TODAY WE HAVE PRESENTATIONS.
DR. SHERRY WILL BE ON ZOOM SO
I'LL START BY INTRODUCING DR.
SUSAN GREGURICK, ODSS LEADS
IMPLEMENTATION OF STRATEGIC PLAN
FOR DATA SCIENCE, THROUGH
SCIENTIFIC, TECHNICAL,
OPERATIONAL COLLABORATION WITH
NIH INSTITUTES, CENTERS,
OFFICES.
DR. GREGURICK WAS PREVIOUSLY
DIVISION DIRECT YOKING FOR
BIOPHYSICS, BIOMEDICAL
TECHNOLOGY, COMPUTATIONAL
BIOSCIENCE NATIONAL INSTITUTE OF
GENERAL MEDICAL SCIENCES,
WELCOME, DR. GREGURICK.
>> IT'S GOOD?
>> WE CAN HEAR YOU.
>> IT SAYS IT'S ON.
>> I HEAR YOU FINE,AN.
>> WE CAN HEAR YOU NOW.
>> IF YOU CAN'T HEAR ME LET ME
KNOW.
IT'S SUCH A DELIGHT TO BE HERE
TODAY TO TELL BUT THE WORK I'M
DOING WITH DR. SEAN MOONEY AND
DR. STEVE SHERRY, IT'S A REALLY
PLEASURE TO WORK ACROSS NIH,
ESPECIALLY WITH LUMINARIES LIKE
SEAN AND STEVE WHO REALLY THINK
ABOUT DATA, DATA SCIENCE,
ARTIFICIAL INTELLIGENCE, I.T.
INFRASTRUCTURE.
I'M FROM DPCPSI, DATA SCIENCE,
DPCPSI AS YOU KNOW IS A
COORDINATING CATALYTIC
SCIENTIFIC ACTIVITY BUT THERE'S
16 OFFICES IN DPCPSI.
I'M JUST ONE OF THEM.
MY ROLE IS TO CATALYZE AND
COORDINATE ACTIVITIES ACROSS THE
INSTITUTES, CENTERS, OFFICES,
AND DATA SCIENCE-RELATED
ACTIVITIES, I'LL TELL YOU ABOUT
THOSE BUT I CAN'T TELL YOU ABOUT
EVERYTHING SIMPLY BECAUSE THERE
WOULDN'T BE ENOUGH TIME.
I'M GOING TO HIGHLIGHT WORK WITH
SEAN AND STEVE IN THE LIBRARY
COMMUNITIES.
WE COORDINATE, CATALYZE, WE'RE
LOOKING TOWARDS A MODERNIZED
BIOMEDICAL SYSTEM, FUTURE PLANS
ARE EXCITING BECAUSE THAT'S THE
ON STEROIDS WHAT WE'VE BEEN
DOING.
EXCITED TO TELL YOU ABOUT THE
WAY IN WHICH WE'RE ENHANCING NIH
DATA SCIENCE WORK FORCE, I CAN'T
TELL YOU ABOUT TRAINING AND
EXTRAMURAL, THAT WOULD BE
ANOTHER TALK.
WE BUILD STRATEGIC PLANS.
YOU WON'T HEAR ABOUT A.I. AHEAD
BUT IT YOU'RE INTERESTED, I'M
HAPPY TO ANSWER QUESTIONS.
WE'RE MOTIVATED BY THE STRATEGIC
PLAN FOR DATA SIGNS.
RFI WENT OUT, CAME BACK, WE'RE
ANALYZING THE RESPONSES.
IT WAS NUMEROUS AND MEATY.
WE'LL HAVE A PUBLIC SYNOPSIS IN
THE FINALIZED PLANS, OUT BY THE
END OF THE YEAR WITH OTHER
STRATEGIC PLANS.
A NUMBER OF GOALS, THE NUMBER
ONE GOAL WE HEARD WE HAVE TO
SUPPORT DATA MANAGEMENT AND
SHARING POLICY, LOUD AND CLEAR,
THE LIBRARY HAS A CRITICAL ROLE
HERE, I'M EXCITED TO EXPLORE
THAT WITH YOU.
SECOND, ENHANCING HUMAN-DERIVED
RESEARCH WITH DR. BERTAGNOLLI,
WORKING WITH SEAN AND MY
COLLEAGUES AT NCATS, AND NIA.
GOAL 3 IS ABOUT A.I. AND
COMPUTATION.
GOAL 4 IS SOMETHING I'LL TALK
BRIEFLY ABOUT BECAUSE YOU IMPACT
SIGNIFICANTLY OUR ABILITY TO
SUPPORT A FEDERATED DATA
INFRASTRUCTURE.
WE WANT TO INVEST IN PEOPLE
BECAUSE THEY ARE THE FUTURE OF
OUR WORKFORCE.
THEY ARE GOING TO TAKE OVER WHEN
I RETIRE, WHEN ALL OF US SEEK
MORE FUN THINGS.
THE NUMBER ONE THING I HEARD AND
THAT YOU HEARD, IT'S ON YOUR
BIND, HOW DO WE EXPAND DATA
CULTURE, DATA SHARING, THAT IS
SUPPORTED BY THE MANAGEMENT AND
SHARING POLICY, THIS IS A REALLY
IMPACTFUL POLICY, IT'S GOING TO
WRITE A DATA MANAGEMENT SHARING
PLAN AT THE TIME OF SUBMISSION
OF GRANTS OR CONTRACT OR
INTRAMURAL RESEARCH PROJECT AND
THEY ARE GOING TO TELL US HOW
THEY ARE GOING TO SHARE DATA.
THIS IS SOMETHING I THINK NLM
HAS DEEP, DEEP EXPERIENCE IN AND
CAN REALLY ADD VALUE IN CURATION
AND THERE'S A LOT OF MAPPING.
I DO A LOT OF MAPPING TO DATA
STANDARDS.
IT'S REALLY IMPORTANT AND
CRITICAL, VALUE ADDED FROM
ANALYTICS AND ANALYTICS
PLATFORMS, FINALLY IMPACT.
HERE IS WHERE IT'S HARD, A HARD
CONVERSATION, BECAUSE WE'RE USED
TO COUNTING CITATIONS BUT WHAT
DO DO YOU IN DATA SHARING?
HOW DO YOU SHOW IMPACT OF
SCIENCE, OF SOMETHING THAT IS
FAR DOWNSTREAM?
THESE ARE THINGS I'M EXCITED
TOWARDS, STEVE AND SEAN ARE.
THERE'S A CONCEPT WE'RE DOING SO
I'M GOING WALK THROUGH A FEW AND
I'LL HIGHLIGHT SOME THINGS I
THINK ARE REALLY IMPACTFUL FOR
NLM, AND I'M NOT GOING TO TALK
TOO BEFORE DATA CURATION NETWORK
BUT I'M GOING TO TELL YOU WE
HAVE PARTNERED TO INSTANTIATE
TRAINING AND EXPERTISE IN THE
LIBRARY COMMUNITY FOR DATA
CRAIGS BECAUSE THE FIRST THING
INVESTIGATORS SHOULD DO IS GO TO
THEIR LIBRARIAN AND TALK ABOUT
DATA SHARING BECAUSE THAT'S
WHERE THE RUBBER MEETS THE ROAD.
THOSE PEOPLE KNOW WHAT DATA
SHARING IS, THEY KNOW ABOUT
REPOSITORIES, THEY KNOW ABOUT
CITATIONS, THEY KNOW HOW TO
CONSTRUCT RETURN ON INVESTMENT.
IF YOU'RE NOT TALK TALKING TO R
LIBRARIAN YOU'RE MISSING OUT.
WE ARE FORMING A FORMAL
PARTNERSHIP WITH ELIXIRE LIKE
WITH RDA, WE'RE FORMING ANOTHER
PARTNERSHIP WITH ELIXIR, IT WILL
LOOK LIKE SCIENCE AND TRAINING
ACROSS OUR TWO.
I WANT TO TELL YOU ABOUT THERE'S
A LOT OF HELP THAT'S NEEDED IN
THE RESEARCH COMMUNITY AND IN
OUR COMMUNITY AT NIH.
OUR PROGRAM OFFICERS ARE GETTING
DATA MANAGEMENT SHARING PLANS
AND NEED SOME GUIDANCE.
THEY DON'T NEED US TO TELL THEM
THE PLAN IS OKAY OR NOT, THAT'S
THEIR JOB.
THEY NEED TO UNDERSTAND WHAT
DOES A GOOD PLAN LOOK LIKE, WHAT
SHOULD IT CONSIST OF.
THIS IS THE DATA SCIENCE CENTER
OF EXCELLENCE.
IT PROVIDES GUIDANCE AND
RESOURCES TOKER OUR NIH
COMMUNITY PROGRAM STAFF, TO
UNDERSTAND WHAT IS A DATA
MANAGEMENT SHARING PLAN, WHAT
DOES IT LOOK LIKE IN DIFFERENT
COMMUNITIES, WHAT IS FAIR, HOW
DOES THAT GET IMPLEMENTED, WE'LL
MAKE EVERYTHING PUBLIC.
WE'RE PROVIDING TRAINING.
FOLKS FROM THE EXTRAMURAL
COMMUNITY WITH LOOK AT RESOURCES
BUT IT'S REALLY FOR NIH STAFF.
CENTER OF EXCELLENCE IS A
PARTNERSHIP WITH THE OFFICE OF
EXTRAMURAL RESEARCH, AND WITH
MANY OF OUR I.C.s.
SO THAT'S AN FYI.
WE'VE GOT OUR EYES ON THIS BUT
KNOW THIS IS A HARD PROBLEM.
ACROSS NIH, WE'RE SUPPORTING
SIGNIFICANT BIOMEDICAL DATA
ASSETS THROUGH TWO FUNDING
ANNOUNCEMENTS.
CAN YOU SEE THE FIST, PAR-20.
OH, THOSE ARE OLD.
SHOOT, NOTE TO SELF, FIX THE
SLIDES.
THESE ARE FUNDING ANNOUNCED, NOT
AS RESOURCE, THOSE ARE THE
GUIDES FOR REVIEWING, LOOKING AT
DOES IT FILL A SCIENTIFIC GAP IN
THE COMMUNITY, IS IT AN
IMPORTANT NEED?
IS THERE GOOD DATA MANAGEMENT
PRACTICES INSTANTIATED IN THIS
RESOURCE?
DOES IT CONTRIBUTE TO THE
COMMUNITIES, IS IT WORKING WITH
THE JOURNALS OF THAT COMMUNITY,
WITH THE RESEARCHERS, DOES IT
HAVE A SCIENTIFIC ADVISORY
BOARD?
FINALLY DOES IT UNDERSTAND DATA
LIFE CYCLE AND PRESERVATION AND
MANAGEMENT.
THIS IS WHAT THE LIBRARY KNOWS
BEST.
I LOVE TO WORK WITH I.C.s AND
NLM ON THIS PROGRAM.
YOU'LL SEE SOME OF THE RESOURCES
WE'RE FUNDING, MY OFFICE
CO-FUNDS, SO THAT'S HOW IT WORKS
IN MY GROUP.
SOME THESE RESOURCES HAVE RED
BOXES, THERE'S A PARTICULAR
REASON, SPECIAL FLAGS.
I'M GOING TO TELL BUT THE GLOBAL
BIODATA COALITION AND CORE
GLOBAL BIODATA RESOURCE, THEY
HAVE GONE THROUGH A SECOND PEER
REVIEW.
IT'S NOT MONETARY.
IT'S A NOTE OF NOTORIETY THAT
THESE ARE CORE RESOURCES THAT
THE COMMUNITY HAS SAID ARE
VALUABLE AND, YOU KNOW, GETTING
RESOURCES IS SO HARD.
OFTEN RESEARCHERS DON'T CITE
DATA OR RESOURCES, WE STRUGGLE
WITH THIS EVERY DAY.
I TALK WITH STEVE A LOT.
HOW IS THE DATA IN REPOSITORY
AND FOR REPOSITORIES TO SHOW
VALUE, THIS IS ONE OF MANY WAYS.
CHRISTY IS HERE.
SHOUT OUT TO CHRISTY.
GENERAL REPOSITORY ECOSYSTEM,
PUT YOUR DATA IN AND GO,
COMMUNITY-DRIVEN REPOSITORIES
ARE IMPORTANT FOR OUR SCIENTIFIC
COMMUNITIES.
WE NEED THE SUPPORT OF
REPOSITORY, FOR RESEARCHERS AND
THERE ARE MANY WHO JUST DON'T
HAVE THE COMMUNITY, THE
RESOURCES AREN'T THERE THEY NEED
TO SHARE TO SHARE DATA IN A WAY
THAT'S EFFECTIVE.
OUR GOAL IS TO MAKE DATA SHARING
MORE EFFECTIVE ABE CROSS THE
GENERALIST REPOSITORY BY
INSTANTIATING THE CONCEPT OF
CO-OPETITION, THINGS WE WITH
COLLABORATE ON TOGETHER.
FOR EXAMPLE COLLABORATE ON WAYS
TO INSTANTIATE CONSISTENT
CAPABILITIES, METADATA, SEARCH
AND DISCOVERY, CAN WE GET DATA
ACCESS, DISCOVERY ACROSS THE
REPOSITORIES.
CAN WE OUTREACH AND TRAIN OUR
RESEARCHERS COLLECTIVELY?
WHY DON'T WE WORK TOGETHER ON
TRAINING?
CAN WE ENCOURAGE RESEARCH WITHIN
THE RESEARCH COMMUNITY THAT USES
THIS DATA, IT'S VALUABLE, WE
WANT TO SEE PEOPLE REUSE DATA IN
IMPORTANT WAYS.
SO THIS IS THE WORK IN GRAY, YOU
CAN SEE THE COLLEAGUES AT THE
BOTTOM, IT'S BEEN A PLEASURE
WORKING ON THIS FOR THE PAST 2
1/2 YEARS.
I REALLY LOOK FORWARD TO
CONTINUING THE PROGRAM AND THANK
CHRISTY FOR HER LEADERSHIP.
WHAT IS THIS?
I KNOW IT WHEN I SEE IT.
STEVE AND OTHERS DEVELOPED A
STRONG CONCEPT THESE SIGNIFICANT
BIOMEDICAL DATA ASSETS ARE
DYNAMIC, REPOSITORIES OR
KNOWLEDGE BASES, MAY BE STATIC.
THEY OFTEN HAVE DATA
COLLECTIONS, MANY TIMES DATA
HARMONIZE, NOT ALWAYS, BUT MANY
TIMES.
THEY PROVIDE STRATEGIC UTILITY
FOR NIH AND OUR MISSION, ACROSS
NIH, LIKE UNIPRO, A MISSION THAT
SHARES MANY I.C.s, AND THEY
ARE REALLY IMPORTANT FOR OUR
UNDERSTANDING OF LIVING SYSTEMS.
WE CAME UP WITH SOME CONCEPTS WE
WANT TO EXPLORE FURTHER, CAN WE
MAINTAIN SUSTAINABILITY PLANS
FOR RESOURCES?
WE CAN PROMISE OVERFUNDING BUT
CAN WE THINK ABOUT WHAT
SUSTAINABILITY MIGHT LOOK LIKE
FOR BIOMEDICAL DATA ASSETS?
ARE THERE OPERATIONAL BEST
PRACTICES THAT CAN BE SHARED?
ARE THERE STANDARDS AND
APPROACHES FOR COLLECTING
METRICS, IT SEEMS EASY, BUT THAT
DOESN'T HAPPEN IN WAYS WE WANT
IT TO SO WE WANT TO THINK ABOUT
METRICS FOR SIGNIFICANT
BIOMEDICAL DATA ASSETS.
WHAT ABOUT INFRASTRUCTURE?
YOU'LL HEAR MORE ABOUT
INFRASTRUCTURE FROM DR. SEAN
MOONEY.
WHAT ABOUT STANDARDS?
OMOP IS A BIG STANDARD FOR A LOT
OF CLINICAL RESEARCH BUT THERE
ARE OTHER STANDARDS.
HOW CAN WE PUSH AND HELP SUPPORT
STANDARDS, COMMON DATA ELEMENTS.
FINALLY ARE THERE WAYS TO THINK
ABOUT OVERSIGHT AND
RESPONSIBILITY FOR
SUSTAINABILITY IN MANAGEMENT,
STRUCTURES THAT HELP ACQUIRE
YOUR FEEDBACK SO WE CAN MAKE
SURE THESE RESOURCES ARE MEETING
YOUR NEEDS.
THIS IS -- THE LIBRARY IS THE
RIGHT PLACE.
YOU'RE EXPERTS HERE.
AND SO I'M THRILLED TO WORK WITH
STEVE AND SEAN ON THESE
ACTIVITIES ACROSS NIH.
WE'RE NOT THE ONLY ONES WORKING
ON THIS.
ELIXIR, YOU KNOW THE CORE DATA
RESOURCES IN ELIXIR.
WE'VE GRAFTED SOME OF THEIR
INDICATORS SUCH AS COMMUNITY
FOCUS, QUALITY OF SERVICE,
FUNDING STRUCK.
THERE'S A DUAL ACTIVITY, MY
COLLEAGUE DR. LAURA BEVIK CAME
UP WITH THIS FOR DOE RESOURCES,
LIKE NIH THEY HAVE CORE
RESOURCES.
FINALLY I'M CALLING OUT
HIGHLIGHTS, THE COALITION,
RESOURCES GO THROUGH THAT AND
ARE DESIGNATED, THOSE ARE THE
RED BOXES AROUND THE ONES I
SHOWED YOU.
I'M SO PLEASED WE CAN WORK WITH
DATA SIGNS, INSTANTIATE ABILITY
FOR OUR DATA RESOURCES THAT ANY
I.C. CAN ACCESS FREE OF CHARGE.
ANY I.C., ANY FUNDED DATABASE,
KNOWLEDGE BASE, CAN HAVE THEIR
RESOURCES WITH PERSISTENT
IDENTIFIERS.
THIS IS FOR EXTRAMURAL RESOURCE
RESOURCES
TO GET CITED.
PLEASE LINK YOUR DATA TO YOUR
ORCID I.D
YOU'LL GET CREDIT ON DATA
SHARING AND WE'LL SHOW A RETURN
ON INVESTMENT.
THERE'S MANY WAYS TO INCENTIVIZE
DATA SHARING.
WE PARTNER WITH CORE DATA
RESOURCE COMMUNITY, THEY HAVE A
LOT OF RESEARCH, WE THOUGHT IT
WOULD BE NICE TO PARTNER AND
HAVE RESEARCHERS TELL US HOW
THEY WOULD LIKE TO WE USE NLM
DATA, OTHER DATA, AND THEN THEY
CAN GET MONEY FOR ACTUALLY
ACCOMPLISHING THOSE GOALS.
SO I'M JUST PLEASED TO BE ABLE
TO CONTINUE THIS PARTNERSHIP.
WE HAVE COOL THINGS.
LAST YEAR THE GUYS WHO WON THE
TOP PRIZE, KIND OF A LOT OF
MONEY, I THINK IT'S LIKE
$100,000, WERE GRAD STUDENTS AND
POSTDOCS.
IT WAS SO COOL.
OKAY, THERE'S WAYS WE CAN THINK
ABOUT BETTER ACCESS, LESS COST
AND FORMATTING, MY COLLEAGUE THE
CHAIR INFORMATICS WORK
FORMATTING FOR FDA AND CMS,
FORMATTING DATA FOR NCC, THAT'S
LIKE PEOPLE.
THAT'S PEOPLE.
WE CAN DO BETTER, WE CAN ALSO
INCREASE THE QUALITY OF DATA.
I TALKED WITH JIM ABOUT THIS.
LET ME TELL YOU ONE OF THE
THINGS THAT I'M PLEASED AND I'M
GOING TO TELL YOU THIS IS REALLY
NLM.
THERE'S A RESOURCE AND I KNOW
THERE ARE CHALLENGES WITH
dbGAP, THERE'S A RESOURCE TO
STREAMLINE ACCESS CONTROLLED
ACCESS OF DATA GENOMICS AND
BEYOND.
THIS IS PART OF THE WORK I
STARTED WITH PATTI BRENNAN WHERE
WE WANTED TO THINK HOW CAN WE
FACILITATE EFFECTIVE BOTH IN
COST AND TIME ACCESS TO DATA IN
A WAY ACROSS OUR I.C.s, WAYS
TO INCREASE DATA ACCESS,
DECREASE TIME OF DATA ACCESS TO
REVIEW THESE APPLICATIONS FOR
dbGAP BECAUSE WE AUTOMATED,
REDUCED TIME FROM TWO DAYS TO A
COUPLE HOURS.
AS LONG AS YOU DON'T HAVE A
SPECIAL PAGE THERE ARE NORMAL
RESEARCHERS, COMING IN FOR DATA
THAT'S EASY TO AUTOMATE, WE CAN
GET YOU THAT DATA REALLY QUICK.
FOR ME, THAT'S A HUGE
ACCOMPLISHMENT.
WE ALSO WANT TO INCREASE
FIRST-TIME LOG-IN TO MAKE IT
EASY, AND LOOK AT THINGS LIKE
SEARCH AND DISCOVERY.
YOU DON'T HAVE TO PUT YOUR DATA
IN dbGAP.
