Understanding the Big Data Enterprise

Philip E. Bourne, PhD, FACMI Associate Director for Data Science

https://datascience.nih.gov/philip.bourne@nih.gov

My Bias

• University professor - 30+ years• Associate Vice Chancellor for Innovation – 2

years• Maintainer of public data resources (PDB etc.

– 15 years)• Open science advocate – 10+ years• Fed – 2 years and counting

None of what I am about to tell you negates what you have heard thus far today…

Much of what you have heard is prerequisite to my 30,000 foot view

My Definition of Big Data

• More than the 4+ “V’s”

• A signal of the coming digital economy

• An economy characterized by using data to gain a business advantage (and yes universities are a business)

What is the Worse that Can Happen?

DigitizationDeception

Disruption

Demonetization

Dematerialization

Democratization

Time

Volu

me,

Vel

ocity

, Var

iety

Digital camera invented byKodak but shelved

Megapixels & quality improve slowly; Kodak slow to react

Film market collapses;Kodak goes bankrupt

Phones replacecameras

Instagram,Flickr become thevalue proposition

Digital media becomes bona fide form of communication

[Steven Kotler]http://bigthink.com/think-tank/steven-kotlers-six-ds-of-exponential-entrepreneurship

Enterprises that are not born digital are at a disadvantage in this new economy…

Fortunately no university has yet to be born digital …

The “Google university” could change that

The Writing is on the Wall(Personal Experiences)

• The story of Meredith• Increasing number of undergraduates as first

authors on my papers• Talking head lectures• Growing frustration at lack of entrepreneurial

support• The Google bus

The Writing is on the Wall(Institutional)

• Changing access models • Changing funding models

– Less federal and state funds– More sponsored research– Increased tuition– More reliance on philanthropy

• Changing pedagogy– MOOCs, SPOCs, DOCCs, flips

• Changing student expectations– Expect to be taught in a different way

• Changing faculty expectations– Expect more from the institution

• Changing staff expectations– Better recognition

• Changing employer expectations

http://collegeparents.org/2011/01/26/when-your-college-student-unhappy/

Yet demand for a quality higher education has never been higher

Leads to the Notion of the University as a Digital Enterprise

• The university is defined by its digital assets:– On-line course materials– All of the research life cycle on-line: grants, data,

computational methods, results, conclusions, publications

– Faculty, staff and student profiles on-line– All administrative data on-line e.g. grants, policies

and procedures, disclosures, contracts, patents, agreements, payroll, academic files

The Most Successful Universities of the Future Will be Those That Can Best Leverage Their Digital Assets – How?

“Life Wasn’t Meant to be Easy”

Malcolm FraserFormer Prime Minister of Australia

How? - Break Down the Silos

Research

Basic Clinical

Education Administration

How? - An Appropriate Organizational Structure

Chancellor

CIO /CDO

ResearchServices

EducationServices

AdminServices

MedicalServices

Library

Use Cases from the University as a Digital Enterprise

Research Data

• Prof x drags and drops her research data to the institutional dropbox. She is asked for a small amount of metadata describing the dataset. Part of that request gives permission for the data to be indexed and the index analyzed by the University. That analysis reveals that two other researchers have worked on the same gene in the past two months and they are all alerted as to their common interest and begin collaborating.

.

Faculty Productivity

• From a single profile a faculty member can, at the push of a button, generate a world-facing current web presence, provide biosketches to the major funding agencies and submit their academic file for review saving countless hours of reformatting which now goes into productive research.

The Education – Research Interface

• The UCSD on-line drug commercialization course which previously had 40 local students now has 12,000 several of whom apply to Dr. Bourne’s lab as PhD students based on the material he presented. The course also highlights UCSD’s leadership role and by navigating the on-line curriculum several students apply to UCSD as undergraduates. One high school student applies to Dr. Bourne’s lab as a summer intern.

The Research-Administration Interface

• Researcher x receives a new grant, researchers y and z are notified since it is very close to areas in which they work and points of collaboration may be possible.

• Researcher x needs to have an assay performed and can immediately locate who on campus and off-campus can perform the work and at what cost.

• Experts on and off campus can immediately be identified for the review of a potential patent filing based on a researcher’s technology.

Talk is cheap – What is NIH doing to address a similar situation?

NIH By Comparison

• 27 silos• Clinical and basic research• Intramural + extramural• Administration• Education role different

https://en.wikipedia.org/wiki/Victory_Soya_Mills_Silos

Established a Commons• Supports a digital biomedical ecosystem• Treats products of research – data, software, methods, papers

etc. as digital research objects • Digital research objects exist in a shared virtual space• Digital objects need to conform to FAIR principles:

– Findable– Accessible (and usable)– Interoperable – Reusable

Commons Framework Pilots (CFPs)• Exploring feasibility of the Commons framework• Facilitating connectivity, interoperability and

access to digital objects • Providing digital research objects to populate the

Commons• Enable biomedical science to happen more easily

and robustly

BD2K Centers, MODS and HMP

Compute Platform: Cloud or HPC

Services: APIs, Containers, Indexing,

Software: Services & Tools

scientific analysis tools/workflows

Data“Reference” Data Sets

User defined data

Digital Object Com

pliance

App store/User Interface

Mapping Commons PILOTS to the Commons Framework

PaaS

SaaS

BD2K IndexingBioCADDIE, Other, schema.org

IaaS

[Vivien Bonazzi]

Compute Platform: Cloud or HPC

Services: APIs, Containers, Indexing,

Software: Services & Tools

scientific analysis tools/workflows

Data“Reference” Data Sets

User defined data

Digital Object Com

pliance

App store/User Interface

Mapping Commons PILOTS to the Commons Framework

PaaS

SaaS

Cloud credits model (CCM)

IaaS

Commons Credits Model

The Commons(infrastructure)

Cloud ProviderA

Cloud ProviderB

Cloud ProviderC

Provides credits Enables Search

Uses credits inthe Commons

IndexesOption:Direct Funding

NIH

Investigator

bioCADDIE

[George Komatsoulis]

Culture Change

http://mitchjackson.com/white-elephants/

How to Change the Culture?

• Intramural and extramural training programs• Fostering open science

– e.g. policies, challenges• Fostering changes to the research life cycle

– e.g. preprints, data citation, open final reports• Strategic planning with buy-in from major

stakeholders• Use cases as exemplars

What is the desired endpoint?

Uber!

Some Thoughts as to Why I am Not Crazy

• A platform to exchange goods – researchers produce and consume reagents, data, knowledge etc.

• A platform built on trust – trust is a key part of the academic enterprise

• A platform provides a sustainable business model

Sangeet Paul Choudaryhttp://www.wired.com/insights/2013/10/why-business-models-fail-pipes-vs-platforms/

Summary

It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of Light, it was the season of Darkness, it was the spring of hope, it was

the winter of despair…

Charles Dickens