Keynote talk for International Workshop on Science Gateways - Australia, https://sites.google.com/site/iwsglife/about-iwsg-a/iwsg-a-2016.

1. science gateway /sī′ əәns gāt′ wā′/ n.
1. an online community space for science and engineering research and
education.
2. a Web-­based resource for accessing data, software, computing services,
and equipment specific to the needs of a science or engineering discipline.
Science Gateways: History, Successes,
Path Forward
A
tale
of
many
slide
templates
J
Thank
you
to
Michelle
Barker,
Richard
Sinnott and
David
Abramson
for
the
invitation
to
speak

2. Remember 2004?
• Microsoft, AOL and Jeeves ruled
the Web
• Facebook launched
– More users today than were on the
entire internet in 2004
• Google 5th most popular brand
behind AOL and Yahoo in
popularity
• Time magazine recommends
friendster as website of the year
• I first start working with science
gateways

3. Beginnings of the TeraGrid program
• TeraGrid develops Deep, Wide and Open strategy
• For the first time we are targeting not just the high-­
end HPC user community
Despite the technological progress of grid technology and deployment, only a
minority of the scientific, engineering, and education community use
today’s national computing infrastructure. Our WIDE strategy addresses this
situation by working directly with specific community leaders who are building
discipline-­specific cyberinfrastructure capabilities and resources for their
communities.
TeraGrid proposal, 2003

4. April 2006
Science Gateways
A new initiative for the TeraGrid
• Increasing investment by
communities in their own
cyberinfrastructure, but
heterogeneous:
• Resources
• Users – from expert to K-­12
• Software stacks, policies
• Science Gateways
– Provide “TeraGrid Inside”
capabilities
– Leverage community investment
• Three common forms:
– Web-­based Portals
– Application programs running on
users' machines but accessing
services in TeraGrid
– Coordinated access points
enabling users to move
seamlessly between TeraGrid and
other grids.
Workflow Composer

5. April 2006
But in the beginning, we had no services
We paid science teams to help us develop them
Science Gateway Prototype Discipline Science Partner(s) TeraGrid Liaison
Linked Environments for
Atmospheric Discovery
(LEAD)
Atmospheric Droegemeier (OU) Gannon (IU), Pennington (NCSA)
National Virtual Observatory
(NVO)
Astronomy Szalay (Johns Hopkins) Williams (Caltech)
Network for Computational
Nanotechnology (NCN) and
“nanoHUB”
Nanotechnology Lundstrum (PU) Goasguen (PU)
Open Life Sciences Gateway Biomedicine and Biology Schneewind (UC), Osterman
(Burnham/UCSD), DeLong
(MIT), Dusko (INRA)
Stevens (UC/Argonne)
Biology and Biomedical
Science Gateway
Biomedicine and Biology Cunningham (Duke), Magnuson
(UNC)
Reed (UNC), Blatecky (UNC)
Neutron Science Instrument
Gateway
Physics Cobb (ORNL) Cobb (ORNL)
Grid Analysis Environment High-­Energy Physics Newman (Caltech) Bunn (Caltech)
Transportation System
Decision Support
Homeland Security Stephen Eubanks (LANL) Beckman (Argonne)
Groundwater/Flood Modeling Environmental Wells (UT-­Austin), Engel (ORNL) Boisseau (TACC)
Science Grid
[GrPhyN/ivDGL/Grid3]
Multiple Pordes (FNAL), Huth (Harvard),
Avery (Uflorida)
Foster (UC/Argonne), Kesselman (USC-
ISI), Livny (UW)

6. So how will we meet all these needs?
• With RATS! (Requirements
Analysis Teams)
• Collection, analysis and
consolidation of requirements to
jump start the work
– Interviews with 10 Gateways
– Common user models,
accounting needs, scheduling
needs
• Summarized requirements for
each TeraGrid working group
– Accounting, Security, Web
Services, Software
• Areas for more study identified
• Primer outline for new Gateways
in progress
• And milestones
April 2006

7. April 2006
Linked Environments for Atmospheric Discovery
LEAD
•Providing tools that are needed to make accurate
predictions of tornados and hurricanes
•Data exploration and Grid workflow