ALSO WORKING WITH NLM
REPOSITORY, CDs ARE IMPORTANT.
IT'S A QUESTION, CLINICAL
QUESTION, CONTENT IN A
STANDARDIZED WAY TO FACILITATE
DATA USE.
WE'VE BEEN WORKING WITH NLM TO
AUTOMATE AND IMPROVE USER
EXPERIENCE OF THE CDE
REPOSITORY, AND INCLUDING
INCREASING THE PROCESS OF THE
CDE REPOSITORY, REDUCING MANUAL
TIME NEEDED TO PROCESS CDE
SUBMISSION SO YOU CAN SEE
AUTOMATED, LOOKS AT MAPPING, YOU
HEARD FROM RICHARD MAYBE A
LITTLE BIT ABOUT SOME OF THIS
TOO, SO VERY COOL.
WE'VE ALSO STARTED ORIGINALLY
WITH NLM AND DESIGNED WAYS IN
WHICH WE CAN BE TRAINING ON
RESOURCES AT INSTITUTIONS THAT
ARE NOT FHIR SAVVY, IDeA
STATES, A LOT OF TRAINING
BECAUSE FHIR, WHICH IS AN
EXCHANGE FORMAT FOR HEALTH CARE
I.T., IS SUPER GREAT FOR
RESEARCH.
WE CAN FORMAT THE DATA IN FHIR
AND FACILITATE DISCOVERY
EXCHANGE ACROSS, WE'RE DOING A
LOT OF THAT NOW WITH A NUMBER OF
OUR COLLEAGUES IN THE I.C. SO
DATA PLATFORM, DATA CATALYST,
FRAMEWORK.
I'M GOING TO RUN OVER ON TIME.
THAT BRINGS ME TO FEDERATION.
WE'VE HAD THIS PROJECT GOING IN
THE BACKGROUND FOR A WHILE NOW.
WHICH IS A FEDERATED WAY FOR BIG
DATA PLATFORMS LIKE dbGAP
EXCHANGE INFORMATION EASILY.
IN THE OLD DAYS HAD YOU TO LOG
IN, DO SEPARATE THINGS THERE.
IT WAS HARD FOR YOU TO CRUNCH
THE DATA ACROSS THOSE PLATFORMS.
I THINK IT WAS PRETTY MUCH
IMPOSSIBLE.
NOW WE CREATED THROUGH CIT,
ACCESS MANAGEMENT SYSTEM
RESEARCHERS CAN LOG IN ONCE AND
GET ACCESS ACROSS THE PLATFORMS,
44 OF THEM NOW USE THE SYSTEM.
WE CAN FIND AND DISCOVER DATA
AND PULL DATA INTO ONE PLATFORM,
DO THE ANALYSIS, THAT'S WHAT
THEY HAVE BEEN DOING.
THEY HAVE BEEN -- THIS IS A
GREAT EXAMPLE USING SRA, PULL
DATA FROM SRA, COLD STORAGE TO
HOT STORAGE, WITH POOLS NCPI
CREATED TO CONCERT SRA METADATA
INTO A SEARCH FORMAT THROUGH
TOOLS NCPI HAS DONE AND PULL
LINKS INTO ANY PLATFORM, IT HAS
TO BE DONE IN THE CLOUD NOW, AND
DO THEIR ANALYSIS.
THIS IS WHAT RESEARCHERS IN THE
DISEASE NETWORK HAVE BEEN
WORKING ON AND HIGHLIGHT, THIS
IS COMING UP MAYBE NEXT WEEK.
THEY WANT TO MOVE TO THE CLOUD,
WE'LL WORK WITH CIT TO GET LIFTS
DONE.
SO GLAD WE CAN SUPPORT NLM.
WE'LL TALK ABOUT CLOUD BUCKS,
WE'RE THE INSTITUTE RUNNING FOR
RESEARCHERS TO GET ACCESS TO
LARGE COMPUTES TO DO A.I. AND WE
HAVE A NUMBER OF FOLKS WHO HAVE
BEEN WORKING WITH US ON THAT.
ONE OF THE COOL THINGS IS THAT
THE CLOUD LAB IS PART OF THIS,
THESE ARE ALL THE RESOURCES WE
SUPPORTING FOR THE NATIONAL A.I.
RESEARCH RESOURCE, AN
INTEGRATION AND COLLABORATION
ACROSS FEDERAL AGENCIES TO
PROVIDE RESOURCES IN A.I. FOR
ANY SCIENCE, INCLUDING
BIOMEDICAL SCIENCE.
IF YOU'RE INTERESTED IN
ACCESSING DATA, WE'RE THE GUYS
DOING IT FOR THE GOVERNMENT.
NAIRR AND WE SUPPORT DATA
SCHOLARS.
WE'VE HAD A NUMBER OF THEM.
WE'RE HAPPY TO EMBED EXPERTS IN
COMPUTER SCIENCE, A.I., DATA
SCIENCE IN THE I.C.s.
A NUMBER OF THESE BECOME FEDERAL
EMPLOYEES, SO YOU CAN SEE WE'RE
ENRICHING OUR COMMUNITY OF
SCIENTISTS AT NIH THROUGH THIS
PROGRAM, AND WE HAVE PATHWAYS
FOR YOUNGER PEOPLE WHO ARE
POSTBACS OR MASTER'S GRADUATES
WHO WOULD LIKE TO COME IN, NOT
AT THE Ph.D. LEVEL BUT GOOD AT
INFORMATION SCIENCE, THE ONLY
THING TO NOTE THEY HAVE TO HAVE
A PATHWAY, THEY COME, LEAVE, MAY
STAY.
THESE GUYS ARE EXPECTED TO HAVE
PATHWAY.
THANK YOU SO MUCH.
I APOLOGIZE IF I WENT A LITTLE
FAST, A LITTLE OVER TIME.
NOW SEAN MOONEY.
>> OKAY.
AS WE TRANSITION SLIDES I'LL
INTRODUCE DR. MOONEY, DIRECTOR
OF THE CENTER FOR INFORMATION
TECHNOLOGY AND IS RESPONSIBLE
FOR PROVIDING LEADERSHIP AND
DIRECTION FOR THE ORGANIZATION
INCLUDING OVERSEEING A PORTFOLIO
THAT FACILITATES RESEARCH
INCLUDING A WORLD RENOWNED
SUPERCOMPUTER, STATE-OF-THE-ART
NETWORK, CLOUD-BASED SERVICE,
COLLABORATION TOOLS TO PROMOTE
FLEXIBILITY AND PRODUCTIVITY.
BEFORE JOINING CIT, DR. MOONEY
SERVED AS PROFESSOR OF
BIOMEDICAL INFORMATICS AND
MEDICAL EDUCATION AT UNIVERSITY
OF WASHINGTON SCHOOL OF
MEDICINE.
WELCOME, DR. MOONEY.
>> GREAT.
I THANK YOU.
IT'S REALLY A PLEASURE TO BE
HERE.
I AM SIX MONTHS INTO MY JOB.
I'M NEW TO THE FEDERAL
GOVERNMENT.
I'M GOING TO START. THERE TODAY
WE'RE GOING TO TALK ABOUT I.T.
AND THE WORK THAT WE'RE DOING TO
THINK ABOUT BOTH HOW WE PROVIDE
INFORMATION TECHNOLOGY SERVICES
TO THE NIH AS A WHOLE BUT THEN
ALSO HOY DO -- HOW DO WE THINK
ABOUT THE CONCEPT OF CYBER
INFRASTRUCTURE FOR THE
BIOMEDICAL RESEARCH COMMUNITY AS
A WHOLE.
I THANK SUSAN AND STEVE WHO
WE'LL HEAR FROM IN A SECOND,
HUGE PARTNERS FOR CIT BEFORE I
GOT HERE, CONTINUE TO BE GREAT
PARTNERSHIP FOR THE WORK THAT WE
ARE DOING.
SO, WHAT I'M GOING TO DO TODAY,
I THINK A LOT OF FOLKS DON'T
REALLY KNOW WHAT THE CENTER FOR
INFORMATION TECHNOLOGY IS.
I'M GOING TO TALK AND INTRODUCE
THE CIT AND THE WORK WE DO.
AND THEN I'LL TALK ABOUT OUR,
YOU KNOW, FOCUS ON BUILDING A
COLLABORATIVE NIH FOR
INFORMATION TECHNOLOGY, TO
SUPPORT ALL NEEDS OF THE OTHER
26 I.C.s WITHIN THE NIH, I'LL
TALK ABOUT THE CLOUD, I'LL TALK
ABOUT THE TOOLS FOR CYBER
INFRASTRUCTURE AND OUR STRATEGY,
AND HOW WE WORK WITH NLM TODAY,
AND HOW WE CAN WORK WITH NLM WE
THINK IN THE FUTURE.
OKAY, SO, CIT WAS STARTED IN
1954, BACK WHEN COMPUTERS WERE,
YOU KNOW, VERY, VERY
RUDIMENTARY, GETTING INTO
SCIENCE AND THE WORK WE DO.
TODAY WE'RE ALMOST 1300 PEOPLE
SUPPORTING I.T. ACROSS THE NIH.
AND I'LL TALK ABOUT THE KIND OF
WORK WE'VE DONE THAT WE'VE
EVOLVED INTO DOING THAT TODAY,
BUT EVERYTHING THAT YOU MIGHT
IMAGINE THAT YOU COULD THINK
ABOUT WHAT THE NIH MIGHT NEED TO
DO AND THINK ABOUT WE PROBABLY
HAVE SOME TOUCH POINTS INTO IT
INCLUDING CLOUD TECHNOLOGIES,
I'LL TALK MORE ABOUT THAT IN A
SECOND, HIGH PERFORMANCE
COMPUTING FOR THE INTRAMURAL
RESEARCH PROGRAM, BOTH BUSINESS
AND RESEARCH APPLICATIONS TO
SUPPORT THE FUNCTIONS OF THE NIH
BUT ALSO SUPPORT LIKE FOR
EXAMPLE CLINICAL RESEARCH,
RESEARCH COMPUTING MORE IN
GENERAL, AS A SERVICE FROM RACK
SPACES AT SERVERS TO
INFORMATICS.
IDENTITY AND ACCESS MANAGEMENT,
WE MANAGE YOUR COMMONS I.D.s,
WE MANAGE ACCESS FOR EMPLOYEES
OF THE NIH.
WE MANAGE THE NIH NETWORK.
I'LL TALK MORE ABOUT CYBER
INFRASTRUCTURE AND DEFINE THAT.
WE MANAGE COLLABORATION TOOLS
AND SUPPORT CYBERSECURITY FOR
THE NIH.
WHEN I GOT HERE THERE WAS IN
FACT A STRATEGY AND PLAN, THINGS
WE COULD WORK OFF OF, PATTI
BRENNAN AND MY PREDECESSOR
ANDREA NORRIS WORKED ON A
STRATEGIC PLAN PLAN FOR THE
DIGITAL NIH.
THAT PLAN WAS PUBLISHED.
YOU CAN GOOGLE IT AND READ IT.
IT'S ONLINE.
AND THEY DEFINED KIND OF FOUR
AREAS FOR, YOU KNOW, FOR THIS
STRATEGIC PLAN.
MANAGEMENT OF THE EXTRAMURAL
PROGRAM THAT YOU MIGHT EXPECT,
INTRAMURAL CLINICAL RESEARCH
PROGRAM, THE INTRAMURAL BASIC
RESEARCH PROGRAM, AND
ADMINISTRATION AND MANAGEMENT OF
THE NIH.
THROUGH THAT THEY MADE FIVE -- A
SET OF FIVE RECOMMENDATIONS,
EXACTLY WHAT YOU MIGHT EXPECT.
YOU KNOW, INNOVATION AND
INFRASTRUCTURE, A COMMON
ARCHITECTURE, THINGS WE TALK
ABOUT WITH THE NLM COMMUNITY.
DIGITAL COMPETENT WORKFORCE.
TECHNOLOGY TO SUPPORT ANYWHERE
POST-PANDEMIC, SO ZOOM CALLS,
LOTS OF TEAMS MEETINGS, AND THEN
OF COURSE CYBERSECURITY, WHICH
IS OF COURSE VERY, VERY
IMPORTANT.
I.T. IS NOT IN THE NIH'S CORE
MISSION WHICH IS INTERESTING IN
THAT WE'RE THE ONLY I.C., CIT,
THAT DOESN'T HAVE A FACA
COMMITTEE LIKE THIS COMMITTEE
THAT'S HERE.
EXTERNAL ADVISORY COMMITTEE
WHICH I THINK IS ABSOLUTELY MIND
BOGGLING BECAUSE WE'RE DOING
STUFF NOT IN THE NIH MISSION,
AND WE'RE ONE PLACE WE SHOULD
GET OUTSIDE ADVISORS.
WE STARTED AS PART OF THE PATH
TO GET THERE, WE STARTED A
WORKING GROUP FOR THE ADVISORY
COUNCIL TO THE DIRECTOR THAT IS
NOW TASKED, WE'VE GOT INVITES
AND ACCEPTANCES OUT, AND WE'RE
GOING TO START MEETING.
THIS IS A LONGER TERM PLAN TO
CREATE A COUNCIL FOR I.T. AND
CYBER INFRASTRUCTURE TO GIVE US
ADVICE, JUST LIKE YOU ARE GIVING
ADVICE TO THE NLM TO THINK ABOUT
WHAT OUR OPERATIONAL STRATEGY IS
FOR I.T. AND SUPPORT US.
LET ME TALK VERY BRIEFLY ABOUT
KINDS OF THINGS WE DO.
I'LL MOVE QUICKLY BECAUSE I WANT
TO MAKE SURE I GET THROUGH
EVERYTHING.
WE RUN THE NIH NETWORK.
45,000 STAFF, 700,000 VISITORS
ACROSS 200 NIH BUILDINGS.
4300 MILES OF 100-GIGABIT
NETWORK THAT INCLUDES NETWORK
OUT OF STATE TO NORTH CAROLINA,
TO MONTANA, TO ARIZONA, THIS
NETWORK IS LEVERAGED BY HEALTH
AND HUMAN SERVICES MORE BROADLY,
AND I'LL JUST SAY THAT AS I'VE
GOTTEN HERE AND LEARNED, REALLY
THIS IS A NATIONAL STRATEGIC
NETWORK, IN TERMS OF THE KIND OF
THINGS THAT GO ACROSS, TO
SUPPORT HHS'S MISSION AND OF
COURSE THE MISSION OF THE NIH.
WITHIN THAT, THE KIND OF
HARDWARE IS MIND BOGGLING.
WE HAVE THE WIRED NETWORK,
ALMOST 10,000 OF WIRELESS ACCESS
POINTS LIKE THE ONES YOU SEE IN
THE BUILDINGS AROUND US.
WE EVEN MANAGE A CELLULAR
NETWORK.
AND ONE OF THE THINGS THAT I
WANT FOLKS TO THINK ABOUT, AND
YOU SEE THIS IN YOUR OWN ROLES,
OVER THE YEARS I.T. COSTS HAVE
GONE LIKE THIS.
WE'VE SEEN WIRED NETWORKS
APPEAR, NOW WE SEE WIRELESS
NETWORKS BUT WIRED NETWORKS
HAVEN'T GONE AWAY.
WE'RE SEEING CELLULAR NETWORKS,
WIRELESS, THE WI-FI HASN'T GONE
AWAY.
COSTS WITH GOING UP IN I.T.
GOING UP IN DATA, AND NOW WE
HAVE A.I., COSTS ARE GOING UP IN
A.I.
ALL THESE ACCUMULATED, WE'RE NOT
REMOVING THINGS FROM THE PAST.
IT'S A REAL CHALLENGE FOR THE
BIOMEDICAL RESEARCH COMMUNITY AS
A WHOLE, HUGE CHALLENGE FOR I.T.
WE MANAGE ALL THE COLLABORATION
TOOLS THAT ARE OUT THERE.
WE'VE INITIATED 2.5 MILLION
ZOOM, WEBEX, AND TEAMS MEETINGS
LAST YEAR UNDER OUR LICENSES
THAT WE SUPPORT.
AND ALL OF THE THINGS THAT --
ALL THE COLLABORATIONS AND
WEBINARS AND THINGS YOU DO, A
LOT ARE RUN BY CIT, NOT ALL, A
LOT OF ICs HAVE THEIR OWN
NETWORKS.
WE RUN A SUPERCOMPUTER, BIOWULF.
IN 2004 I WAS DOING RESEARCH,
AND BACK THEN IBM BLUEJEAN WAS
FASTESSED.
TODAY TODAY KIDS' GAME SYSTEMS
HAVE THE SAME AMOUNT OF
CALCULATIONS IT CAN DO AS THE
$2,004,
2000 $100 MILLION SUPERCOMPUTER.
WE DID A LOT OF RESEARCH IN THE
INTRAMURAL PROGRAM, OUR
SUPERCOMPUTER IS 105,000 CORES,
AT ONE POINT IN THE TOP 50
AGING, NEED TO REFRESH IT, IT'S
JUST IN THE BUILDING THAT'S
RIGHT OVER HERE.
AND IT HAS ABOUT A THOUSAND
GPUs.
GPUs ARE KEY, I READ IN THE
NEWS TESLA HAS BUILT A $3
BILLION SUPERCOMPUTER IN TEXAS
TO SUPPORT THEIR A.I.
ACTIVITIES.
IT'S ALL GPUs, YOU CAN IMAGINE
JUST EXACTLY HOW MUCH CAPABILITY
IS NEEDED TO MEET THAT A.I.
WORLD, AND WE'RE DEFINITELY
PAYING ATTENTION TO IT.
NOT SURPRISINGLY, BIOWULF IS
SATURATED TODAY IN TERMS OF USE,
RUNNING RIGHT NOW ABOUT 100%,
AND WE ARE AVERAGING AT THIS
POINT NOW ABOUT 600 PAPERS
PUBLISHED USING BIOWULF'S
INFRASTRUCTURE TODAY.
ALL RIGHT.
LET'S TALK ABOUT CYBER
INFRASTRUCTURE.
I LIKE THAT TERM.
I DON'T KNOW IF EVERYBODY LIKES
THAT TERM BUT I LIKE IT.
IT CAME FROM THE NATIONAL
SCIENCE FOUNDATION ABOUT 20
YEARS AGO, REALLY TALKS ABOUT
THAT COLLABORATIVE NETWORK AS
DATA AND COMPUTER INFRASTRUCTURE
OF ALL THOSE THINGS THAT ENABLE
BIOMEDICINE AND BIOMEDICAL
RESEARCH.
AND THAT'S THE WAY I LIKE TO
THINK ABOUT THINGS.
AT THE NIH, CYBER INFRASTRUCTURE
IS A PARTNERSHIP BETWEEN ODSS
AND SUSAN, THE NATIONAL LIBRARY
OF MEDICINE HERE, CIT, THE
OFFICE OF THE CIO, AND THEN ALL
OF THE I.C.s WITHIN THE NIH
HAVE THEIR OWN I.T. SHOPS DOING
INFORMATICS AND DELIVERING THE
MISSION THEY HAVE TO DELIVER.
JUST LIKE A UNIVERSITY, WE'RE
PRETTY SILOED, I THINK.
I THINK THAT'S A GOOD WAY TO
CHARACTERIZE IT.
I COME FROM THE UNIVERSITY OF
WASHINGTON, SIX MONTHS AGO I WAS
IN A SCHOOL OF MEDICINE AT A
HEALTHCARE SYSTEM THAT SAW A
MILLION PATIENTS A YEAR, VERY
SIMILAR.
32 OR 31 ACADEMIC DEPARTMENTS
ALL DOING THEIR OWN THING WITH
THE HEALTH SYSTEM THAT SOME
PARTS WERE ALSO DOING ITS OWN
THING, SOME WERE MORE
CENTRALIZED OR INTEGRATED.
LET'S TALK ABOUT THE CLOUD.
YOU HEARD ABOUT THE STRIDES
PROGRAM BRIEFLY FROM SUSAN, WE
HAVE A PARTNERSHIP WITH THE
THREE KEY CLOUD VENDORS, AMAZON,
GOOGLE, MICROSOFT.
AND HAVE AN AGREEMENT WITH THOSE
CLOUD VENDORS TO PROVIDE CLOUD
RESOURCES AT A DISCOUNT, AND
STRIDES IS WIDELY USED
INTERNALLY AT THE NIH, BUT ALSO
IN THE EXTRAMURAL WORLD, MAYBE
SOME OF YOU HAVE USED STRIDES
BEFORE, I THINK WHEN I WAS AT
THE UNIVERSITY OF WASHINGTON WE
MADE HEAVY USE OF THE STRIDES
PROGRAM.
AND I THINK ONE OF THE THINGS I
WANT TO IMPRESS UPON THIS GROUP
IS THAT STRIDES IS NOT JUST A
DISCOUNT.
I THINK IT'S A COMMON PLATFORM
THAT ENABLES US TO BUILD OFF OF
THE CLOUD, COLLABORATIVELY.
I'LL GIVE EXAMPLES OF HOW WE'RE
DOING THAT.
TODAY THERE ARE 334 MILLION
GIGABYTES IN THE STRIDES
PROGRAM, SERVING ABOUT 2500
RESEARCH GROUPS, RESEARCH
PROGRAMS, MANAGING EVERY SINGLE
KIND OF DATA THAT YOU COULD
POSSIBLY IMAGINE.
