Big Data

Big Data Coming of Age, the Standards

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Big Data is more than just being talked about:

Standards committees nationally and internationally are addressing

Big Data to establish definitions, formats, etc.

NIST developed in late 2015:Big Data Interoperability, Taxonomies, Architectural Framework: Special Publication 1500-1,2,6 others…

ISO/IEC JTC 1/WG9, Information technology-2015/2016: TR 20547-5

Big Data Analytics – Integration of results Big Data Engineering - Storage and Data Manipulation Big Data Models – logical and computational Big Data Paradigm – distribution of data to achieve scalability, etc.

INCITS/ANSI: Established a national working group in 2015


Initial Benefits derived from Big Data

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Did you know that Big Data is already being used to better

understand and manage future transit investment decisions, such as accumulating the following Big Data results:

As of 2016; 52% of all Americans spend an hour or less per day commuting?

Or that large city public transit riders such as in Los Angeles travel over 7.5 miles/trip

Or that large city riders may spend more than 2-hours a day on public-transport

Or that non-frequent public transit riders are often concerned with usingpublic transit because of first and last mile connections

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Where are the transit oriented populations within a region?

Where are the employment, event, retail malls centers located?

When, Where, Why and Now Often do people travel and specifically onpublic transit?

What modes of travel are they using, and are there better options?

Where are the gaps in public transit service?

What technology do riders have and prefer to use?

What methods of payment are used and or preferred?

What is the amount of time expended per trip?

What riders types travel as individual or in groups?

What does social media say about our agency?

Transit rail and bus , etc. on-time performance data.


A Sampling of Big Data:

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So why Consider Big Data?

The rider’s transit experience is ever more multimodal and is

expecting a seamless cost effective, connective and convenient trip planning

Transit agencies are faced with higher ridership expectations and a growing private competitive transport environment

Transit agencies are now expected to understand the riders total landscape? Having the data derived from the big picture, is a good start:

Rail BusTransit

ParkingTolling

Bike

ShareUber or

Lyft

City/Private

ParkingStreet

Car

Commuter

RailRetail

PartnersEntertainment

Venue

Pubic Transport

Private Transport

Airlines and

Amtrak


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How might the Transit Industry make use of Big Data?

Implementing Big Data may be challenging but is also realistic

and may now actually be a necessity for public transit operators

The proliferation of Smart phones and recent standardization achievements has changed everything

Transit agencies must consider applications that bring personalization to the rider’s trip planning experience, players in the industry must understand how to achieve this?

To ensure a useful Big Data implementation of a personalized transit

rider’s experience, consider the following:


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Standardized and secure open standards protocols for lower-level data

and security interoperability such as, OSPT-CIPURSE or other transactional protocols utilizing: ISO/IEC, NIST and ANSI/ INCITSstandards

Become familiar with what Big Data represents and what it can provide inunderstand agency long-term transit planning needs by leveraging Big Data

Consider system integrators and software processing providers that can alsointegrate Big Data into the total transit back office experience

Let Big Data contribute to the personalized rider experience on smart mediaand especially transit provided or directed mobile applications giving the rider a complete transit experience at his/her finger tips.

How might the Transit Industry make use of Big Data?, Continued…


Walt Bonneau Jr.

ALINC Consulting

Email: [email protected]

www.ALINCconsulting.COM

Improving the Rider's Transit Experience with Big Data

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Our Contact Information:

Al Chan

ALINC Consulting


www.ALINCconsulting.COM

Greg Coogan

Infineon Technologies


www.Infineon.com


Thank You!

improving the rider's transit experience with big data...big data coming of age, the standards...

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