8. Social Informatics Data Grid
Collaborative access to large, complex datasets
•SIDGrid is unique among
social science data archive
projects
–Streaming data which change
over time
•Voice, video, images (e.g. fMRI),
text, numerical (e.g. heart rate,
eye movement)
–Investigate multiple datasets,
collected at different time
scales, simultaneously
•Large data requirements
•Sophisticated analysis tools

9. Viewing multimodal data like a
symphony conductor
•“Music-­score” display and
synchronized playback of video
and audio files
– Pitch tracks
– Text
– Head nods, pause, gesture
references
•Central archive of multi-­modal
data, annotations, and analyses
– Distributed annotation efforts by
multiple researchers working on a
common data set
•History of updates
•Computational tools
– Distributed acoustic analysis using
Praat
– Statistical analysis using R
– Matrix computations using Matlab
and Octave
Source: Studying Discourse and Dialog with SIDGrid, Levow, 2008

10. Over the years, the program developed
I gave lots and lots of talks

11. Eventually we had a program
• And
customers
• Starting
in
2013,
gateway
users
surpass
command
line
users
in
XSEDE
Gateways
Login

12. Proliferation of Science Gateways
These are some that use XSEDE supercomputers

13. Cyberinfrastructure for Phylogenetic Research
(CIPRES)
PI Mark Miller, SDSC, www.phylo.org
• 210
US
research
universities
– Harvard,
Yale,
UC
Berkeley,
Stanford,
etc.
– Non-­‐PhD
granting
colleges
(including
one
all-­‐
women’s
college,
community
colleges,
and
Hispanic-­‐serving
institutions)
• 3 K-­‐12
school
systems
• 43
non-­‐governmental
organizations,
– Museums
including
the
Smithsonian
Institution,
the
American
Museum
of
Natural
History,
and
the
Field
Museum),
– Botanical
gardens,
(e.g.
Chicago,
Rancho
Santa
Ana,
and
New
York)
– Institutes
(e.g.
JCVI
and
Broad)
• 10
US
governmental
agencies
– Including
NIH,
USDA,
NOAA,
US
Forest
Service
• Curriculum
delivery
(76)
• 2000+
publications
since
2010
• 47%
of
all
XSEDE
users
in
Q4
2015

14. CIPRES’ reach is deep and wide
Nature article, Feb 2016
Mass. state science fair, July 2012

15. Saving wetlands with the Simulocean science gateway
Football field-­sized parcel of land lost every hour
It's
important
to
enhance
the
collaboration
among
earth
scientists,
computer
scientists,
cyberinfrastructure
specialists
and
coastal
engineers
tasked
with
solving
the
sustainability
issues
of
deltaic
coasts
like
those
in
Louisiana.
Dr.
Jian
Tao,
research
scientist,
LSU
Source:
XSEDE
External
Relations

16. Some NSF programs even specify the use of gateways
This is the right direction to go! Gateways as cost-­effective infrastructure

17. • Developers
typically
– work
in
isolation
– must
bridge
to
variety
of
resources
– need
building
blocks
in
order
to
focus
on
higher-­‐level
functionality
– struggle
to
secure
sustainable
funding
Despite many successes, there are still
challenges
Gateways often funded as 3-­year research projects
Early
adopters
Publicity
Wider
adoption
Funding
ends
Scientists
disillusioned
New
project
prototype

18. In 2014, we sent a survey to 29,000 NSF PIs
and academic CIOs and CTOs
5000 responded
We wanted to understand both the
importance of gateways and challenges
developers face

19. Specialized
Resources
Percent
Data
collections
75%
Data
analysis
tools,
including
visualization
and
mining 72%
Computational
tools 72%
Tools
for
rapidly
publishing
and/or
finding
articles
and
data
specific
to
my
domain
69%
Educational
tools 67%
Platforms
for
fostering
group
or
community
collaboration 63%
Simplified
interfaces
that
eliminate
the
need
to
learn
coding 62%
Citizen
science
and
other
public
engagement
resources 47%
Workflows
that
automate
or
capture
tasks
or
processes 42%
Scientific
instruments,
such
as
telescopes,
microscopes,
or
sensors 39%
We learned that 88% of respondents felt Web-­
based applications were important to their work
n=4,004,
or
88%
of
4,538
researcher/educators.
Percentage
indicates
these
resources
are
“somewhat”
or
“very”
important
to
their
work.