MOST OF THE I.C.s TAKE
ADVANTAGE OF STRIDES INCLUDING
NLM, PART OF THE OUR
COLLABORATION WITH THE NATIONAL
LIBRARY OF MEDICINE AND MANY
RESEARCH FUNDED PROGRAMS ENABLE
THIS.
STRIDES IS LED OUT OF ODSS,
MANAGED BY CIT, SO A GREAT
EXAMPLE OF HOW LEADERSHIP OUT OF
SUSAN'S TEAM AND THE OPERATIONAL
WORK THAT CIT DOES CAN
COLLABORATE AND BUILD HOPEFULLY
A MORE COLLABORATIVE BIOMEDICAL
RESEARCH INFRASTRUCTURE.
ONE EXAMPLE OF SOMETHING YOU MAY
HAVE SEEN WE'VE ANNOUNCED
RECENTLY ALSO A GOOD
COLLABORATION WITH ODSS AND LED
OUT OF SUSAN'S TEAM IS NIH CLOUD
LAB.
THIS IS ANYBODY THAT'S
ASSOCIATED WITH NIH OR
AFFILIATED WITH NIH RESEARCH
PROGRAMS COULD BE, WITHIN THE
EXTRAMURAL WORLD, CAN MAKE A CAN
AND GET $500 OF CREDITS TO
ACCESS TO THE CLOUDS, ONCE THEY
GET THOSE $500 OF CREDITS AND
GET IN THEY CAN GET ACCESS TO
TRAININGS, OTHER THINGS
COLLABORATIVELY DEVELOPED BY A
NUMBER OF IDeA STATES
INSTITUTION, FUNDED BY IDSS,
THAT WORK TOGETHER TO BUILD
TRAININGS HOW TO USE THE CLOUD.
IF YOU HAVE INVESTIGATORS
INTERESTED IN GETTING ACCESS TO
THE CLOUD, UNDERSTANDING HOW THE
CLOUD WORKS, WORKING, THEY CAN
GET FREE ACCESS UP TO $500 BUT
WILL ALSO GET BIOMEDICAL
RESEARCH COMMUNITY DEVELOPED
TRAININGS HOW TO USE IT IN
DIFFERENT AREAS LIKE SEQUENCE
ANALYSIS, THAT SORT OF THING.
I WANT TO STRESS THAT WE BUILT A
COMPUTATIONAL PLATFORM THAT
GIVES YOU A DISCOUNT AT ACCESS
BUT IS LEVERAGED TO BUILD UPON
IT AS A PLATFORM TO DO THINGS
COLLABORATIVELY THAT ARE OF
INTEREST.
OKAY.
LET ME TALK ABOUT SOME TOOLS FOR
MANAGING CLINICAL RESEARCH DATA.
AND THE KIND OF DIGITAL
ECOSYSTEM OF CYBER
INFRASTRUCTURE.
I THINK ABOUT THIS LIKE LEGO
BLOCKS, PLASTIC INTEROPERABLE
BLOCKS, REUSABLE, INTEROPERABLE,
YOU INVESTIGATORS CAN BUILD THEM
IN THE WAY THAT THEIR NEEDS,
WHAT THEY WANT TO ACCOMPLISH.
SO I LIKE TO THING ABOUT CYBER
INFRASTRUCTURE LIKE
INTEROPERABLE BLOCKS, WE PROVIDE
TOOLS HOPEFUL THEY WILL BE
INTEROPERABLE THAT THAT WAY AND
SUPPORT ANYTHING YOU COULD
IMAGINE, BIOINFORMATICS
WORKFLOWS, COMPONENTS OF
CLOUD-BASED PLATFORMS, COULD BE
SPECIALIZED COMPUTING LIKE
GPUs, OR A.I. TOOLS, ANYTHING
YOU COULD IMAGINE A BIOMEDICAL
RESEARCHER MIGHT PUT TOGETHER.
ONE OF THOSE EXAMPLES IS THE
RESEARCHER EDUCATION SERVICE,
REF, A GREAT COLLABORATION
WHETHER WE'RE SOLVING COMMON
PROBLEM OF GETTING
AUTHENTICATION INTO SYSTEMS,
INTO THE CLOUD, LEVERAGING THE
STRIDES PROGRAM, AUTHORIZATION
ACROSS DIFFERENT PLATFORMS
MANAGING CONTROLLED ACCESS
DATA THAT LEVERAGES dbGAP AND
WORK CIT IS DOING, ET CETERA.
SOMETHING WE'RE VERY INTERESTED
IN IS THE CONCEPT OF A
COMPUTATIONAL WORKSPACE.
THAT IS, WE'VE SEEN A NUMBER OF
DIFFERENT PLATFORMS THAT ARE
CLOUD BASED THAT MANAGE DATA.
BEFORE I CAME HERE, I WAS
CONSULTING FOR A NON-PROFIT THAT
WAS REFRESHING THEIR CLINICAL
RESEARCH PLATFORM, INCLUDING
PATIENT DATA, GENETIC DATA,
IMAGING PATHOLOGY DATA, ALL THE
THINGS YOU MIGHT EXPECT.
THEY WERE REFRESHING THEIR CLOUD
PLATFORM, PUT AN RFP UP TO GET
VENDORS TO COME IN AND DO THAT
REFRESH.
AND THEY GOT A LOT OF PROPOSALS.
THERE'S A HUGE INDUSTRY NOW
THAT'S OUT THERE THAT IS
BUILDING KIND OF THE NEXT
GENERATION OF THESE CLOUD TOOLS
TO SUPPORT CLINICAL DATA
MANAGEMENT.
SO WE'RE THINKING ABOUT HOW CAN
WE LEVERAGE THE EXISTING
PLATFORMS AND WHAT ARE THE TOOLS
THAT WE CAN PROVIDE AS A SERVICE
THAT CAN MAKE THEM EASIER TO
USE, MAKE THEM MORE
INTEROPERABLE, SPIN UP EASIER,
EASIER TO WORK WITH IN THE
FEDERAL GOVERNMENT ENVIRONMENT.
WE CAN TALK ABOUT THAT IN THE
DISCUSSION, AND HOW CAN WE SCALE
THEM BETTER.
LOTS OF EXAMPLES, ONE EXAMPLE IS
NIH RECOVERS PLATFORM IS BUILT
OFF OF, AGAIN, CLOUD AND --
CLOUD AND CIT AND OTHERS HAVE
PROVIDED.
SO, LET'S TALK ABOUT OUR
STRATEGY.
AGAIN, I'M PRESENTING HERE DOING
A ROAD SHOW THIS WEEK, IT'S
COUNCIL WEEK.
I'M DOING A ROAD SHOW THIS WEEK,
LOOKING FOR ADVICE, EITHER TODAY
OR OFFLINE IN THE FUTURE, ABOUT
WHERE WE'RE HEADED.
AND HOW WE'RE -- YOU KNOW, WHAT
DIRECTION WE'RE GOING IN.
I'D LOVE THIS GROUP HERE, YOU
ARE REALLY EXPERTS THAT CAN KIND
OF HELP US WITH HOW WE ARE
MOVING FORWARD.
SO, WE REALLY DESIRE TO BE THE
HUB FOR I.T. SERVICES.
WE WANT TO PROVIDE TOOLS THAT
CAN BE COLLABORATIVE, IN
COLLABORATION WITH I.C.s,
INCLUDING NLM, ODSS, AND OTHERS,
THAT WILL MAKE, YOU KNOW,
MANAGING OR DOING BIOMEDICAL
RESEARCH EASIER.
THINGS WE ALREADY DO, I TALKED
ABOUT CLOUD, TALKED ABOUT
AUTHORIZATION AND
AUTHENTICATION, BASICALLY IAM
FOR BIOMEDICAL RESEARCH,
WORKSPACES AND HOW WE SUPPORT
THEM.
I DIDN'T TALK ABOUT BRICKS, BUT
IT'S A PLATFORM THAT WE SUPPORT,
ONE OF THOSE TOOLS THAT ARE
WORKSPACES.
IF YOU HAVE DATA, NEED A SERVICE
TO MANAGE, WE CAN HELP WITH
THAT.
WE'RE ALSO HELPING WITH
ENTERPRISE ROLLOUT OF LARGE
LANGUAGE MODELS AND KIND OF
ADVANCED A.I., THESE ARE
SERVICES WHERE WE CAN SHARE
FEDERAL NIH CONFIDENTIAL
INFORMATION, WITH THE CLOUD,
WITH THESE A.I. SERVICES, IN A
WAY THE INVESTIGATORS KNOW THEY
ARE SECURELY PROTECTED.
THINGS WE WOULD LIKE TO DO IN
THE FUTURE, SCALE BETTER, BE
MORE AUTOMATED IN TERMS OF WHAT
WE DO, COLLABORATE MORE WITH
GROUPS LIKE NLM, AND WE WANT TO
MAKE ANALYSIS ENVIRONMENT
EASIER.
I WORKED WITH A NUMBER OF
NIH-FUNDED CONSORTIA BEFORE I
CAME HERE TO CIT, WHEN I WAS AT
THE UNIVERSITY OF WASHINGTON,
AND I TELL 'YA, ALL OF THEM WERE
WORKING, TRYING TO BUILD
CLOUD-BASED ENCLAVES OR
SANDBOXES, WHATEVER YOU WANT TO
CALL THEM, AND WERE STRUGGLING,
COME UP WITH THEIR OWN SOLUTION
AND STRUGGLING.
ONE PROJECT THREE TIMES TO GET
WHERE THEY ARE, WE MAY BE ABLE
TO HELP WITH SOME OF THAT.
CLINICAL TRIALS TOO IS AN
IMPORTANT AREA.
I FIND THAT CLINICAL TRIALS KIND
OF SPACE IS MAYBE -- NEEDS
MODERNIZATION AT NIH.
THEY HAVE NOT KEPT UP WITH
INSTITUTIONSES AND THERE MAY BE
OPPORTUNITIES, I CAN'T TELL YOU
HOW MANY CLINICAL TRIALS ARE
CURRENTLY BEING RUN AT THE NIH
RIGHT NOW, IT'S SURPRISING.
SO I'M JUST ABOUT OUT OF TIME.
SO I WANT TO MENTION ALSO WHAT
ARE WE UNLIKELY TO DO?
WE'RE NOT GOING TO BUILD AND
LEAD NATIONAL INFORMATION
RESOURCES, THAT'S WHAT THE NLM
DOES.
WE'RE NOT GOING TO BUILD
CANCER-BASED CLOUD PLATFORMS FOR
MANAGING, THAT'S WHAT NCI DOES.
WE'RE NOT GOING TO RUN AN
ASSOCIATION STUDY, THAT'S WHAT
NHGRI DOES.
REMEMBER THE OLD COMMERCIALS, WE
DON'T MAKE THE THINGS YOU DO, WE
MAKE THE THINGS YOU DO BETTER,
THE OLD BASF COMMERCIALS, WE
WANT TO BE SERVICES WE CAN
PROVIDE TO MAKE CYBER
INFRASTRUCTURE EASIER, MORE
SCALABLE, AND MEET KIND OF ALL
THOSE THINGS WE TALK ABOUT A
LOT, BUT, YOU KNOW, AND ARE
THINKING ABOUT HOW TO GET THERE,
FAIR DATA, ET CETERA.
SOMETHING ELSE BRIEFLY IS THE
CONCEPT OF DATA LIFE CYCLE,
SOMETHING THE NLM HAS THOUGHT A
LOT ABOUT OVER THE LAST -- OVER
PROBABLY ITS ENTIRE EXISTENCE,
AND THE CLINICAL WORLD, CLINICAL
INFORMATICS WORLD, HAS COME UP
WITH THIS CONCEPT OF A MATURITY
MODEL THAT YOU'RE FAMILIAR WITH,
MANY OF YOU ARE MORE EXPERTS
THAN I AM ON, AND I LOVE THE
CONCEPT OF THE MATURE MODEL AND
DATA RESOURCES, THINKING ABOUT
THE LIFE CYCLE OF A RESOURCE,
THINK ABOUT ALL THESE THINGS I
JUST TALKED ABOUT, LEGO PIECES,
CYBER INFRASTRUCTURE, TALKED
ABOUT FAIR DATA, YOU CAN IMAGINE
DEFINING AND MEASURING MATURITY
OF RESOURCE BASED ON HOW FAIR
THE DATA IS, HOW INTEROPERABLE,
LEVERAGING THE PLATFORMS OR LEGO
BLOCKS, HOW STANDARDIZED ARE
THEY.
AS WE TALK ABOUT THESE, YOU
KNOW, SIGNIFICANT OR STRATEGIC
DATA ASSETS THAT SUSAN WAS
TALKING ABOUT, WE WOULD LIKE TO
COME IN AND HELP THINK ABOUT THE
MATURITY OF THOSE RESOURCES FROM
JUST AN I.T. SERVICES
PERSPECTIVE.
AND WE'VE BEEN TALKING A LITTLE
BIT ABOUT KIND OF LIKE WHAT
WOULD BE THE SUSTAINABILITY,
WHAT WOULD BE THE TOOLS THAT
WOULD HELP DEFINE WHAT THAT
MATURITY IS.
THIS IS A CONVERSATION MAYBE
COME BACK TO THIS GROUP ON AT
SOME POINT IN THE FUTURE,
THINKING ABOUT HOW WE FUND
BIOMEDICAL DATA RESOURCES.
THERE ARE A LOT FUNDED ACROSS
THE I.C.s, SILOED, MANY OF
THEM, WHAT IS THE LIFE CYCLE,
HOW DO WE SUSTAIN, SUNSET,
SUPPORT THEM LONG TERM, MAKE
THEM MORE EFFICIENT, EASIER TO
RUN.
ALL RIGHT.
I'M DEFINITELY OUT OF TIME.
WE ALREADY COLLABORATE A LOT
WITH THE NLM.
WE MENTIONED RESEARCH OR
AUTHENTICATION, STRIDES, WORK IN
GENERATIVE A.I. AND SPINNING UP
OPERATIONAL I.T. GENERATIVE A.I.
TOOLS, NLM UTILIZED STREETS, WE
HAVE A TON OF DISCUSSIONS HOW WE
CAN COLLABORATE ON I.T.
PERSPECTIVE OF THINGS WE DO.
AND I THINK A.I. IS A HUGE AREA,
VERY IMPORTANT, EVERYBODY WANTS
ACCESS TO IT.
WE WANT TO PROVIDE IT IN A
SECURE WAY.
SOMETHING I DO WANT TO MENTION
THAT I DON'T TOTALLY -- MAYBE
THIS GROUP KNOWS BUT I DON'T IF
THE RESEARCHER COMMUNITY AND THE
WORLD HAS FIGURED OUT WE'VE
ENTERED THE AGE COOPERATIONAL
A.I., GETTING IMPLEMENTED
WITHOUT HAVING DATA SCIENTISTS
IN THE LOOP.
I DON'T THINK THAT'S EVER
HAPPENED BEFORE.
USUALLY THEY ARE IMPLEMENTING IN
A PRACTICE, DOESN'T MATTER IF
IT'S OUTSIDE MEDICINE, A MACHINE
LEARNING GUY, A PERSON BEHIND IT
IMPLEMENTING AND DOING THAT.
TODAY WE'RE PUTTING -- DRAFTING
IN-BOX MESSAGES IN MY CHART,
AMBIENT SCRIBES FOR
DOCUMENTATION, ZOOM MEETINGS
TRACKING NOTES, ALL BEING DONE
OUTSIDE THE CONTEXT OF A DATA
SCIENTIST.
THERE'S A HUGE OPPORTUNITY TO
STUDY THAT.
WE'RE JUST THROWING A.I. AT
PROBLEMS, SOLVING IT, AT THE
RESEARCH, NEEDS TO GET IN THERE
AND HELP STUDY BETTER.
SOMETHING WORTH TALKING ABOUT.
DEFINITELY OUT OF TIME.
WE'LL HAVE A NEWSLETTER.
YOU SHOULD READ IT.
THANK YOU.
I'LL HAND OFF TO STEVE WHO I
THINK IS ONLINE AND WE'LL DO
QUESTIONS AT THE END.
>> GREAT.
THANK YOU, SEAN, AND EVERYONE.
LET ME PULL MY SLIDES UP HERE.
I WANT TO SAY AGAIN I REGRET I
CANNOT BE THERE IN PERSON TODAY
THIS HAS BEEN A FANTASTIC
PRESENTATION AND DISCUSSION THIS
MORNING.
AND WHAT I'M HOPING TO DO IS
SIMPLY SHOW A LENS HERE OF SOME
COLLABORATIVE PRIORITIES
DESCRIBED BY SUSAN AND SEAN,
THEY HAVE DONE A FANTASTIC JOB
LAYING OUT THE ENVIRONMENT IN
THE CONCEPT NLM IS INTERACTING
WITH NIH, HHS, SCIENTIFIC
COMMUNITY.
I SELECTED THREE THEMES TO WALK
THROUGH BRIEFLY FROM OUR SIDE
LOOKING BACK OUT AT THEM AS A
PARTNER WHAT ARE WE DOING IN
THIS SPACE.
BUT I COULD REVIEW THAT WITH YOU
BECAUSE I DON'T THINK I COVERED
THIS FOR THE BOARD BEFORE IN ANY
PARTICULAR DETAIL.
THE THREE THINGS ARE A.I.,
SUSTAINABILITY, AND ENTERPRISE
INFORMATION LANDSCAPE.
SO JUST REAL QUICKLY, YOU KNOW,
NLM BRINGS STRONG ASSETS INTO
THE A.I. RESEARCH CONVERSATION.
WE HAVE A MISSION AROUND
INFORMATION, STRONG REPUTATION,
EXPERTISE AND WORKFORCE CAPACITY
THAT COULD BE DEVELOPED TO APPLY
A.I. BOTH INTERNALLY TO
PRODUCTION OPERATIONS AND
EXTERNALLY AS ADVICE OR SUPPORT
FOR THE COMMUNITY.
INTERNALLY THIS YEAR, I THINK
THIS HAS BEEN BRIEFED TO YOU
BEFORE IN AN UPDATE BUT WE HAVE
DONE SOME PILOT PROJECTS WITHIN
NLM.
THIS WAS ACROSS OUR DIVISIONS.
WE WERE LOOKING AT TRYING TO
ADVANCE A COUPLE GOALS.
FIRST WE WANTED TO UNDERSTAND
THIS WORKSPACE IN AZURE OUT OF
PROGRAM SEAN ELOQUENTLY
DESCRIBED, HOW DO WE GO GO
THROUGH THE MECHANICS OF HAVING
STAFF CREATE AND DEVELOP
PROJECTS.
WE WANTED TO DEVELOP PROJECTS
THAT APPLY TO THEIR NLM WORK,
NOT RESEARCH BUT ACTUALLY THESE
WOULD BE OPERATIONAL TASKS,
VALUES TO OUR SERVICES.
IT WAS AN OPPORTUNITY THEN TO
TRY TO APPLY SOME OF THE UTILITY
AND RISK MITIGATION FRAMEWORKS,
INTRODUCE THAT AS A CONCEPT AND
I'LL COME BACK TO THAT.
FINALLY DO SOME WORKFORCE SKILL
DEVELOPMENT IN GENERATIVE A.I.
AND THE BENEFITS WE WERE SEEING
COMING OUT OF THESE PILOTS WAS
GOING TO BE EFFICIENCY,
REDUCTION OF COST IN TIME, DOING
SOME PROFESSIONAL WORK,
CURATION, COMPOSITION, RESPONSE
TO USER INQUIRIES, ET CETERA.
IMPROVING QUALITY AND ACCURACY
OF OUR INDEXED TERMS AND
SERVICES, AND SO IT IS ACTUALLY
LOOKING FOR ERRORS AND OUTLIERS,
LARGE CORPUS IN DATASETS,
ENHANCE THE USER EXPERIENCE
THROUGH MORE CUSTOMIZED AND
RESPONSIVE ANSWERS TO PARTICULAR
USER QUESTIONS, INSTEAD OF
GENERIC FAQs, AND TRY TO DRIVE
USER ACCESS AND DISCOVERY.
I'LL TALK ABOUT THAT A LITTLE
BIT MORE TOO.
WE DID THIS IN FOUR LARGE AREAS,
I THINK THERE'S TEN PROGRAMS
HERE SHOWN ON THE RIGHT.
I WON'T REVIEW THE LIST BUT THEY
WERE IN THE FOUR DOMAINS,
RESPONSIVE CUSTOMER SERVICE, AND
THIS WOULD BE AROUND HOW DO WE
ANSWER CUSTOMER COMMUNICATION,
WE GET THOUSANDS OF RESPONSES A
DAY, HOW TO DO THAT IN A SAFE
WAY.
WE'RE LOOKING DEEPLY INTO
OPERATIONAL PROCESS EFFICIENCY.
NLM, YOU'VE HEARD IN SEVERAL
TALKS, HAS PETABYTES OF DATA
FLOWING IN.
WE HAVE A FLAT OR MODESTLY
GROWING BUDGET WITH LIMITED
STAFF.
WE'RE ALWAYS LOOKING FOR NEW
OPPORTUNITIES TO LEVERAGE STAFF
EXPERTISE AND HAVE CURATION
APPLIED AT SCALE, HAVING
ORGANIZATION APPLIED AT SCALE
THROUGH TRANSFORMATION OF
METADATA AND RETRIEVAL SYSTEMS,
OR AS I MENTIONED YESTERDAY EDIT
SUPPORT FOR UMLS IN NEW TERMS
AND CONCEPTS, HOW DO YOU MATCH
THEM INTO EXISTING VOCABULARY
SYSTEM.
WE'RE TRYING TO LEVERAGE
ANALYTICS PARTS, SUMMARIZATION
AND ANALYSIS, LOOKING FOR DATA
VISUALIZATION.
WE'VE GOT RICH TOOL DEVELOPMENT
IN THE EXTRAMURAL PROGRAM
LOOKING AT GRANT PORTFOLIO
ANALYSIS, DOING NETWORK ANALYSIS
IN OUR SYSTEMS, HOW DATA AND
QUERIES ARE MOVED ACROSS USER
SESSIONS TO UNDERSTAND WHERE THE
INTERACTIONS ARE BETWEEN DATA
SYSTEMS.
FINALLY THERE'S RESEARCH WITHIN
THE IRP THAT'S DOING THINGS LIKE
SUPPORTING CLINICAL SUPPORT IN
TRIAL GPT, UNDERSTANDING
CLINICAL TRIALS, A SAMPLING FROM
THE FIRST ROUND OF CREATING DEMO
PROJECTS THAT WERE BOTTOM-UP
DESIGNED AND PROPOSED BY STAFF.
IT WAS A POWERFUL OUTCOME,
COMPLEMENTARIES ON THE
INTRAMURAL RESEARCH SIDE THERE'S
A SECOND CHALLENGE HOW DO WE
TAKE THE DATA AND HOLDINGS WITH
NLM AND IMAGINE TRANSFORMING
INTO KNOWLEDGE, KNOWLEDGE
GRAPHS, WE HAVE RICH
COLLECTIONS, BIG DATA SETS, ON
ONE HAND A RICH CORPUS OF
LITERATURE FROM PUBMED CENTRAL,
OUR COLLECTION THERE, MANUSCRIPT
SUBMISSION SYSTEM FAIRLY
UNSTRUCTURED WITH ASPIRATION WE
COULD TAKE THE PRE-COMPUTE LINKS
AND ADDITIONAL COMPUTATION AND
GENERATE WHAT'S ILLUSTRATED IN
THE CENTER, A KNOWLEDGE GRAPH
THAT WOULD BE REPRESENTATIVE AND
QUERIABLE AROUND PARTICULAR
FACETS.
SO WE'RE TRYING TO PILOT THIS IN
A LIMITED DOMAIN, I SAY LIMITED,
THROUGH SOMETHING CALLED THE
CELL KNOWLEDGE BASE.
CELLS ARE FUNDAMENTAL TO
BIOLOGY, AND YET AT NLM IT'S THE
ONE PART OF LIFE SCIENCES WE
DON'T HAVE A REAL RESOURCE
AROUND.
WE HAVE RESOURCES AROUND
MOLECULES, AROUND CHEMICAL
COMPOUNDS, SYSTEMS, AND HIGHER
LEVEL PHYSIOLOGICAL THINGS LIKE
HEALTH AND OUTCOME, BUT AT THE
LEVEL OF CELLS WE DON'T HAVE
ORGANIZED INFORMATION.
NIH OBVIOUSLY PUTS A LOT OF
RESEARCH IN THIS AREA.
WE HAVE THE CELL ATLAS AND MANY
PROGRAMS GENERATING DATA AS
SHOWN ON THE LEFT-HAND SIDE, AND
THERE ARE RICH STRATEGIC TOOLS
AND ASSETS THAT DESCRIBE MUCH OF
THE CELLULAR EXPRESSION, EVEN
DOWN TO SPECIFIC CELL IN THE
BRAIN, EFFECTS, WHERE THEY ARE
DOING TISSUE-SPECIFIBASED
EXPRESSION, TRYING TO UNDERSTAND
HOW THAT INTERACTS WITH DRUG
DOSING AND PHENOTYPIC OUTCOMES
SUCH AS ALZHEIMER'S DISEASE, WE
CAN IMAGINE A PROTEOSTASIS TIME
IN RESEARCH TRYING TO TAKE THIS
PRE-COMPUTED INFORMATION ON THE
LEFT-HAND SIDE AND COUPLE THAT
WITH SEMANTIC AND STATEMENTS
EXTRACTED FROM LITERATURE IN
PubMed
PUBMED CENTRAL THROUGH THE
SITUATION ITEM WE CAN MINE, OPEN
AC -- SYSTEM WE CAN MINE, TRAIN
TO GENERATE AND DEVELOP LARGE
LANGUAGE MODELS.
THE GOAL AND ASPIRATION IN THE
PILOT THEN IS TO DEVELOP LIKE I
SAID THIS KIND OF CENTRAL
KNOWLEDGE GRAPH WHICH REPRESENTS
CELL TYPES, BIOMARKERS, DISEASES
MANIFEST IN GENES AND COMPOUNDS
IN A STATEMENT QUERIABLE WAY
WHERE YOU COULD ASK QUESTIONS,
AS SHOWN HERE, WHAT ARE ARE
GOING TO BE CELL TYPES AND WITH
MARKER GENES THAT ARE ASSOCIATED
WITH ALZHEIMER'S DISEASE, THE
DRUG AS A TARGET, YOU CAN GET
CELL TYPES TARGETED OR CELL
TYPES THAT EXHIBIT BOTH, YOU
KNOW, MULTIPLE GENES THAT ARE
ASSOCIATED WITH BIOMARKERS FOR
ALZHEIMER'S DISEASE.
THIS IS JUST ONE STEP TO
UNDERSTAND HOW DO WE BUILD THESE
GRAPHS, HOW DO WE ORGANIZE THEM
FOR EFFICIENT COMPUTE, HOW DO WE
EXECUTE THOSE QUERIES IN REAL
TIME AT SCALE, MEANING MILLIONS
OF OPERATIONS PER SECOND,
BECAUSE THAT'S THE LOAD WE GET
IN PubMed AND ENTREE AND
OTHER SERVICES.
SO THIS IS VERY MUCH AN
ENGINEERING PROBLEM FIRST, TO
SAY WHAT'S THE RIGHT MODALITIES.
IT'S AN AREA WE'RE GOING TO HAVE
STRONG PARTNERSHIP WAS SEAN AND
SUSAN, AS WE UNDERSTAND HOW TO
DO THIS FIRST LOCALLY WITHIN NLM
HOLDINGS, AND THEN GENERALIZE
THIS ACROSS THE I.C. AND THE
OTHER ENTERPRISE ACTIVITIES.
THE LAST PART OF A.I. I WANTED
TO MENTION QUICKLY IS OUR ETHICS
TEAM.
WE HAVE A LEADERSHIP OPPORTUNITY
AT NLM TO UNDERSTAND AND HELP
PROMOTE BEST PRACTICES THAT CAN
TRY TO MAXIMIZE THE BENEFITS OF
A.I. DEVELOPMENT, WHILE
CONSCIOUSLY UNDERSTANDING
MODELING AND MITIGATING RISK.
THIS IS DONE THROUGH A COUPLE OF
RISK MITIGATION FRAMEWORKS.
THERE'S ONE DEVELOPED BY NIST.
THERE'S ONE THE FDA USES FOR
CLEARANCE AND EVALUATION OF
MEDICAL DEVICES, W.H.O. RELEASED
ONE LAST WEEK AROUND PANDEMIC
A.I. SURVEILLANCE.
THERE'S MANY OTHER LEGAL WHITE
HOUSE INITIATIVES AND EXECUTIVE
ORDERS THAT CREATE A CONTEXT
THAT'S ASKING FOR A CULTURE OF
CARE, CAUTION, TRUSTWORTHINESS,
TRANSPARENCY, IN THE DEVELOPMENT
OF A.I., THIS IS A PLACE WHERE
GOVERNMENT CAN LEAD, AND THIS IS
SOMETHING THAT NLM IS TRYING TO
INTERNALIZE, WHICH REALLY MEANS
IT'S A CULTURE CHANGE BECAUSE
YOU'RE HAVING TO TAKE THIS SENSE
OF RISK, BIAS, STRUCTURE, YOU
KNOW, QUESTIONING EVERY
ASSUMPTION ABOUT DATA AND MODELS
OF REPRESENTATION, HOW YOU'RE
TRAINING MODEL, AND ASKING WHAT
IS THIS REPRESENTATIVE OF, WHO
IS IT MISSING, IS IT
GENERALIZABLE TO THE AMERICAN
EXPERIENCE FOR ALL MINORITIES,
AGE GROUPS, DEMOGRAPHICS, AND
THAT'S ANALYTICAL EXERCISE THAT
IS IN A WAY VERY TAXING AND
CHALLENGING BUT REWARDING WHEN
YOU GET IT RIGHT.
THIS IS A NEW CULTURAL PIVOT FOR
NLM, SO WE BUILT A TEAM THAT HAS
REPRESENTATIVES OF ALL NLM
DIVISIONS TRYING TO PILOT THIS
WITH SOME OF OUR MAJOR SERVICES
AND PRODUCTS.
TO SEE HOW DO WE INTRODUCE
CULTURE OF CHANGE IN RESPONSE
A.I. OVERSIGHT.
THERE'S CHALLENGES, AS I
MENTIONED, THERE'S MANY
PLATFORMS WHICH ONE DO YOU WORK,
HOW DO YOU SOCIALIZE THIS?
HOW DO WE INCENTIVIZE INNOVATION
IN EXISTING FRAMEWORKS AROUND --
INSTEAD OF BUILDING YET ANOTHER
FRAMEWORK THAT THERE'S A BIT OF
EXHAUSTION MAYBE THERE'S TOO
MANY, UNDERSTANDING THE SWEET
SPOT.
MORE TO COME.
THIS IS SOMETHING WE'RE TRYING
TO APPLY AS WE DO OUR A.I.
DEVELOPMENT.
THIS WAS DONE IN OUR TEN DEMO
PROJECTS.
REAL QUICKLY I'M SENSITIVE TO
TIME HERE, THAT THE OTHER TWO
AREAS I WANTED TO MENTION, SUSAN
AND SEAN I THINK DID A FANTASTIC
JOB SETTING UP.
BUT JUST TO MENTION
SUSTAINABILITY IS A PRIORITY FOR
NLM AND NIH.
AND OUR ROLE IN THIS IS HELPING
TO OFFER SOME INSTITUTIONAL I.C.
LEADERSHIP IN DEVELOPING
MANAGEMENT TOOLS FOR SUFFICIENT
PLANNING AND SUSTAINING
STRUCTURES FOR STRATEGIC
BIOMEDICAL DATA ASSETS, HOW DO
WE MEASURE THEIR IMPACT?
THERE'S A LOT OF FUDGINESS IN
THIS AREA.
SUSAN REVIEWED EARLIER, IT'S
DIFFICULT TO GET METRICS.
IT'S DIFFICULT TO SAY EXACTLY
WHAT IS STRATEGIC.
THERE'S MANY INTERNATIONAL
GROUPS LIKE THE GLOBAL BIODATA
COALITION AND OTHERS TRYING COME
UP WITH STRATEGIES AND FRAMINGS.
WE'RE REALLY DIALING IN ON A
COUPLE OF FUNDAMENTAL TOOL
AREAS, FIRST IS UNDERSTANDING
SUSTAINABILITY PLANS, SEAN
OUTLINED THE CONCEPT TO APPLY TO
OUR OWN INTERNAL OFFERINGS AND
SYSTEMS TO SAY WHERE DO THEY
LAND ON THIS AXIS OR MATRIX,
WHAT CAN WE DO TO ENRICH AND
UNDERSTAND HOW THIS COULD BE
USED AS A FORWARD MANAGING TOOL.
WE'RE TRYING TO PARTICIPATE IN
COLLECTION AND REPORTING OF
METRICS, LIFE CYCLE OF DATA,
INCENTIVIZING SUBMISSION,
REWARDING AND IDENTIFYING
SUBMITTERS.
SUSAN MENTIONED DOIs, WE GO
TRY LOOK TO SAY ARE THERE
OPPORTUNITIES HERE TO CREATE
SERVICES AND RECORDS ALIGNED TO
SUBMITTERS, GIVING THEM A
MEASURE OF VALUE THROUGH USAGE
OR CITATION, AND SUNSETTING IS
RELEVANCE AS IMPORTANCE MIGHT
DIMINISH AS QUESTIONS OF SCIENCE
EVOLVE.
THAT'S NOT IN THE FIELD SO WE
HAVE TO LEARN TO LET YESTERDAY'S
WORK GO TO DO TOMORROW'S WORK.
THE DEVELOPMENT OF SBDA ADOPTION
OF STANDARDS, COMMON DATA
ELEMENTS, WE NEED TO THINK HOW
DO WE MAKE THAT SYSTEMATIC RICH
AND VALUABLE AND CROSS-WALK
BETWEEN CLINICAL AND RESEARCH
DATASETS.
THOSE FOUR AREAS ARE SUMMARIZING
THIS AT HIGH LEVEL TRYING TO
LOOK FOR TOOLS AND FRAMEWORKS TO
ASSESS THE MATURITY OF STRATEGIC
BIODATA ELEMENTS, TRYING TO
ASSESS THEIR IMPACT AND
SIGNIFICANCE, WE'RE TRYING TO
LOOK AT SUNSETTING AND
UNDERSTANDING ARE THEY STILL
RELEVANT TODAY?
ARE THEY VALUABLE BUT NEED TO BE
REIMAGINED FOR THE FUTURE?
FINALLY UNDERSTAND THEIR
INTEROPERABILITY, FOUR IMPORTANT
LENSES TO FLESH OUT MATURITY
MODELS AND FIGURE OUT WHERE TO
MAKE INVESTMENTS MOST IMPACTFUL,
INTERNALLY AND EXTERNALLY.
FINALLY THE COLLABORATIVE
OPPORTUNITIES AROUND INFORMATION
TECHNOLOGY.
SEAN DID A GREAT OUTLINING WHAT
PATI AND ANDREA AND DORIS SET
UP, DIGITAL NIH, THE AWARENESS
THAT SUSAN'S OFFICE ODSS, SEAN
AT CIT, NLM AND OFFICE OF THE
CHIEF INFORMATION OFFICER, ALL
PLAY ROLES COLLECTIVELY TO
ADVANCE THE ENTERPRISE
INFORMATION TECHNOLOGY LANDSCAPE
AT NIH.
NOT ONE OFFICE CAN DO IT ALL.
WE HAVE DIFFERENT ROLES.
THE NLM ROLE IN THIS KIND OF
QUARTET IS LEADING
BIOINFORMATICS AND DATA SCIENCE
IMPLEMENTATION.
WE DO THAT AS SHOWN THROUGH
SPECIFIC ROLES AND
RESPONSIBILITIES HERE ON THE
LEFT.
WE DO DEEP COLLABORATION WITH
ODSS AND CIT.
WE TRY TO ADVANCE AND SUPPORT
NIH'S STRATEGIC PLAN FOR DATA
SCIENCE.
WE HAVE OUR OWN DATA SCIENCE
PLANS AND STRATEGIC GOALS HERE
AT NLM THAT ARE COUPLED CLOSELY
TO THOSE, THEN WE HAVE
OPERATIONAL SERVICES AROUND
CURATION, STANDARDIZATION, AND
DOING RESEARCH.
WE'VE HEARD SEVERAL OF THESE
TODAY.
WE DEVELOP INFRASTRUCTURE.
WE HAVE KEY PARTNERSHIPS.
WE HELP DEVELOP RAS.
THIS CONCEPT OF AUTHORIZATION
AND APPROVAL FOR AC STOWS DATA
WILL BE TRANSFORMATIVE AND KEY
TO OPERATING FEDERATED DATA
SYSTEMS AROUND CONTROLLED ACCESS
DATA, WE NEED TO KNOW WHO PEOPLE
ARE, WHAT RIGHTS AND
RESPONSIBILITIES THEY HAVE USING
DATASETS.
RAS PROVIDES THAT, NOW BEING
ADOPTED BY I THINK NEARLY A
DOZEN SYSTEMS.
SO THE MORE WE CAN DO THAT
BECOMES LEGO BLOCKS, THE MORE WE
CAN BUILD THIS INTEROPERABLE
SYSTEM.
WE HAVE ROLES IN GOVERNANCE, WE
HELP DO POLICY DEVELOPMENT, BOTH
WITHIN NIH AND HHS, AND AS I
TRIED TO REVIEW WITH ARTIFICIAL
INTELLIGENCE THERE'S SO MUCH
WORK GOING ON HERE, WE'RE TRYING
TO BE KEY PARTNERS AND SHARE OUR
EXPERTISE WITH CIT IN THE NIH
COMMUNITY THROUGH THINGS LIKE
OFFICE HOURS AND COMMUNITY
PRACTICE.
THOSE ARE MY FEW REMARKS.
I'M A FEW MINUTES OVER.
APOLOGIES FOR THAT.
BUT I THINK WE'VE GOT A RICH
AMOUNT OF INFORMATION ON THE
TABLE TO SHARE, TO TAKE TO
DISCUSSION.
I'LL STOP THERE.
>> WE HAVE MR. SHAFER AND DR.
PORTILLO TO LEAD THE DISCUSSION.
>> THANK YOU FOR AN INTERESTING
PRESENTATION, WORKING CLOSELY
TOGETHER.
AT MY INSTITUTION WE'RE
CONCERNED ABOUT COST, NOT
CONVINCED OF UTILITY OF DATA
SHARING AND MANAGEMENT.
HOW CAN WE IMPROVE ROI?
>> MAYBE I CAN TAKE A STAB.
>> ANY ONE OF THE THREE OF YOU,
YEAH.
>> SO --
>> DO HOW DO WE GET THE SKEPTI?
>> ONE THING IS LOOK AT CORE
REPOSITORIES LIKE SRA, DATA
REDISTRIBUTION FOR A DECADE NOW.
ONE THING WE'VE OBSERVED OVER
THE LONG CYCLE OF FUNDING,
PERIODS OF LEAN AND RICH
FUNDING, WHEN FUNDING
OPPORTUNITIES ARE DIMINISHED
THROUGH FEDERAL -- CHANGES IN
FEDERAL PRIORITIES THERE'S A
SHIFT TO THE REUSE AND
INTERROGATION OF AVAILABLE DATA
THAT THE SCIENCE DOESN'T STOP
BUT IF PEOPLE DON'T HAVE THE
FUNDING TO GENERATE NEW
EXPERIMENTS THEY RECAST IT
LOOKING AT EXISTING DATASETS.
AND THAT'S ALSO AN OPPORTUNITY
FOR DEVELOPING INSTITUTIONS NOT
DEEPLY RESOURCED, AS WE HEARD
FROM DR. TABAK YESTERDAY, THEY
CAN JUMP IN AND IMMEDIATELY
START WORKING ON VALUABLE DATA
IN THEIR OWN QUESTIONS AND
PROBLEMS OF LOCAL PRIORITY
BECAUSE THE DATA IS AVAILABLE.
WHAT WE DON'T DO WELL IS
SHOWCASE THAT REUSE OF DATA.
WE LEAVE IT TO THE SUBMITTER TO
CITE THE DATASETS, AND THERE'S
PROBABLY MORE WE CAN DO TO SHOW
HOW DATASETS ARE BEING REUSED.
THAT'S IN A DOMAIN OF METRICS,
I'LL STOP THERE.
SUSAN OR SEAN, DO YOU HAVE OTHER
IDEAS?
>> YES, I COMPLETELY AGREE WITH
STEPHEN.
IT'S REALLY INSTANTIATED, MAKING
SURE THE DATA IS FINDSABLE,
CITEABLE, SO RESEARCHERS CAN --
[ INAUDIBLE ]
WE HAVE A LOT OF WORK TO DO IN
THIS SPACE.
THAT MIGHT BE SOMETHING WE CAN
ALSO -- [ INAUDIBLE ]
FUNDING OPPORTUNITIES IS ANOTHER
WAY TO HELP THE COMMUNITY, WE'RE
GOING TO CREATE IT, TO PUSH FOR
THAT.
>> IT'S A TOUGH QUESTION.
I THINK ON ONE SIDE YOU'VE GOT
INCENTIVES, PROMOTION AND
TENURE, IN THE I.C. WORLD MY
PERSPECTIVE WHEN WE PUT FORTH
TOOLS THAT WE OFTEN -- WE'LL SAY
IF YOU USE THIS IT'S LESS
EXPENSIVE TO MANAGE DATA OR LESS
EXPENSIVE TO DO SOMETHING WITH
DATA, IN PRACTICE THAT ALWAYS
HASN'T BEEN TRUE.
LOOK HOW EXPENSIVE THAT IS.
SOMETHING WE'RE AWARE OF.
STEVE IS AWARE OF.
SOMETHING WE'RE LOOKING AT
CLOSELY, CYBER INFRASTRUCTURE,
MUST BE EFFICIENT.
WE WANT IT TO BE -- YOU KNOW, TO
HELP MAKE, YOU KNOW, WE'RE
WORKING ON TRYING TO THINK ABOUT
WHY THAT MAY OR MAY NOT
ACTUALLY -- I WILL SAY, THIS MAY
NOT BE THE OFFICIAL VIEW OF THE
NIH, BUT BUILDINGS ARE
EXPENSIVE.
CLOUD SPACE IS EXPENSIVE,
GENERATING DATA IS EXPENSIVE.
MAYBE WE NEED THINK ABOUT I.T.
AND I.T. INFRASTRUCTURE, MORE
LIKE A FACILITY THAN DIRECT
COST.
I THINK THAT'S A LOT OF
OPPORTUNITIES TOO TO THINK ABOUT
BUSINESS OF RESEARCH, AND HOW WE
SUPPORT I.T. INFRASTRUCTURE AND
COMPUTE.
>> SO, MY MAJOR QUESTION IS THIS
WAS SPONSORED BY DR. MOONEY'S
PRESENTATION, COMING FROM THE
COMMUNITY I THINK ABOUT SMALL
CLINICS.
I THINK ABOUT HEALTH
DEPARTMENTS.
HOW DOES THIS GET TRANSLATED
DOWN TO THAT LEVEL?
HOW DOES THE SUPPORT --
EVERYBODY THAT'S BEING GENERATED
HERE, GET TRANSLATED TO THAT
LEVEL AND THE KIND OF SUPPORT
THAT THEY WOULD NEED?
>> SUSAN COULD BETTER ANSWER
SOMETHING, MY PREVIOUS TIME AT
THE UNIVERSITY OF WASHINGTON WE
WORKED A LOT WITH FQHCs AND
SMALL CLINICAL SITES, AND IT WAS
HARD.
IT WAS HARD TO GET RESEARCH INTO
THOSE ENVIRONMENTS.
THERE WAS OFTEN BARRIERS TO
IMPLEMENT.
AND ONCE WE RAN, IF THERE WAS
RESEARCH THAT WAS HAPPENING, OR
WE HAD AN AGREEMENT OF FUNDING,
WHATEVER, OFTENTIMES TECHNICAL
SKILLS WOULDN'T BE IN THAT SITE.
WE WOULD HAVE TO EMBED -- WE
WOULD EMBED PEOPLE UNDER HIPAA,
BUSINESS ASSOCIATES, DOING WORK
ON THAT.
HOW WE CAN HELP WORK WITH
SMALLER SITES AND A LOT OF
CHALLENGES AND BARRIERS TO, YOU
KNOW, TO DOING THAT.
I THINK IT'S REALLY IMPORTANT,
VENDORS PLAY A ROLE HERE, IN THE
OLD DAYS, THE MEDICAL RECORD WAS
ON THE PHONE, RIGHT?
CONSUMER HEALTH DATA, AN
INTERESTING THING TO TALK ABOUT
TOO.
BUT I REMEMBER -- I GOT MY
COVID-19 VACCINE, IN A
DRIVE-THROUGH CLINIC, A PARKING
LOT, MY WATCHED BUZZED ME AND
SAID YOU JUST GOT A VACCINE FOR
COVID.
WHOA, HOW DID THAT HAPPEN?
COMMUNITY HEALTH SUPPORT AND
PERFORMANCE.
>> YEAH, THAT'S WELL SAID.
ONE OF THE THINGS THAT WE'RE
DOING IS THE CARE NETWORK, DR.
BERTAGNOLLI, INITIATING, WORKED
WITH RURAL SITES, CLINICAL SITES
TO INSTANTIATE CLINICAL TRIALS,
ACROSS THE UNITED STATES.
WE'RE LOOK AT DATA AND I.C.
INFRASTRUCTURE NEEDED FOR
COMMUNITY.
THE RURAL COMMUNITIES
PARTICIPATED IN DATA SCIENCE.
THROUGH TRAININGS -- [ INAUDIBLE
]
"ALL OF US" TOO HELP
TRANSMISSION OF BIONETWORK, SO
THERE ARE THINGS WE CAN DO TO
INCENTIVIZE, PROVIDE TRADITIONAL
RESOURCES FOR THOSE SITES AND
FOR THOSE COMMUNITIES TO PULLEY
PARTICIPATE IN RESEARCH AND
STUDIES.
>> I WOULD SUGGEST, YOU KNOW,
THAT THIS, YOU KNOW, YOUR GROUP
TAKE ON A DEMONSTRATION PROJECT,
TAKING ON EITHER A RULE SETTING
OR FQHC TO SEE HOW THIS WOULD
REALLY TRANSLATE.
I THINK IT COULD BE A WIN-WIN
SITUATION BECAUSE WE'RE TALKING
ABOUT DATA PERHAPS COLLECTED AT
THE RURAL SITE THAT COULD BE
PART OF THE DATA SHARING, AT THE
SAME TIME THEY WOULD WIN BY THE
FACT OF, YOU KNOW, SOME
APPLICATIONS THEY DON'T HAVE.
>> I WOULD LOVE TO TALK ABOUT
SOME OF THE WORK WE'RE DOING CIT
AND A FEW OTHERS, ON EXACTLY
THAT.
[ INAUDIBLE ]
>> ANOTHER COMMENT, MANY YEARS
AGO I DID A TALK, FEDERAL HEALTH
CORPORATION, ORGANIZATION WITH
THE TRIBES OF ALASKA, THERE'S
LIKE 250 OF THEM.
SONG THAT I DIDN'T APPRECIATE
BEFORE I GAVE THAT TALK IS THAT
A LOT OF THE CHALLENGES THAT WE
DEAL WITH IN BIOMEDICAL RESEARCH
HAVE NO RELEVANCE TO THEM.
THE KINDS OF PROBLEMS THEY FACE
WAS THEY HAVE -- THEY HAVE
REGIONAL SITES.
THEY HAVE A PROBLEM, A PERSON
MAY OR MAY NOT BE A DOCTOR WHO
CAN USE THE PHONE AND WORK WITH
A PATIENT AND A KEY DECISION
THEY HAVE TO MAKE, GET THE
PATIENT TO THE HOSPITAL, AND
THOSE KINDS OF PROBLEMS THAT
THEY WERE LOOKING AT IN HEALTH
CARE WERE VERY DIFFERENT THAN
THE PROBLEMS WE'RE SOLVING IN
INFORMATICS, MAKES ME WONDER
WHETHER SPECIAL POPULATIONS WE
LOOK AT THAT HAVE TROUBLE
ACCESSING AREN'T ONE PROBLEM TO
SOLVE BUT MANY DIFFERENT
PROBLEMS TO SOLVE, ALL VERY
DIFFICULT AND DIFFERENT.
SOMETIMES IN RESEARCH OUR STUDY
SECTIONS LOOK AT IMPACT
STATEMENT SIGNIFICANCE,
DIABETES, THIS PERCENTAGE OF
POPULATION, HUGE, AND SOME OF
THESE PROBLEMS ARE SMALL AND
REALLY IMPORTANT TO ADDRESS.
AS RESEARCHERS, WE MIGHT THINK
ABOUT THAT, ABOUT THE CHALLENGES
THAT SOME POPULATIONS THAT ARE
ARE INACCESSIBLE TO RESEARCH
MIGHT HAVE VERY DIFFERENT
PROBLEMS TO SOLVE IN INFORMATICS
THAN WE DO.
>> I'LL OFFER ONE MORE IDEA
HERE.
THIS KIND OF FEEDBACK THAT SEAN
AND SUSAN ARE DESCRIBING MIGHT
BE AN OPPORTUNITY TO PILOT IN
OUR NATIONAL NETWORK WITH NODES
IN SOME RURAL AREAS.
I DON'T KNOW HOW CONSISTENTLY
ALIGNED THE NODE DISTRIBUTION IS
IN THE NATIONAL NETWORK.
BUT THE NETWORK IS OUTWARD BOUND
PUSHING OUT INFORMATION FROM NLM
BUT COULD BE USE AS A
PROBLEM-GATHERING TOOL.
LARRY TABAK YESTERDAY SAID AS
SEAN OBSERVED A LONG TAIL OF
PROBLEMS THAT YOU'RE SEEING IN
RURAL COMMUNITIES AND THERE'S
NOT ONE SOLUTION.
THERE'S MANY BUT HOW DO WE
CREATE A NETWORK TO GATHER THAT
IS SOMETHING TO LOOK AT AS WELL
BECAUSE WE'RE REIMAGINING THE
NEXT FIVE-YEAR PROGRAM FOR THE
NATIONAL NETWORK.
>> THE PROBLEM, THAT PROBLEM IS
VERY SIMILAR TO A LOT OF THE
MILITARY PROBLEMS.
SOME DON'T HAVE -- [ INAUDIBLE
].
A LOT OF SMALL POPULATIONS IN
AGGREGATE DO ROLL UP TO A
CERTAIN SET OF PROBLEMS, ALSO
HAVING LIVED ON GUAM FOR TWO
YEARS, IT'S ONE PIXEL ON A MAP.
BUT THOSE PROBLEMS, THEY REALLY
DON'T WORK WELL, THE CLASS OF
PROBLEMS THAT PEOPLE IN LARGE
METROPOLITAN AREAS, OKAY?
ANYBODY HERE LIVE OUTSIDE A
LARGE METROPOLITAN ZIP CODE?
CRICKETS.
THAT MIGHT BE A REPRESENTATION.
>> EXCELLENT.
FIRST OF ALL, WONDERFUL
PRESENTATION, ALL THREE, A REAL
TOUR DE FORCE, KUDOS FOR THE
ACTIVITY.
RESEARCHERS MOVED TO TRYING TO
REUSE DATA I FIND RELUCTANCE TO
GET THEIR HANDS DIRTY WITH
UNDERSTANDING THE MEANING OF THE
DATA, METADATA, PROVENANCE OF
THE DATA, AND INSTEAD OF RELYING
ON ANALYSTS WHO CAN WORK WITH
DATA AND TURN IT INTO THE
SPREADSHEET THEY WANT, AND
THERE'S OFTEN A DISCONNECT
BETWEEN WHAT THE ANALYSTS
UNDERSTAND IS A RESEARCH
QUESTION, AND WHAT THE
RESEARCHERS THINK THE ANALYSTS
ARE GIVING THEM.
IT'S OFTEN UNRECOGNIZED
DISCONNECT.
WE HAVE ENOUGH DATA SOMETIMES IT
BECOMES NOISE.
NOW MOVING TO THIS IDEA OF THE
ENCLAVE, WHEN WE'RE MOVING AND
EXPECTING A RESEARCHER TO GET IN
THERE THEMSELVES NOT ONLY
EXTRACT AND DEAL WITH DATA BUT
ANALYZE IT, IN AN ENVIRONMENT
THAT MAY NOT BE FAMILIAR TO
THEM, WONDERING WHAT YOU'RE
DOING TO TRY TO HELP GET THE
RESEARCHERS TO OVERCOME THAT,
YOU KNOW, ENERGY HUMP.
THERE'S SMART PEOPLE, THEY
LEARNED A LOT, THEY CAN LEARN
HOW TO DO THIS BUT I FIND
RESISTANCE TO MOVING OUT OF THE
COMFORT ZONE AND GETTING IN AND
WORKING THAT, TRUE HERE AT NIH
WITH INTRAMURAL RESEARCHERS,
TRUE AT UAB, AND I'LL BET IT'S
TRUE IN A LOT OF PLACES.
HAVE YOU THOUGHT ABOUT HOW
YOU'RE GOING TO HELP PEOPLE,
YOU'RE PUTTING THINGS OUT THERE
FOR THEM, HOW ARE YOU GOING TO
GET THEM OVER THAT HUMP TO GET
THEM WORKING WITH IT?
>>> AND LET ME SAY, I GAVE AWAY
A THOUSAND DOLLAR PRIZE FOR
PEOPLE ALL THEY HAD TO DO WAS
DOWNLOAD SOME DATA AND WRITE A
ONE-PAGE ABSTRACT, I GAVE AWAY
THREE PRIZES, I GOT THREE
APPLICATIONS.
SO EVERYBODY WON.
EVERYBODY'S A WINNER.
EXCEPT ME, I COULDN'T GET
PEOPLE -- ALL YOU HAD TO DO WAS
GO IN i2b2 AND WRITE A
ONE-PAGE ABSTRACT, COULDN'T GET
PEOPLE TO MAKE THAT EFFORT.
>> I THINK OUR GOAL IS TO
UNDERSTAND THE SCIENTIFIC
COMMUNITY, EVERYBODY HAS THEIR
OWN TOOLS, JUPYTER NOTEBOOK, PIE
PYTHON, SOME USE GALAXY.
THE BEST IS UNDERSTAND WHAT THE
PLATFORMS ARE THEY USE AND
PROVIDE IT TO THEM TO MAKE IT
SEAMLESS TO GO INTO AN ENCLAVE
ENVIRONMENT.
>> (INAUDIBLE) PEOPLE LIKE
YOU'RE DESCRIBING, ANALYSTS,
RESEARCHERS, MAYBE RESEARCHERS,
TO DEVELOP SOFTWARE THAT WILL
HELP ALLEVIATE THAT PROBLEM,
IT'S REALLY BRINGING TOGETHER TO
THE ACADEMIC SOFTWARE
(INAUDIBLE) TO THINK ABOUT
SOFTWARE DESIGN.
SO THIS IS A GREAT PROGRAM TO
START TO ADDRESS THAT PROBLEM.
(INAUDIBLE) COMMUNITY DRIVEN,
HAS A LOT OF IDEAS, MODULARITY,
THE OTHER PROBLEM, NIH WORKING
GROUP, IDeA STATE, RESEARCHER,
SOFTWARE, AWARDS WERE RESEARCH
ENGINEER, P.I., SALARY, TRAVEL,
CAREERS, TO HELP THEM TRANSITION
TO WHAT MIGHT BE MORE R01, IT'S
REALLY A PROGRAM TO SUPPORT
P.I.s THEMSELVES WHO WOULD NOT
BE SUPPORTED, (INAUDIBLE).
YEAH, SO THIS IS TWO AREAS WE
REALLY HAVE TO RECKON WITH,
WE'RE TRYING TO SOLVE IT.
DATA REUSE, PRIZE CHALLENGING.
>> WE HAVE A SIMILAR ISSUE IN
DoD WITH DATA, IT'S NOT -- I'M
SURE WE HAVE IT ON THE RESEARCH
SIDE, BUT JUST ON THE
OPERATIONAL SIDE I'M INVOLVED
WITH THREE SERVICES, DIFFERENT
DATA, I'M 100% CERTAIN THAT THE
WAY THEY FILL THEIR DATA IS 100%
ACCURATE FOR THE WAY THEY FILL
THEIR DATA, 100% WHEN THE DATA
IS PUT TOGETHER AND THEY ROLL IT
INTO SOMETHING USED AT MOST
SENIOR PART OF THE UNITED STATES
GOVERNMENT FOR DECISIONS ON
OPERATIONAL ISSUES THAT IT'S NOT
100% ACCURATE TO THE WAY IT'S
GOING TO BE INTERPRETED.
AND SO I ACTUALLY HAVE A COLONEL
RIGHT NOW WORKING ON THIS FOR ME
TO LOOK INTO THAT DATA, HOW ARE
WE GOING TO BE IDENTIFYING THAT
DATA, AND HOW ARE WE MAKING SURE
THAT IT'S CONSISTENTLY APPLIED
WITH INCONSISTENT MECHANISMS
FROM DIFFERENT SERVICES.
ONE OF THE WAYS WE TALK ABOUT
INTERNALLY WITH MY GROUP IS PART
IS THE DOCUMENTATION OF THE
ASSUMPTIONS HOW THE DATA IS
POLLED.
I DON'T KNOW IF THAT'S HAPPENS
ON THE RESEARCH SIDE BECAUSE I'M
NOT A RESEARCHER THE ASSUMPTION
OF HOW THE DATA IS POLLED
DOESN'T FLOW WITH THE DATA AS
YOU CONSOLIDATE INTO LARGE
DATABASES.
THEREFORE EVEN IF YOU DID ROLL
UP YOUR HANDS AND GET DIRTY TO
WRITE A PAPER YOU HAVE NOTHING
TO WRITE ABOUT BECAUSE YOU DON'T
KNOW THE UNDERLYING ASSUMPTION.
THE WAY THE ARMY MIGHT COUNT
PEOPLE, THE WAY THE NAVY MIGHT
COUNT, THE WAY I MIGHT COUNT
PEOPLE IN A PERSONNEL DATABASE
WILL BE TOTALLY DEAF DIFFERENT
THAN THE WAY YOU'LL ASSUME IT
WAS COUNTED AS THE RESEARCHER
PUT IT TOGETHER.
I WANTED TO THROW THAT OUT.
WE HAVE DR. KATZ AND I THINK
WE'RE OVER TIME.
SOUNDS LIKE THERE'S A NEED FOR
SOCIAL TECHNICAL EMBEDDING,
PEOPLE UNDERSTANDING THAT PART
OF IT.
>> I WANTED TO BUILD ON WHAT
CARMEN WAS TALKING ABOUT.
IT'S NOT JUST THE FQHCs, THE
PURPOSE OF ALL OF WHAT WE'RE
DOING IS TO IMPROVE THE QUALITY
OF HEALTH CARE THAT PEOPLE ARE
RECEIVING.
AND WHILE DATA SCIENCE HAS MADE
TREMENDOUS -- SORT OF AMAZING,
YOU KNOW, MOVES FORWARD MOST
CLINICAL INTERACTIONS ARE STILL
A DOCTOR, A NURSE, P.A., IN A
ROOM WITH PATIENTS.
AND I MEAN I THINK THAT
PubMed IS EXAMPLE OF A
REALLY SUCCESSFUL NLM PRODUCT
THAT IS ACTUALLY USED.
IT'S PROBABLY NOT USED AS MUCH
AS IT SHOULD BE USED.
I WOULD GUESS WE'RE STILL 80%
CLINICAL DECISIONS MADE WITHOUT
ANYBODY CONSULTINGYBG.
BUT I THINK PubMed IS AN
INCREDIBLE SUCCESS BECAUSE IT
ALLOWS A CLINICIAN TO FIND THE
BEST EVIDENCE AND IT'S FREE, YU
DON'T NEED A SUBSCRIPTION.
CHALLENGE IN THE NEXT PHASE, TO
SAY, OKAY, HOW DOES THIS
TRANSLATE TO THE WORK THAT
NURSES AND DOCTORS AND OTHERS
ARE DOING IN CLINICS AND
HOSPITALS, WHETHER IN A RULE OR
METRO AREA, HOW DOES THIS HELP?
AGAIN, ALWAYS GOING TO BE A
LACK.
THAT'S OKAY.
SCIENCE GOES FIRST.
BUT AT LEAST AS A CLINICIAN
LISTENING TO THE DATA IT FEELS
LIKE A VERY LARGE GAP BETWEEN
WHAT WE'RE TALKING ABOUT AND HOW
I WOULD IMAGINE APPLYING
ANYTHING TO THE PATIENTS I SEE.
AND I'M NOT -- I THINK IT'S
WORTH THINKING ABOUT, YOU KNOW,
WHAT IS OVER THE NEXT FIVE TO
TEN YEARS AS THE DATA WORK GOES
FORWARD, HOW ARE THE WAYS THAT
WORK IS GOING TO AFFECT THE WAY
DOCTORS AND NURSES AND OTHER
HEALTH CARE PROFESSIONALS TAKE
CARE OF PATIENTS.
IF WE DON'T ACHIEVE THAT, THEN,
YOU KNOW, THIS IS JUST ABSTRACT
SCIENCE FOR THE SAKE OF SCIENCE,
NOT REALLY WHAT NIH OR NLM IS
SUPPOSED TO BE.
>> IF I COULD DO A QUICK IDEA
AND REMARK, IT'S NOT A COMPLETE
ANSWER, BUT ONE OF THE THINGS IS
HOW DO WE GET RELATE WORLD
HEALTH OUTCOME DATA FROM
SOMETHING LIKE DRUG ADVERSE
EVENTS, WE'RE DOSING POPULAR
DRUGS, MILLIONS OF TIMES A DAY
ACROSS THE COUNTRY.
THERE'S NATURAL EXPERIMENTS
RUNNING.
FDA DOES NOT GET THAT DATA BACK
AFTER PHASE 3 APPROVAL.
IS THERE SOMETHING WE CAN DO TO
FACILITATE AGGREGATION AND
ANALYSIS AT A POPULATION LEVEL,
YOU KNOW, INCLUDING
REPRESENTATIVE MINORITIES ABOUT
HOW DRUGS ARE WORKING AND ARE
THERE CAUTIONS OR ADVERSE EVENTS
WE NEED TO TRACK FOR SAFETY AND
EFFICACY.
THAT'S JUST AN EXAMPLE TRYING TO
FIGURE OUT HOW DO WE USE DATA
BEING GENERATED AND CAPTURED
PASSIVELY BACK INTO THIS SYSTEM
WHERE IT COULD BE REINTERPRETED
FOR VALUE-ADDED ANALYSIS AND
DECISION MAKING.
I DON'T KNOW IF THERE'S OTHER
DIRECT ANALOGS OF PubMed.
LAST THING I'LL OFFER, IT'S USED
A LOT IN MEDICINE, ONE OF THE
FEW RESOURCES THAT HAS CLEARANCE
TO RETURN DURING A SHUTDOWN
BECAUSE IT'S USED TO INFORM
SURGERIES.
SO I KNOW IT'S USED A LOT, AND
WHEN IT'S TURNED OFF IT'S A
CRISIS.
>> IT'S A HUGE SUCCESS.
>> THANK YOU.
>> I WAS INTRIGUED BY THE
ECOSYSTEM OF MODELS.
AND ALSO WE TALKED ABOUT
UTILITY, VALUE, ROI.
BUT I WAS INTRIGUED ABOUT THE
DATA-TO-KNOWLEDGE, BUT FROM THE
PUBLIC PERSPECTIVE NOT
NECESSARILY RESEARCH
PERSPECTIVE, BECAUSE
INTERACTIONS WITH ADVANCED
PRACTICE NURSES, COMMUNITY
NURSES, COMMUNITY PHYSICIANS, MY
WIFE'S PERSONAL LIBRARIAN
BECAUSE OF HER COMORBIDITIES AND
DISABILITIES, BUT TRYING TO FIND
OUT IF THERE'S ROADMAP FOR A
MORE PUBLIC-FACING -- HOW DOES
THE TAXPAYER GET THAT VALUE AS
WELL?
BEYOND PubMed YOU'VE GOT
RICHNESS OF DATA, ET CETERA.
WHAT HAS HELPED WITH MY WIFE AND
THE FEW PHYSICIANS WHO WOULD
LISTEN TO INFORMED PATIENTS,
THAT PubMed AND THE CASE
STUDIES GIVES ME THAT HOLISTIC
PERSON, AS OPPOSED TO
SPECIALTIES.
I CAN GO TO THE SPECIALTIES BUT
I COME WITH A HOLISTIC
PERSPECTIVE BECAUSE THE
LITERATURE AS WELL AS OTHER
RESOURCES HAVE GIVEN ME THAT
TOTALITY.
ESPECIALLY THE VALUE OF CASE
STUDIES BECAUSE YOU GET THAT
WHOLE PATIENT.
SO, I WOULD REALLY CHALLENGE
YOU, I THINK YOU'VE GOT THE
TOOLS, THE MINDSET, BUT THE SOME
POINT WE'VE GOT TO SELL THINKING
ABOUT THE LOST PATIENT OUT THERE
WHO KNOW WHAT IS THEY ARE GOING
TO GET IN THIS WORLD, BUT I
THINK ABOUT WHETHER IT'S A SMALL
MODEL, OPEN A.I., WHATEVER,
BECAUSE I KNOW THERE'S A COST
INVOLVED, BUT SOMEHOW, SOME WAY,
THINKING ABOUT THIS FOR THE
PUBLIC AS WELL, AND IT'S NOT
JUST THE PATIENT BUT IT'S ALSO
THAT PROVIDER WHO DOES NOT HAVE
THE LIBRARY WITH THE $5 MILLION
BUDGET BUT THERE'S STILL A LOT
OF PEOPLE OUT THERE STRUGGLING
AND SUFFERING WITH INFORMATION
OVERLOAD BUT AT THE SAME TIME
INFORMATION DESERT.
AND THIS IS I THINK -- THIS ALSO
GOES TO MY GLOBAL HEALTH WORK IN
LIBERIA, SAME THING.
NOT THAT YOU'RE PROVIDING VALUE
FOR THE NON-TAXPAYERS BUT THERE
IS AN TREATMENT VALUE TO THE
GLOBAL WORLD AS WELL WITH THE
NIH RESOURCES.
SO THANK YOU.
>> WE'LL TAKE ONE LAST BEFORE
BREAK, WE'LL COME BACK WITH A
SHORTER BREAK.
>> DO YOU WANT MY QUESTION TO
COME AFTER THE BREAK?
>> YES, ACTUALLY.
>> OKAY.
>> WE'LL GET BACK AT 10:40.
>> YESTERDAY WE HEARD FROM LARRY
TABAK ABOUT SOMETHING WE'VE BEEN
THINKING A FAIR BIT ABOUT,
CREATING A PORTFOLIO, WE'VE DONE
THAT WITH EDUCATIONAL,
CONVENTIONAL PORTFOLIO IN
EDUCATION IS ENTREPRENEURIAL, HE
COMMENTED ON THE NEED TO SEND US
DATA, MAKE DATASETS AVAILABLE TO
US, SO ON.
TODAY WE HEARD ABOUT A VARIETY
OF DATA SHARING OPPORTUNITIES,
SO WHAT IS EMERGING TO ME, I MAY
ADMIT THIS, WHAT ARE THE
STRATEGIES AND OPERATIONAL PLANS
FOR ROLLING OUT STRATEGIES
STANDARDIZING WAYS WHICH WE
REPORT DATASETS, ARTICLES,
PROMOTIONS COMMITTEE.
I WOULD LOVE TO MAKE A
COLLABORATION PORTFOLIO
SOMETHING THAT I CAN TAKE TO
INSTITUTIONS BUT I DON'T KNOW
THE STANDARDS, SO I REALLY THINK
THERE NEEDS TO BE A STRATEGY,
AND SOME WAY OF COMMUNICATING
ENOUGH SO WE CAN MAKE THIS A BIT
MORE REAL AS OPPOSED TO JUST
DISCUSSING THE POSSIBILITY OF
COLLABORATION IN THE PORTFOLIOS.
>> SO, I HEAR YOU.
I DON'T HAVE A STRATEGY, AND I'M
NOT AWARE OF, MAYBE I'LL TURN TO
SUSAN TO KNOW IF THERE'S
ANYTHING AT THE NIH LEVEL THAT'S
FORMAL, BUT I WOULD ADD TO THAT,
NOT JUST COLLABORATION BUT DATA
SUBMISSION, AND IT'S ADJACENT TO
THAT BUT I THINK THIS IS WHERE
WE REALLY NEED TO FIGURE OUT HOW
TO REPORT ON SUBMISSION VALUE.
WE COULD DO THIS FOR SOME LEVEL
OF SUBMITTERS BUT I THINK THE
COMMUNITY AND BROADLY NEEDS SOME
STANDARDS, WHO GETS CREDIT, YOU
KNOW, HOW DO WE COUNT USAGE, HOW
DO WE COUNT SUBMISSIONS,
ESPECIALLY IN LARGE
INTERNATIONAL AND MULTI-CENTER
PROJECTS.
INCREASINGLY HAVE SOMETHING THAT
COMES IN, LIKE 100 AUTHORS ON
THE PAPER, ARE THEY ALL ATTACHED
TO THE DATA, IS IT JUST
PARTICULAR TEAMS?
THERE'S STILL SOME QUESTIONS OR
ISSUES TO PILOT, AND THEN HOW DO
WE GET THAT ATTACHED TO
IDENTITIES.
THERE'S A GENERAL PROBLEM RIGHT
NOW AROUND IDENTITY MANAGEMENT
AND PUBLISHING, THAT'S COMING UP
AROUND CHANGES IN SURNAMES,
AROUND AUTHOR IDENTIFICATIONS,
THINGS LIKE ORCID I.D. WHEN THEY
ARE NOT PART OF THE INITIAL
CONSTRUCTION OF THE MANUSCRIPT,
NLM IS PARTY TO THAT BUT WE
CAN'T SOLVE THE PROBLEM.
I DON'T WANT TO BUILD A SHADOW
SYSTEM ATTACHING COLLABORATIONS
AND METADATA OUTSIDE THE
OFFICIAL RECORD.
IT NEEDS TO BE A PARTNER TO
PUBLISHER ALIAS, AKAs,
ATTACHED.
BETWEEN ORCHID I.D.s,
SUBMITTER NAMES AND DATA.
I'LL TURN TO SUSAN.
>> WE'RE REQUIRING ORCID IDs
IN GRANT APPLICATIONS, I CAN SEE
WE NEED ADDITIONAL TECHNOLOGIES
AND TOOLS TO HELP LINK WHAT'S
COMING FROM THE DATA MANAGEMENT
SHARING PLANS, WE HAVE SOME
RESOURCES WITH NLM AND OTHERS.
THIS MIGHT BE A GREAT
APPLICATION FOR OPPORTUNITY AND
RESEARCH DEVELOPMENT.
EXACTLY AS STEVE SAID, WE REALLY
NEED TO UNDERSTAND WHEN
RESEARCHERS -- HOW IT'S
CONTRIBUTING BACK TO THEIR DATA
SHARING PLANS IN WAYS WE CAN
HELP TRACK THAT, THAT COULD
INSTANTIATING BETTER METADATA.
WE'VE PILOTED THIS WITH THE
BRAIN TO SOME EXTENT BUT I THINK
THIS IS REALLY NEEDED AND IT'S A
GREAT ROLE FOR NLM AND FOR NIH
TO DEVELOP TECHNOLOGIES.
SO WE'RE NOT THERE YET.
LOVE YOUR IDEAS.
I'VE LOVE TO SEE WHAT WE CAN DO
TO HELP INSTANTIATE THAT.
>> I WAS THINKING ABOUT
SOMETHING QUITE SIMPLE,
CONCEPTUALLY.
STANDARDS AROUND DATASET,
IDENTIFICATION, SO EVERYBODY IT
COULD BE A DOI FOR EXAMPLE BUT
THAT BECOMES A STANDARD LIKE A
CLINICAL TRIALS IDENTIFIER FOR
DATASETS, A LOT OF THE DIVERSITY
HOW COLLABORATION PROPOSES BUT
WE DON'T EVEN HAVE THAT.
AND SO I DON'T KNOW HOW TO TAKE
THIS CONCEPT TO UNIVERSITIES.
IT FEELS LIKE NLM AND NIH SHOULD
BE AT LEADERSHIP HELM.
>> I DON'T KNOW IF DIANNE BABSKI
IN THE ROOM BUT WE HAVE A
METADATA MODEL FOR DESCRIBING
DATASETS, GIVING SOME
RUDIMENTARY ATTRIBUTION, MEANT
TO BE A MINIMAL SET SO I DON'T
KNOW IT WILL IF ALL OF
COMPLEXITY NEEDED.
IT COULD BE EVALUATED, FEEDBACK
BUTTON OR DIRECTLY TO DIANA OR
OTHERS FROM THE LIBRARY AROUND
ITS SUITABILITY OR DEFICIENCIES.
IF WE'RE TRYING TO UNDERSTAND
HOW TO ADVANCE THAT VERY PROBLEM
HOW DO WE DESCRIBE DATASETS IN A
CATALOG TYPE OF WAY THAT COULD
WORK INTERNATIONALLY.
>> ALL RIGHT.
SO WE HAVE DEVELOPED THE DATASET
CATALOG.
OUR PRODUCT DONOR IS RIGHT HERE.
I SHOULD PASS THE MIC OVER TO
HIM.
ONE OF THE THINGS WE DID DO WAS
TO CREATE A -- THE EQUIVALENT OF
JOURNAL ARTICLE TAGS THAT BECAME
THE STANDARD FOR PUBLISHING,
WHAT DESCRIBES A CITATION.
AND SO WE DID THE SAME THING
WITH OUR DATA MODEL.
WHAT IS THE MINIMUM CRITERIA FOR
DESCRIBING A DATASET AND BEING
ABLE TO POINT BACK OR LINK OUT
TO IT AS WELL.
DOIs ARE INCLUDED IN THOSE AS
WELL, AND THE MODEL IS VERY
ROBUST, SO THAT YOU CAN TAKE IT,
USE IT IN YOUR OWN ENVIRONMENT,
EXTEND IT, AND MAKE IT WORK IN
WHATEVER CAPACITY THAT YOU NEED.
WE WORKED WITH W-3C, AND SOME
OTHER ORGANIZATIONS, AND WE HAVE
A COUPLE OTHER INSTANCES WHERE
THAT MODEL HAS BEEN IMPLEMENTED.
I CAN'T REMEMBER THE UNIVERSITY.
HELP ME OUT.
>> AGREEMENT WITH UNIVERSITIES.
>> RIGHT.
>> (INAUDIBLE).
>> RIGHT.
SO REALLY THE GOAL OF THIS IS TO
TURN THIS DATASET CATALOG INTO A
PubMed, IF YOU WILL,
REFINING DATASETS.
THEY DON'T HAVE TO SEARCH ACROSS
17 REPOSITORIES, AND KNOW WHERE
A UNIVERSITY REPOSITORY IS.
THEY SHOULD BE ABLE TO PULL IT
IN TOGETHER.
AND SO THAT IS A KEY THING.
WE KNEW THAT WAS GOING TO COME
UP, ESPECIALLY WITH THE SHARING
PLANS, EVERYONE IS RECEPTIVE,
SOMETHING PROOF OF CONCEPT IN
OUR DATA, RIGHT NOW, AND TRYING
TO SEE HOW THAT WORKS.
AND IF YOU HAVEN'T TRIED IT YET,
I'M GOING SHAMEFULLY PLUG IT.
CHECK IT OUT.
GIVE US FEEDBACK.
IT'S IN AN NPT RIGHT NOW.
WE'RE IN THE PROCESS OF DOING
ASSESSMENT STEVE TALKED ABOUT
YESTERDAY TO THINK ABOUT WHERE
WE'RE GOING WITH THIS NEXT AND
WHAT DO WE NEED TO WORK ON
FIRST, AND OUR LONG RANGE PLAN.
>> LET ME ASK A FOLLOW-ON.
SO, WITHIN THE DATA -- SO YOU'LL
HAVE BASICALLY INFORMATION
ABOUT, YOU KNOW, DATASETS, WILL
IT ALSO INCLUDE THE DIFFERENT
USES OF THAT DATASET?
THAT COULD GET TO THE
COLLABORATION TALKING ABOUT SO
YOU CREATE PubMed SOURCES
LIKE USED IN ALL THESE WAYS, I
CAN PUT THAT ON MY CV.
>> THAT'S A FUTURE GOAL.
THE GOAL IS JUST WITH ALL OF OUR
DATA, HOW DO WE CREATE THOSE
LINKAGES FROM ONE SYSTEM TO THE
OTHER?
SO IF YOU'RE IN PubMed, YOU
CAN SEE ASSOCIATED DATASETS, SO
THE GOAL TO HAVE THE WHOLE WEB
OF FINDABILITY AND
DISCOVERABILITY, BUT I'M HOPE
YOU'RE TAKING NOTES OF SOME OF
THIS, STEVE.
>> WE BUILT IT AS A SEMANTIC
DATA MODEL TO DO EXACTLY WHAT
YOU'RE DESCRIBING.
(INAUDIBLE).
>> IF YOU HAD ANYTHING ELSE TO
ADD?
>> THIS IS REALLY GREAT.
THE MORE WE CAN WORK WITH DATA,
THE DATA NLM IS DOING, COMMUNITY
EFFORTS, WE CAN WORK WITH NLM
AND OTHER COMMUNITY EFFORTS SUCH
AS WHAT'S HAPPENING WITH DATA
CITE TO INSTANTIATE THIS CONCEPT
OF THE SCHEMA, THERE'S A LOT OF
ACTIVITIES IN THIS AREA,
DIFFERENT COMMUNITIES, WHICH
REALLY PROMOTES THE BROAD SCALE
DISCOVERABILITY.
NSF FUNDED SOMETHING CALLED THE
PROTOOPEN KNOWLEDGE NETWORK, A
KNOWLEDGE GRAPH ACROSS ALL
SCIENCE, MANY AGENCIES ARE
PARTICIPATING WITH NSF.
WE ARE FOR THE BIOMEDICAL
KNOWLEDGE GRAPH.
I THINK THERE'S OPPORTUNITIES
HERE TO START TO INTEGRATE THE
SCHEMAS ACROSS -- SCHEMA OF
SCHEMAS, AND THERE'S SOME REALLY
INTERESTING WORK IN NLM, THIS IS
WHERE THE FUTURE IS, SO WHAT I
SEE IS WE PROBABLY HAVE TO
UPSCALE THE DATA MODEL QUITE A
BIT TO MAKE SURE IT SCALES
ACROSS OUR DATA REPOSITORIES AND
RESOURCES.
>> I'LL PUT YOU ON THE SPOT
ABOUT MAYBE WHAT THE NSF IS
DOING.
>> ACTUALLY, SHE JUST GAVE THE
BIGGEST PLUG.
>> OH.
>> FOR THE THING THAT WE'RE
DOING.
WE'VE HAD DATA MANAGEMENT PLANS
ACTUALLY BEFORE NIH DID.
>> OH.
I DID NOT KNOW THAT.
OKAY.
>> I WAS GOING TO CALL FOR --
THERE MIGHT BE SOME UTILITY IN
BIOSURVEILLANCE SPACE, BUT
THERE'S A CHIEF DATA A.I.
OFFICE, THEY HAVE A VERY SIMILAR
PROBLEM SET, AND IT'S A SUPER
SET OF MEDICAL DATA.
SO WE HAVE MEDICAL DATA AND THEN
ALL SORTS OF OTHER DATA, WHERE
THAT PERSON WENT, SICK, LOTS AND
LOTS AND LOTS OF DIFFERENT
DATASETS, THEY DEVELOPED AND
HAVE THIS UTILITY ACROSS THE
WORLD REALLY, PEOPLE WHO SOLVED
THE SCHEMA OF SEEMA PROBLEMS.
>> DR. SHERRY, IT'S GOOD TO SEE
YOU.
AND WHAT CAPTAIN OLSON WAS JUST
REFERRING TO ACTUALLY THE THREE
OF US ON THE SERVICES SIDE HAVE
BEEN TALKING ABOUT THIS.
IF YOU'RE INTERESTED, I'D BE
HAPPY TO HELP FACILITATE A
MEETING TO HELP SHARE SOME OF
YOUR RESOURCES AND YOURS AS
WELL, SUSAN, WITH SOME OF OUR
RESEARCHERS AND SOME OF OUR DATA
FOLKS BECAUSE I'M NOT SURE THAT
WE FULLY APPRECIATE THE SCOPE
AND LEVEL OF SOME OF THE
RESOURCES THAT YOU AND YOUR TEAM
HAVE, AND SO YOU CAN REACH OUT
TO ME AFTERWARDS AND YOU GOT MY
INFORMATION, BUT I WANT TO THROW
THAT OUT THERE, AS AN OFFER THAT
I'M GLAD TO FACILITATE THAT WITH
THE ARMY AND THE NAVY FOR A
FOLLOW-ON DISCUSSION IF YOU
DESIRE.
>> ABSOLUTELY.
THANK YOU SO MUCH.
AND DEFINITELY WE'LL BE IN TOUCH
TO FOLLOW UP ON THAT.
THERE'S WISDOM AROUND THE WORLD
IN DIFFERENT PARTS OF THE
GOVERNMENT ON THIS, AND I DON'T
THINK ANYONE HAS A LOCK ON THE
PROBLEM.
I DON'T KNOW THAT WE HAVE A
COMPLETE SET OF REQUIREMENTS SO
JUST LEARNING WHAT OTHERS ARE
DOING, THE WHOLE SET OF
CHALLENGES WOULD BE GREAT TO
HAVE A COMMUNITY PRESENCE IN
THIS SPACE.
THE OTHER THING, I DON'T KNOW IF
YOU SHARED THIS AT THE TABLE,
ISSUE I
COULDN'T HEAR IT.
DO WE HAVE ACADEMIC PARTNERS,
CIRCLING BACK TO PROMOTION AND
TENURE PROBLEM, IS THERE AN
ORGANIZATION WE CAN PARTNER
WITH, TO SERVE UP INFORMATION IN
A WAY THAT'S ACTIONABLE AND
USABLE TO THE COMMITTEES?
I DON'T HAVE A PARTNER IN MIND
AND WONDERING IF YOU KNOW OR
HAVE INSTITUTIONS THAT ARE
LOOKENING TO BE LEADERS IN THIS
SPACE.
>> I WAS GOING SAY (INAUDIBLE)
HAS BEEN DISCUSSING THERE'S A
ROUNDTABLE UNDER THE --
SPECIFICALLY ON INCENTIVES.
>> DOES SOMEBODY HAVE THE RIGHT
PEOPLE AT THE TABLE FROM THE
ACADEMIC INSTITUTIONS WHO WOULD
CHAMPION THIS AND HAVE PILOTED
TO SOME EXTENT, YES.
>> AND THERE'S ALSO THE NATIONAL
ACADEMIES, BECAUSE I'M SURE --
>> YEAH.
>> THAT'S THE ROUNDTABLE.
>> EX OFFICIO NOW.
>> WHO IS AU?
>> AAU AND APLU.
>> AMERICAN ACADEMY OF
UNIVERSITIES.
>> OH, OKAY.
>> THE OTHER ONE IS INSURE
(INAUDIBLE).
>> OTHER QUESTIONS, SUGGESTIONS?
>> SO, IT'S VERY EXCITING TO SEE
THE A.I. PROJECTS, AND COMING
FROM A HEALTH PROFESSION
BACKGROUND, BY THE WAY THIS IS
(INAUDIBLE) SO I'M CURIOUS ABOUT
A LOT OF THESE ARE RELATED TO
ACTION, EDUCATION, A.I. LEADERS.
SO, I'M JUST CURIOUS WHAT ARE
SOME OF THE, YOU KNOW,
RESOURCES, MORE TANGIBLE
RESOURCES, TRAINING PROGRAMS
INITIATIVES OR FUNDING
OPPORTUNITIES THAT NOW PROVIDE
OR IN PARTNERSHIP WITH ACADEMIC
INSTITUTIONS, WITH THE GOAL TO
ENHANCE RESEARCHERS, MEDICAL
STUDENTS, A.I. LEADERS TO HELP
LIKE MORE EFFECTIVELY LEVERAGE
THE USE OF A.I. IN LIKE
DIFFERENT STAGES OF RESEARCH IN
CLINICAL DECISION MAKING.
>> SO NIH HAS THE AIM AHEAD
PROGRAM, AND PRECISION A.I.
BRIDGE TO A.I. RATHER, A COMMON
FUND PROJECT.
NLM SUPPORTS INDIRECTLY.
WE'RE NOT LEAD I.C.s ON EITHER
OF THE PROJECTS.
A LOT OF THE WORK WE'RE DOING AS
AN INSTITUTE IS AROUND THE
OPERATIONAL APPLICATIONS OF A.I.
TRYING TO UNDERSTAND HOW DO YOU
INSERT THE RISK MITIGATION
FRAMEWORK CENTERED RESEARCH AND
DEVELOPMENT.
WE DO THAT IN OUR INTRAMURAL
PROGRAM, AND INTEROPERATIONAL
DIVISIONS LISTER HILL, USER
SERVICES COLLECTION DIVISION,
NCBI.
SUSAN, DO YOU WANT TO SPEAK TO
AIM AHEAD?
I THINK THAT'S ONE OF OUR
OFFICE'S PROGRAMS, RIGHT?
>> YEAH, AIM AHEAD IS A.I.
MACHINE LEARNING CONSORTIUM TO
ADVANCE THE REPRESENTATION OF
UNDERSERVED POPULATIONS AND
RESEARCHERS IN THE CONSTRUCTION
OF A.I. DATA AND ALGORITHMS, AS
WELL AS EMPLOYMENT OF THOSE
COMMUNITIES.
IT GOES ON WHAT'S CALLED
CO-DESIGN APPROACH WHICH MEANS
YOU DEVELOP THE ALGORITHMS WITH
THE COMMUNITY, THAT YOU WANT TO
SERVE.
SO WE HAVE CLINICIANS,
PHARMACISTS, WE HAVE COMPUTER
SCIENTISTS, BUT THE OVERRIDING
THEME IS THESE ARE ALL FROM
UNDERREPRESENTED UNIVERSITIES,
TRIBAL COMMUNITY COLLEGES, AND
ACTUAL COMMUNITY GROUPS.
AND IT'S OVER A 1200
INSTITUTION, WE HAVE OVER 2600
INVESTIGATORS, 1200-SOME
MENTEES, THERE'S FELLOWSHIPS,
CAPACITY BUILDING, THERE'S
INFRASTRUCTURE CAPABILITIES, NO
ONE-SIZE-FITS-ALL HERE.
YOU HAVE TO GO AND WORK WITH
THESE GROUPS TO UNDERSTAND WHAT
KIND OF INFRASTRUCTURE IS GOING
TO BEST SUIT THEIR NEEDS.
IT'S BEEN FANTASTIC.
IT'S BEEN A GREAT LEARNING
EXPERIENCE.
AND SO I JUST WANTED TO PUT THE
PLUG IN FOR AIM AHEAD AND ALSO
TELL YOU SOMETIMES, TWO YEARS
AGO I THINK, WE SUPPORTED WITH
NLM AN R25 PROGRAM FOR CURRICULA
AND STUDENT DEVELOPMENT AND
A.I., NOT NECESSARILY FOCUSED ON
UNDERREPRESENTED COMMUNITIES BUT
WE'VE GOT A LOT OF GREAT
COMMUNITIES PUTTING IN GRANTS, I
HAD THE PLEASURE OF GOING TO
WAKE FOREST AND SITTING IN ON
ONE OF THE CALLS WITH THE
P.I.s THERE WITH THAT R25.
I LEARNED IT'S SUPPORTING PEOPLE
WHO MAY NOT NECESSARILY HAVE
GOTTEN TRAINEE AWARDS TO WORK
WITH LARGER INSTITUTIONS LIKE
WAKE FOREST TO ACTUALLY DEVELOP
A.I. SO I WANT TO THANK NLM FOR
THEIR PMI.
THEY WERE THE ONLY I.C. WHO
PARTNERED ON THIS CONCEPT, IT
WAS REALLY A PLEASURE.
THERE'S A LOT OF HIDDEN TALENT
HERE, IF YOU DIG DOWN YOU'LL
FIND A LOT OF HIDDEN TALENT.
>> THIS IS NOT AN NLM RESOURCE,
BUT THERE'S DATA CARPENTRY.
INITIATIVE HAS BEEN PUSHING, SO
MY UNIVERSITY ACTUALLY HAS ONE
OF THESE, WHERE WE HAVE SOMEONE
WHO LEARNS HOW TO TEACH PEOPLE
R.
THE IDEA FOR BASIC SCIENTIST,
PEOPLE WHO DON'T NORMALLY DO
ANALYTICS WHO AT LEAST
UNDERSTAND SO WHEN THEY ARE
TALKING TO SOMEONE AS JIM
MENTIONED, THEY HAVE A BETTER
SENSE OF WHAT THEY ARE ASKING
FOR AND WHAT THEY CAN GIVE THEM,
SO THAT'S ANOTHER EFFORT.
I DON'T KNOW HOW IT SCALES OR
WHETHER THERE'S A PARTNERSHIP
WITH THE NIH.
BUT A LOT OF PEOPLE HAVE FOUND
THAT VERY USEFUL AT MY
UNIVERSITY BECAUSE IT'S SORT OF
BITE SIZED.
THEY TAKE A ONE-WEEK WORKSHOP
AND LEARN SOMETHING.
>> ABSOLUTELY I THINK WE'RE
PARTNERING IN SOME WAYS WITH THE
CARPENTRIES GROUPS AND PROCERA,
THERE'S A LOT OF PARTNERSHIPS
UNDER THE COVER, TAKING STEPS
FORWARD.
>> THE OTHER PARTNERSHIP I MIGHT
ADD THERE IS I THINK I DID A
BRIEF PASSING IN MY REMARKS, ANY
COMMUNITY OF PRACTICE BEING SET
UP FOR SUPPORTING A.I.
BETWEEN CIT AND NLM.
RUNNING TECHNICAL OFFICE HOURS.
IT'S A WAY THAT'S MORE ADVANCED
SUBJECT MATTER EXPERTS CAN
PROVIDE REALTIME SUPPORT,
ADVICE, DIRECT CONSULTATION TO
OTHER INTRAMURAL INVESTIGATORS
OR EXTRAMURAL PROGRAM OFFICERS
TRYING TO BUILD A.I. SERVICES
AND TOOLS HERE.
AND I DON'T KNOW HOW MUCH WE CAN
GROW THAT, I THINK IT'S, AGAIN,
DIANE MIGHT HAVE REMARKS ON THE
UPTAKE AND IF THERE'S PLANS ON
GROWTH BETWEEN THAT AND CIT.
>> YES, SO WE CREATED AN NIH
COMMUNITY OF PRACTICE AROUND
GEN-A.I.
YOU CAN IMAGINE EVERYONE WAS
EXCITED TO GET INTO THAT BUT
IT'S NOT PLUG AND PLAY, OUR
ENVIRONMENT STRIVES, SO WE BY
WORD OF MOUTH HAVE OVER 600
MEMBERS AND IT CONTINUES TO
GROW, TONS OF ENGAGEMENT.
IT'S A GREAT PLACE FOR EVERYONE
BECAUSE WE'RE LEARNING AS WE GO
AS WELL, AND A LOT OF THESE
TOOLS ARE CHANGING BECAUSE
AMAZON, GOOGLE, MICROSOFT, HOW
IT LOOKS TOMORROW, SO WE'RE
WORKING ACROSS USE CASES,
SIMILAR USE CASES.
WE DON'T NEED TO CREATE 27
DIFFERENT CUSTOMER
SERVICE-RELATED CHATBOTS BUT
SOME WANT TO USE OTHER
RESOURCES.
KNOWLEDGE SOURCES.
WE'RE WORKING TOGETHER, TRYING
FIND THESE COLLABORATIONS SO
WE'RE PULLING PEOPLE WITH
DIFFERENT STRENGTHS THAT MIGHT
BE BETTER CONTENT ARRANGEMENTS
OTHER ORGANIZATIONS HAVE
TECHNICAL SKILLS, AGAIN ANOTHER
GREAT PLACE WE WERE TALKING
ABOUT THAT, NLM RISK GROUP,
TALKING TO EACH OTHER, WHY ARE
WE DOING THAT, WHAT IS THAT
INTENTION, ANOTHER WAY TO THINK
WHAT YOU'RE DOING HERE AND IS
THIS THE RIGHT RESOURCE, THE
RIGHT WAY TO PRESENT THE MESSAGE
YOU'RE TRYING ON ACCOMPLISH.
WE STARTED THOSE TECHNICAL
OFFICE HOURS.
WE HAVE TWO DAYS A MONTH.
ONE IS GENERAL PURPOSE, WE GET
PRESENTERS WHO WANTS TO SHARE
USE CASES, BUT ALSO WE HAVE
OFFICE HOURS WHERE WE'RE TRYING
GET PEOPLE, BARRIERS TO WORKING
THROUGH THEIR CHALLENGES.
I ALSO WANT TO PLUG THE NETWORK
RESOURCES SINCE WE'RE TALKING
ABOUT TRAI A HUGE TRAINING
RESOURCE TO GET INVOLVED, AND
THEY ARE AVAILABLE THROUGH THE
NETWORK.
>> I APPRECIATE ALL THESE
DIFFERENT KIND OF EDUCATIONAL
INITIATIVES BECAUSE AS MENTIONED
LIKE THE, FOR EXAMPLE, THE
TECHNOLOGY IS FAST, WE DON'T
NECESSARILY TEACH OUR USERS OR
STUDENTS TO STEP OUT,
EVER-EVOLVING ADVANCEMENTS OF
TECHNOLOGIES, SO WHAT WE FOUND
THAT IS INVOLVING LIKE THE NURSE
IN THE CO-DESIGN PROCESS
HELPFUL.
THERE ARE A LOT OF LIKE
DISCUSSIONS, ALSO, YOU KNOW,
HESITANCY USING GEN-A.I. IN
EDUCATION, THERE ARE PLAGIARISM
ACTIVITIES, PROACTIVELY
INVOLVING THE NURSE IN THE
PROCESS OF LIKE CRITICALLY
EVALUATE OR MAKE JUDGMENTS HOW
THEY PLAY A ROLE IN LEARNING IS
QUITE HELPFUL, SO I'M
APPRECIATIVE.
>> YEAH, BRINGS SOMETHING TO
MIND, NOT IN EDUCATION SPACE.
A COUPLE MONTHS AGO I DON'T KNOW
IF YOU HEARD HERE BUT NURSES AT
CEDARS-SINAI ON THE WEST COAST
WENT ON STRIKE ABOUT THE USE OF
A.I.
AND WHAT IT LED US TO THINK
ABOUT, BECAUSE THEY WERE
BASICALLY PUSHING BACK AGAINST
THE IDEA OF THE HYPE WITHOUT
EVALUATION.
I'M WONDERING WHAT THE NLM OR
ODSS, WHAT'S BEING DONE.
THERE'S A LOT OF EXCITEMENT
ABOUT A.I., DEFINITELY.
BUT THE EVALUATION PART, THE
EQUIVALENT OF, YOU KNOW, WHAT
THE FDA IS AFTER THE DRUG IS
OUT, POST-MARKET SURVEILLANCE,
WHERE IS THE POST-MARKET
SURVEILLANCE STUDIES FOR A.I.?
>> WELL, (INAUDIBLE) MIGHT BE
ONE PLACE TO START.
THEY HAVE WANTED THIS FROM A.I.
SURGE PERSPECTIVE, AND
PROBABLY -- SURVEYED ALL THE
SPECIALTIES.
FIRST REALLY GOOD AT VALIDATING
TECH, GENERATIVE A.I. MORE
WORKFLOW ANALYSIS PROBLEMS BUT
TEST PROBLEMS.
SO ONE OF THE QUESTIONS HOW TO
START DOING THIS.
THERE'S THE IDEA OF TECHNICAL
COMPONENT OF BILLING IS HOW
PATHOLOGY HAS GOTTEN (INAUDIBLE)
THE OTHER PART IS VALIDATING THE
MODELS IS HELPFUL, BUT THE
MODELS NEED RELEVANT DATA TO
VALIDATE.
>> OKAY.
>> SO IT TURNS OUT WE HAVE THIS
PROBLEM WHERE BACK TO THE
ISLANDS, MAYO CLINIC DOESN'T
NEED ANY HELP BECAUSE THEY HAVE
THE SUBSPECIALISTS IN ALL THE
THINGS, ALL THE EDUCATIONS
ALREADY.
IT'S TWO-PERSON SHOP IN RURAL
COLORADO WHERE YOU MAY NOT HAVE
EVER ENCOUNTERED THE CASE YOU'RE
MOST AFRAID OF.
SO, THE WAY TO GET AROUND THE
PROBLEM REFERENCE SUPPLIERS OF
STANDARD MATERIALS, JUST ORDER
SOME SODIUM SOLUTION
(INAUDIBLE), YOU COULD ORDER
DIGITAL STANDARD MATERIALS FOR
PURCHASE ACCESS TO MATERIALS
HELD AT ACCESS CONTROLLED
ENCLAVE, RIGHT, PUSH THE
ALGORITHM TO THAT, AND HAVE
VALIDATED AGAINST DATA YOU WILL
NEVER HAVE IN YOUR INSTITUTION
BUT AT LEAST YOU CAN KNOW IT
WORKS AGAINST THAT DATA.
YOU KNOW, PROSTATE CANCER, I
NEVER SAW ONE OF ON GUAM BUT
THAT'S THE ONE, THAT'S THE
PERSON WHO NEEDS THE HELP.
BIG HOSPITALS, THE METROPOLITAN,
THE BIG METROPOLITAN AREAS DON'T
CARE.
IT'S, YOU KNOW, PEOPLE IN SMALL
SPACE THAT HAVE THESE PROBLEMS.
>> BUILDING ON WHAT HE SAID, THE
MITRE CHI ASSURANCE LAB
PARTNERING TO TEST THE CONCEPT
HE DESCRIBED WITH A FEW
RESEARCHERS TO PILOT BIOMEDICAL
SPACE THAT AREN'T PATHOLOGY, ANY
A.I., ANY LEVEL OF MATURITY
MODEL, EARLY, YOU KNOW, LATER,
WE JUST WANT TO TEST OUT WHAT WE
NEED TO KNOW, WHAT WE DON'T
KNOW, YET CLINICAL BASIC
SCIENCE, SO I'M REALLY EXCITED
TO PARTNER WITH MITRE AND
ASSURANCE LAB ON THIS TO SEE HOW
WE CAN SUBSTANTIATE GOING
FORWARD.
THAT'S ONE OTHER.
NLM IS ALSO THINKING ABOUT A.I.
ASSURANCE AND A.I. RISK
MANAGEMENT FRAMEWORK SO MAYBE
I'LL PASS THE BALL TO STEVE.
>> THANKS, SUSAN.
I JUST WANTED TO MAYBE TAKE THE
CONVERSATION UP A LITTLE BIT AND
THINK BACK TO DR. TABAK'S
REMARKS YESTERDAY, ABOUT THE
NLM, BEING REIMAGINED FOR THE
FUTURE, THE NEEDS AROUND DATA
FEDERATION, AROUND STANDARDS,
INTEROPERABILITY IN A LARGE
ECOSYSTEM OF REPOSITORIES, ASK
THE BOARD ARE THERE ANY OTHER
SPECIFIC DIRECTIONS MAYBE THAT
NLM SHOULD CONSIDER IN THE
FUTURE AS WE THINK ABOUT
STRATEGIC PLANS OR HOW TO CREATE
PRIORITIES IN RESPONSE TO DR.
BERTAGNOLLI'S VISION AND
PRIORITIES FOR NIH?
WE TALKED A LOT ABOUT A.I. BUT
THERE'S OTHER -- CLINICAL CARE,
UNDERSERVED COMMUNITY, LISTENING
TO SEE IF THERE ARE OTHER
PRIORITY AREAS THE BOARD CAN
THINK OF THAT WE SHOULD MAKE
SURE WE'RE ATTENDING TO.
>> SO, STEVE, THIS IS JOHN
AGAIN.
I THINK I WOULD CHALLENGE YOU TO
THINK WHERE DR. LARRY WAS GOING
YET, DR. TABAK, BIGGER INTO THE
FUTURE.
WE SEE A LOT OF DIFFERENT
DATABASES COMING OUT THAT
EMULATE WHAT YOU'RE DOING.
BUT WE SEE CHALLENGES DOWN THE
ROAD LIKE THE STANDARD TYPE
THINGS.
SHOULD NNLM BE MORE OF THE
STANDARD REPOSITORY TO VALIDATE
SOME OF THESE OTHER SYSTEMS OF
SYSTEMS?
AND SHOULD WE START THINKING IN
THAT NATURE?
I'M NOT SAYING GET AWAY FROM
WHAT YOU'RE DOING NOW WITH
PubMed OR OTHER THINGS BUT
THINKING IN THE FUTURE WHAT IS
GOING TO BE THE STANDARD OF
THOSE VALIDATIONS, WHAT IS GOING
TO BE THE CRITERIA?
THINK OF IT AS A STANDARD, JATO,
HOW THEY INSPECT, COME UP WITH
STANDARDS APPLIED IN THE SYSTEM
SO THEY DON'T HAVE TO BE THE
REFERENCE LIBRARY BUT HAVE TO BE
THE REFERENCE OF THE REFERENCE
LIBRARY.
SO I WOULD ONLY SAY WITHOUT
BEING AN EXPERT IN YOUR FIELD,
AND I'M NOWHERE NEAR THAT, IS
THINKING ABOUT WHERE THE PUCK IS
GOING AS OPPOSED TO WHERE IT'S
AT, AND I WOULD JUST NOT WANT
THIS GREAT INSTITUTION TO BE --
TO LOOK UP ONE DAY AND REALIZE
THEY ARE JUST ANOTHER PLAYER IN
THE FIELD AS OPPOSED TO THE
LEADER OF THE PACK.
>> SO, ONE OF THE TENSIONS WE
HAVE TO RESOLVE IS AN
EXISTENTIAL QUESTION TO THE
LIBRARY, WHICH CENTERS ON THE
UNIVERSALITY AND COMPLETENESS OF
OUR COLLECTIONS.
PART OF THE VALUE AND POWER I
THINK WE HAVE OF UNIFORMLY
APPLYING STANDARDS ACROSS OUR
OWN CONTENT, THAT'S SOMETHING WE
CONTROL, RIGHT?
AND WE CAN WORK TO THE QUALITY
STANDARDS WE SET FOR OURSELVES,
ALLOWS US TO CREATE LARGE
UNIFORM CORPUSES OF DATA.
AS WE FED RATE THAT, HOW DO --
AS WE FEDERATE THAT, ATTEND TO
THE QUALITY, MAYBE THAT'S WHAT
YOU'RE SAYING ABOUT BEING
STANDARD OF STANDARDS, THERE'S
FRAMEWORKS, THERE'S GOING TO BE
SOME VALUE PREMISED
CERTIFICATIONS LIKE SUSAN
DESCRIBED WITH THE GLOBAL
BIODATA CATALYST OR OTHER
COMMUNITIES OF PRACTICE, BUT I
STILL THINK THERE'S TENSION
AROUND HOW MANY DATA NEEDS TO BE
CENTRAL VERSUS DO THINGS LIKE
COMPUTE.
BECAUSE ON SOME COMPUTE YOU HAVE
TO BRING DATA TOGETHER IN
MEMORY.
AS PROBLEMS AND QUESTIONS GET
BIGGER WE NYING NEED TO NEED AT
REDUCING TASKS, REDUCE THE MAP
ALGORITHM OR THINK THERE ARE
SOME THINGS THAT ARE VALUABLE
ENOUGH WE WANT TO HAVE CENTRAL
COPIES?
SO THAT IF SOMETHING DISAPPEARS
FOR WHATEVER REASONS RELATED TO
SUSTAINABILITY OR CHANGE IN
MISSION WE HAVE A COPY OF THE
DATA.
AND I DON'T KNOW THE ANSWER BUT
I WOULD HEAR THE BOARD THINKING
AROUND HOW MUCH THEY EXPECT
LIBRARIES TO HAVE A COMPLETE
COLLECTION VERSUS THE CATALOG
THAT CAN POINT YOU TO WHERE TO
GET THE DATA.
IT MIGHT NOT BE THERE, RIGHT?
CATALOG ENTRIES COULD DISAPPEAR,
THEY STOP PAYING THE BILL, I
HAVE AN ANXIETY ABOUT TURFING
OUT TOO MUCH BUT WE CAN'T HOLD
THE WORLD'S DATA EITHER.
THERE ARE LIMITS TO WHAT WE CAN
DO FIGURING OUT HOW TO BE
STRATEGIC AND PUTTING MOST VALUE
IN OF INTO THINGS WE NEED TO
COLLECT.
I THINK THAT'S A TOPICAL AREA WE
WANT TO UNDERSTAND IN OUR NEXT
STRATEGIC PLAN AND INVITE YOU TO
COMMENT NOW, AND IF THAT BRINGS
UM SOME PRIORITIES OR YOUR OWN
EXPERIENCE AROUND WORKING WITH
FEDERATED DATA SYSTEMS AND
CAUTIONS.
>> DOES ANYONE HAVE A RESPONSE.
>> YES, VERY GOOD POINT, REALLY
IMPORTANT DISCUSSION, I THINK
IT'S WORTH CONSIDERING HOW TO
INCORPORATE A COMMUNITY THAT
WANTS TO CONTROL THEIR OWN DATA,
THINKING ABOUT INDIGENOUS PEOPLE
IN THE U.S., THERE'S BEEN A PUSH
FOR INDIGENOUS DATA LATELY, ONE
DATABASE ESTABLISHED BY
INDIGENOUS COMMUNITIES SO THEY
CAN CONTROL THEIR OWN DATA.
I THINK IT'S REALLY IMPORTANT
FOR NIH TO THINK ABOUT HOW CAN
YOU WORK, FOR EXAMPLE, GROUPS
THAT WANT TO CONTROL THEIR OWN
DATA WITHOUT THAT DATA BEING
SILOED AND NOT BEING PART OF THE
ECOSYSTEM THAT NIH IS BUILDING
OFF.
HOW DO YOU SOLVE THAT PROBLEM, I
DON'T KNOW, BUT I THINK IT WILL
BE IMPORTANT PRIORITY IN THE
FUTURE TO FIGURE OUT HOW TO
SOLVE THIS PROBLEM ABOUT A DATA
SOVEREIGNTY, WHILE MAINTAINING
INTEGRITY OF THE WHOLE
ECOSYSTEM.
>> GREAT POINT.
WE'RE WORKING THROUGH -- WE HAVE
AN OFFICE FOR TRIBAL RELATION
AND REGULAR CONVERSATION, ON OUR
STRATEGIC PLAN TO HAVE THAT
CONVERSATION, HOW DO WE
REPRESENT INDEX OR CATALOG WHILE
GIVING THEM AUTONOMY WITH
ACCESS, WHAT THEY WANT TO
DISCLOSE, WHAT'S DIRECTED TO
THEM FOR DISCOVERY.
THAT MIGHT BE A MODEL FOR OTHER
CONSTITUENCIES.
SO DATASET CATALOG IS OUR
STRATEGY TO PREVENT
VULCANIZATION, THERE ARE GOING
TO BE FORCES THAT WILL WANT
COMMERCIAL OPERATIONS THAT
COLLECT DATA AS PART OF
PUBLISHING OR PREPARING THEIR
OWN INFORMATION SYSTEMS TO
FIREWALL AND LICENSE THAT DATA
FOR TRAINING.
AND SO I THINK WE NEED TO BE
LOOKING STRONGLY AT CREATIVE
COMS LICENSES, MAKING SURE THEY
ARE EXPRESSIVE AND RIGHTS ARE
RETAINING FOR A.I. TRAINING SETS
AND WE HAVE REACHED-THROUGH
PRINCIPLES TO REUSE DATA AND
SEMANTIC INFORMATION, DERIVED
KNOWLEDGE SET, WITHOUT HAVING TO
GO BACK AND RELICENSE OR
RESUBSCRIBE ANOTHER CLASS OF
INFORMATION.
AND I'M NOT SAYING THAT WILL
HAPPEN WITH TRIBAL AT ALL.
I'M JUST SAYING I THINK THE
ISOLATION OR THE AUTONOMY THAT
WE ARE RESPECTING IN THE TRIBAL
COMMUNITY HARASS ANALOGS IN
INDUSTRY, I WANT THAT SAME KIND
OF AUTONOMY OR COMMERCIAL
AUTONOMY, AND WE HAVE TO BE
CAREFUL, HE THINK, ABOUT WHAT
ARE THE PRINCIPLES AROUND THE
FREE FLOW OF INFORMATION FOR
SCIENCE.
WE HAVEN'T TALKED MUCH ABOUT
TRAINING FOR A.I., AND
DISCLOSING WHAT INFORMATION AND
ALGORITHMIC AUDITING, HOW A.I.
SETS ARE TRAINED, I THINK
THERE'S CONVERSATION A MOMENT
AGO AROUND RELIABILITY, TRUST,
AND UNDERSTANDING, WHAT'S BEING
MEASURED AND HOW DO WE DESCRIBE
FITNESS OF OUR SERVICES.
THAT MIGHT BE A FRAMEWORK TO
ALSO GET INTO SOME OF THESE
PRINCIPLES THAT CAN WE MAIN
OBJECTIVE, ANCHORED TO PUBLIC
PRINCIPLES, TRUST OF INFORMATION
OR SAFETY FOR TAXPAYERS.
>> THANKS, STEVE.
I'M GOING TO LOOK THIS WAY
INSTEAD OF AT THE SCREEN.
A NUMBER OF DR. BERTAGNOLLI'S
PRIORITIES DEAL WITH OR RELY ON
ELECTRONIC HEALTH RECORD DATA,
AND I THINK GENERAL
ACKNOWLEDGMENT THAT THE QUALITY
OF ELECTRONIC HEALTH RECORD DATA
IS POOR AND NEEDS IMPROVEMENT
BUT I DON'T THINK ANYBODY'S
OWNING THAT PROBLEM.
YOU KNOW, I DON'T THINK VENDORS
ARE OWNING IT.
I'M PRETTY SURE THE HEALTH
SYSTEMS DON'T SEE IT AS A
PRIORITY.
PRACTITIONERS DEFINITELY DON'T
SEE IT HAVE INCENTIVE TO APPROVE
DATA WITH THE IDEA TO HELP
SOMEBODY ELSE'S RESEARCH.
SOME IS INFORMATICS RESEARCH
NEEDED TO FIGURE OUT HOW DO WE
ACTUALLY IMPROVE THE QUALITY OF
DATA, INCREASE QUANTITY OF DATA,
WITHOUT INCREASING OR PERHAPS
REDUCING THE BURDEN ON PEOPLE
WHO HAVE TO CAPTURE THE DATA.
SO THAT RESEARCH I THINK VERY
MUCH IS IN THE NIH WHEELHOUSE,
AND WHILE INVESTIGATOR INITIATED
STUDIES MIGHT ADDRESS THAT AND
PANELS MIGHT GET THAT THAT'S A
PRIORITY THE NLM COULD PUSH THAT
AGENDA, HOW ARE WE GOING TO
CEASE THAT SORT OF TWO-SIDED
SWORD WHILE NOT BURDENING THE
PEOPLE WHO HAVE TO COLLECT IT.
>> ABSOLUTELY.
AND I THINK THAT IS ONE OF
DIRECTOR BERTAGNOLLI'S
PRIORITIES.
SHE'S WORKING WITH CONGRESS, I
THINK, THE LAST 12 MONTHS ABOUT
THIS VERY CONCEPT.
AND EAGERLY LOOKING FORWARD TO
THE NEXT LEVEL ROUND OF
APPROPRIATION HEARINGS.
I THINK NIH MIGHT BE DIRECTED TO
DO SOME NEW WORK IN THIS SPACE
BY CONGRESS, AND BE FORCED TO DO
IT, SO LET'S SEE IF WE CAN
ELEVATE THIS THROUGH SOME NEW
PROGRAMS.
BUT I THINK WE HAVE TO WAIT AND
SEE WHAT HAPPENS IN THE
APPROPRIATION CYCLE.
BUT THAT BEING SAID, THERE'S
WORK WE CONTINUE TO INVEST IN
AROUND FHIR AND INTEROPERABILITY
OF EHR AND REPRESENTATION OF
DATA.
THERE'S DRIVER CASES THAT WOULD
BE EASIER TO DO IF CONGRESS
DECIDES THIS IS A PRIORITY FOR
NLM.
SO, I THINK WE HAVE TO SEE WHAT
HAPPENS WITH OUR NEXT ROUND OF
APPROPRIATIONS.
>> I'LL JUST REITERATE WHAT I
MENTIONED EARLIER, BECAUSE I DO
SEE A CONNECTION BETWEEN WHAT
WAS IT, LABORATORY CLINIC UNITY
AND CARE FOR HEALTH.
AS I MENTIONED, WITH THOSE
NON-ACADEMIC PHYSICIANS, ADVANCE
PRACTICE NURSES, ALSO WITH THE
PUBLIC.
I MEAN, JUST THINKING WHETHER
IT'S BETTER ALGORITHMS OR
SMALLER LANGUAGE MODELS OR
WHATEVER RAG TECHNOLOGY, BUT HOW
DO YOU HELP COMMUNITY WITH
TRYING TO BRING IN THAT
INFORMATION FROM CT.GOV, FROM
GENETIC DATABASE,
MedlinePlus AND THE
LITERATURE, AND WHETHER OR NOT
SOMEONE CAN GET EITHER
SCIENTIFIC PROMPT, SO SCIENTIFIC
RESPONSE, OR EVEN A LAYPERSON'S
RESPONSE, BUT -- BECAUSE WE TALK
ABOUT DATA, YOU KNOW, BEING A
PART OF THE BOARD, BUT, YOU
KNOW, I CONSIDER MYSELF
INFORMATION ECOLOGIST, AND I'M
HEAVILY BIASED TOWARDS THE NEXT
STEP OF DATA.
THE INFORMATION, HOW DO WE
TRANSLATE IT TO IMPROVE OUTCOMES
AND POLICIES.
SO IS WE'LL HAVE PEOPLE TO FIGHT
WITH THE DATA AND FIGHT WITH
INFORMATION, BUT SOMEHOW I CAN
SEE OVER THE LAST TWO DAYS FROM
DR. TABAK'S PRESENTATION AND
FROM WHAT YOU MENTIONED TODAY
THAT THERE'S DEFINITELY WORK
THAT CAN BE DONE.
I TOTALLY RESPECT HOW WE FOCUS
WITH THE RESEARCH AND BASICS AND
THEORETICAL, BUT AT THE SAME
TIME WE HAVE TO THINK ABOUT THE
COMMUNITY AS WELL AND VALUABLE
RESOURCES HERE ACROSS THE ENTIRE
I.C. HERE, AS WELL.
>> SO, I THINK THERE'S A GREAT
POINT, AND THAT REALLY IS THAT
FINAL, YOU KNOW, MILE TO CONNECT
ALL OF THE HEALTH INFORMATION,
MAKING IT ACTIONABLE, AND
RELATABLE, AND AVAILABLE TO
COMMUNITY MEMBERS.
YOU KNOW, WE HAVE MEDLINE PLUS.
WE HAVE HEALTH INFORMATION
SYSTEMS THAT ARE WORKING I THINK
WITH AGGREGATE LEVEL DATA BUT
THERE'S STRONG OPPORTUNITY TO DO
SOMETHING MORE PERSONAL AND
INDIVIDUALIZED BASED ON
INFORMATION.
THE CAUTION IS HOW DO WE DO THAT
WITHOUT PRACTICING MEDICINE,
RIGHT?
WE'RE TRYING TO BUILD
INFORMATION SYSTEMS, WE DON'T
WANT TO BECOME, YOU KNOW, AN
IMPERFECT ANALOG FOR HEALTH
CARE.
WE NEED EXPERTISE.
THERE'S A PLACE TO SYNTHESIZE
WHAT'S KNOWN IN REAL TIME OUT OF
CLINICAL TRIALS, HEALTH
INFORMATION, OUT OF BEST
PRACTICES AND RESEARCH,
PubMed AND PMC, TO TRAIN
GENERATIVE MODELS THAT MAYBE
HAVE INTERROGATIVE RELATIONSHIP
WITH PATIENTS THAT IS PLAIN
LANGUAGE.
I THINK THAT'S SOMETHING TO
TEST, HOW DO WE DO THIS, KEEP IT
FACTUALLY UP TO DATE, HOW OFTEN
DO WE HAVE TO REMAIN MODELS?
THERE'S A WHOLE OPERATIONAL
FRAMEWORK AND QUESTIONS.
DOES NLM DO THIS, IS IT NIH
ENTERPRISE?
A LOT OF THAT INFORMATION IS
ALSO OUT WITH THE ICs, DISEASE
SPECIALTY AREAS.
MAYBE IT'S A PARTNERSHIP WITH
CIT.
THAT'S WHY I THINK THE CELL
KNOWLEDGE PROGRAM I ILLUSTRATED
IS A TEST INTO THAT SPACE DOING
SOMETHING NARROW JUST AROUND
CELLS AND ONLY -- - THE PROBLEM
GETS RICHER AND INFORMATIVE AS
YOU MOVE TO PATIENTS IN WHOLE
HEALTH BUT HARDER, RECURRENT,
WE'RE LEARNING HOW TO CRAWL,
WHAT'S THE BUDGET, FRAMEWORK,
EXPERTISE, THE COMPUTATIONAL
LIFT TO OPERATE THAT, THAT WE
CAN GENERALIZE.
IT'S MY GOAL AND VISION, SPEAK
FOR MYSELF AS ACTING DIRECTOR,
LEAVE IT TO THE PERMANENT
DIRECTOR TO SET THE LONGER-TERM
PRIORITIES FOR NLM BUT A SPACE
WE'RE RICH WITH DATA, A
CHALLENGE AND OPPORTUNITY TO
TURN THAT INTO KNOWLEDGE ACROSS
ALL OUR SYSTEMS.
I HEAR THAT.
AND I THINK WE CAN TAKE THAT
BACK AND CONTINUE TO WORK WITH
OUR SERVICE TEAMS AND FIGURE OUT
WHAT ARE THE NEXT STEPS WE CAN
DO TO EMPOWER THAT, FOR RURAL
COMMUNITIES.
I HEARD A LOT ABOUT
DISADVANTAGED AND HEALTH
EQUITIES, THAT WOULD GIVE US
MEANINGFUL ADVANCE IN THEIR
ACCESS TO INFORMATION.
>> THANK YOU.
WE'RE COMING UP ON TIME BUT
SUSAN HAD A --
>> I JUST WANTED TO FOLLOW UP ON
THE TRIBAL DATA SOVEREIGNTY, THE
TRIBAL RESEARCH OFFICE IS
WORKING ON THE TRIBAL DATA
SOVEREIGNTY DATA SHARING POLICY
WITH HHS, ACROSS NIH, LED BY
KARINA WALTERS, 574 TRIBAL
NATIONS, HAVING WORKED WITH A
FEW OF THESE, THEY ALL HAVE
DIFFERENT CONCEPTS OF WHAT DATA
SHARING WOULD LOOK LIKE UNDER
THEIR CONTROL, IT'S NOT A
ONE-SIZE-FITS-ALL.
I WOULD SET UP A TRIBAL LEADER
REPOSITORY FOR RADx, NOT EASY.
SHE'S GOING TO HOST A WORKSHOP
NEXT WEEK, 16th AND 17th, I
BELIEVE, A DEEP DIVE TO DISCUSS
THIS FURTHER.
I CAN SEE ABOUT SHARING THIS
INFORMATION WITH THE BOARD IF
YOU'RE INTERESTED.
IT'S A REALLY IMPORTANT PROBLEM.
SO GLAD WE HAVE KATRINA TO WORK
ON THAT.
>> FROM THE SLIDES THERE'S A
DATA USE ONTOLOGY BEING
DEVELOPED, I THINK VERY VALUABLE
FOR THESE KINDS OF APPLICATIONS
TO FINE TUNE WHAT IS A COMPONENT
OF THE DATA USE AGREEMENT THAT
CAN BE TAILORED TO DIFFERENT
COMMUNITIES AND THINGS LIKE
THAT.
IT'S AN INTERESTING STANDARD TO
TAKE A LOOK AT.
>> WELL, THANK YOU.
WE'RE COMING UP ON TIME.
THANK YOU FOR A RICH DISCUSSION.
WE'RE GOING TO MOVE TO
PRESENTATION OF REGENTS AWARD.
I'M RECOGNIZING THE RECIPIENT
FOR SCHOLARSHIP OR TECHNICAL
ACHIEVEMENT THIS YEAR.
ESTABLISHED IN 1970, BY THE
BOARD OF REGENTS RECOGNIZING
INDEPENDENT CREATIVITY, USE OF
SCHOLARLY OR TECHNICAL
ACHIEVEMENTS THAT ENRICH
BIOMEDICINE, A NEW PRODUCT OR
METHODOLOGY THAT IMPROVES
BIOMEDICAL KNOWLEDGE OR SERVICE.
THE BOARD CONSIDERS THIS AWARD
THE HIGHEST HONOR IT CAN GIVE TO
A MEMBER OF THE NLM STAFF.
WE HAVE TWO AWARDS THIS YEAR FOR
THE REGENTS AWARD.
FIRST IS PRESENTED TO DR. LU, A
SENIOR INVESTIGATOR IN THE
COMPUTATIONAL BIOLOGY BRANCH,
INTRAMURAL RESEARCH, DEVELOPED
AN ALGORITHM, THAT ANALYZES FREE
TEXT FROM CLINICAL NOTES IN A
PATIENT'S ELECTRONIC HEALTH
RECORD TO HELP MATCH PATIENTS
WITH ENROLLMENT CRITERIA FOR
OPEN CLINICAL TRIALS.
BASED ON THE 184 PATIENTS AND
THREE LARGE NCI CLINICAL TRIALS,
IT WAS 87% ACCURATE IN
PREDICTING A PATIENT'S
ELIGIBILITY.
A SIMILAR ACCURACY FROM MANUALLY
READING NOTES BUT REDUCED
SCREENING TIME BUT 50%.
UNLIKE OTHER MODELING STRATEGIES
TRIALGPT CAPTURED EXPLANATION
ALLOWING CLINICAL PRACTITIONERS
TO UNDERSTAND HOW THE MODEL
REACHED CONCLUSIONS.
WHILE INTENDED FOR CLINICIANS,
TRIAL GPT HAS POTENTIAL USE TO
FIND SUITABLE CLINICAL TRIALS.
THE MANAGEMENT DESCRIBING
TRIALGPT HAS BEEN ACCEPTED FOR
PUBLICATION IN NATURE
COMMUNICATION.
>> NEXT IS PRESENTED TO A GROUP
OF EMPLOYS, MR. JEFFREY BECK,
NANCY POLGREN, MR. SIEBERT,
MR. STOCKDALE.
MR. BECK IS A SUPERVISORY
INFORMATION SPECIALIST IN THE
INFORMATION ENGINEERING BRANCH
OF THE NATIONAL CENTER FOR
BIOTECHNOLOGY INFORMATION,
MS. SIEBERT IS SPECIALIST IN THE
HEALTH DATA CENTER BRANCH OF
USER SERVICES.
MR. STOCKDALE AND MISS FALLGREN
ARE IN THE DISCOVERY BRANCH OF
THE SAME DIVISION, THEY
DEVELOPED AND LAUNCHED DATASET
CATALOG DATA PRODUCT AND DATASET
METADATA MODEL, PROVIDING
METADATA TO LOCATE AND ACCESS
DATASETS AT THEIR SOURCE.
LED BY MR. SIEBERT WITH OTHERS
PROVIDING EXPERTISE IN LINKED
DATA, THE TEAM WORK ACROSS THE
NIH EXTERNAL HOLDERS, EXTERNAL
STAKEHOLDERS, AND STANDARDS
ORGANIZATIONS TO DEVELOP DATUM,
OFFERINGS AND INTERFACE ACROSS
REPOSITORIES, RELATED
INFORMATION THAT MIGHT BE
OBSCURE AND LOCATING THE MOST
SUITABLE DATASETS.
DATA MODEL AND CATALOG
STANDARDIZE METADATA AND ALLOW
RESEARCHERS TO SEARCH, DISCOVER,
RETRIEVE DAFT SETS ACROSS
REPOSITORIES WITH FUTURE
POTENTIAL TO FIND DATA BEHIND
THE LITERATURE.
LET'S EXPEND WARM
CONGRATULATIONS TO THESE FOR
THEIR EXCELLENT ACHIEVEMENTS.
>> SO, I GUESS IT'S TIME TO
ADJOURN.
I WANTED TO SEE IF YOU HAD
ANYTHING TO SAY BEFORE WE
ADJOURN.
>> THANK YOU, EVERYONE.
I WISH I COULD HAVE BEEN THERE
IN PERSON.
THIS WAS A GREAT MEETING.
I APPRECIATE AS ALWAYS THE
FANTASTIC FEEDBACK, THOUGHTFUL
DISCUSSION ENGAGEMENT.
I MISSED DINNER LAST NIGHT BUT
YOU WERE ON MY MIND.
LOOK FORWARD TO OUR NEXT
MEETING.
I WISH EVERYONE SAFE TRAVELS,
AND THANK YOU, ON BEHALF OF NLM,
FOR EVERYTHING YOU DO IN SERVICE
TO US.
IT'S BEEN A REAL TREAT TODAY.
>> I WOULD LIKE TO THANK
CHRISTINE AND THE EVENT
MANAGEMENT STAFF FOR BRINGING
THIS ALL TOGETHER, COORDINATING.
>> YES, THANK YOU.
>> THANK YOU ALL, AND MEETING IS
ADJOURNED.