20. 57% played some role in gateway creation
and these gateways were used for a variety of purposes
n
of
application
types=7,805,
by
2,756
creators
(out
of
2,819);
mean=2.8
application
types
per
application
creator

21. 34% 36%
20%
17%
31%
26%
42%
16%
30%
18%
45% 44%
14% 15%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Usability
Consultant
Graphic
Designer
Community
Liaison/
Evangelist
Project
Manager
Professional
Software
Developer
Security
Expert
Quality
Assurance
and
Testing
Expert
Wished
we
had
this
Yes,
we
had
this
A variety of expertise was needed for successful
gateway development
n=2,756
respondents
or
98%
of
application
creators

22. NSF has recognized the importance of
gateways as well

23. We’ve come a long
way since 2004,
baby

24. A successful gateway institute will provide
leadership to
– 1)
bring
science
gateway
developers
together
with
each
other
and
with
the
developers
and
operators
of
existing
and
potential
cyberinfrastructure elements
that
science
gateways
integrate
and
enable
the
use
of
• in
order
to
promote
the
efficient,
effective,
and
sustainable
development
of
scientific
web
and
mobile
interfaces
– 2)
educate
developers
and
the
next
generation
of
investigators
to
effectively
use
the
gateway
software
ecosystem to
solve
real
research
problems;
and
– 3)
educate
the
next
generation
of
researchers
to
enable
them
to
create
the
software
cyberinfrastructure required
to
both
advance
fundamental
understanding
of
science
gateways
and
enable
researchers
to
address
the
grand
challenge
problems
of
the
future

25. Science Gateways Community Institute
Est. Aug, 2016

26. • Incubator
– Modeled
after
business
incubators
– Diverse
expertise
on
demand
• Extended
Developer
Support
– We
help
others
build
gateways
and
teach
them
in
the
process
• Scientific
Software
Collaborative
– Listing
of
both
functional
gateways
and
gateway
software
• Community
Engagement
and
Exchange
– Annual
conference
– Gateways
in
the
news
– Job
postings
– International
and
inter-­‐
agency
community
building
– Campus
expertise
• Workforce
Development
– Student
interns
– Gateways
in
the
classroom
SGCI Highlights

27. • New
developments
in
electron
detectors
and
electron
microscopes
now
provide
images
of
macromolecules
(protein,
RNA,
etc.)
that
can
be
determined
to
atomic
resolution
• Inherent
low
signal
to
noise
ratio
means
300,000
images
needed
for
one
object
of
interest
• HPC
resources
to
calculate
atomic
structures
based
upon
these
thousands
of
images
• Now
discovering
the
structures
of
macromolecules
that
were
previously
unattainable
using
traditional
methods
• The
importance
of
these
discoveries
has
brought
global
interest
into
our
field
from
scientists
without
HPC
training
Our first customer
Dr. Michael Cianfrocco, Cryo-­EM gateway
Source:
Michael
Cianfrocco

28. The
cryo-­‐EM
science
gateway
will
offer
users
access
to
HPC
resources,
requiring
only
that
they
have
raw
cryo-­‐EM
data.
This
will
have
a
wide-­‐ranging
impact
as
national
cryo-­‐EM
centers
are
coming
online
in
the
coming
years,
requiring
that
users
have
a
location
to
process
their
data.
We
are
building
a
gateway
that
can
handle
all
cryo-­‐EM
data,
whereas,
currently,
every
user
has
to
navigate
the
complex
work
of
HPC
data
analysis
to
either
install
software
on
local
clusters
or
get
access
to
national
centers
for
data
analysis.
Long
term,
we
will
incorporate
workflows
that
will
guide
new
users
through
the
processing
pipeline,
helping
them
assess
data
quality
along
the
way.
This
pipeline
will
be
the
first
of
its
kind.
Source:
Michael
Cianfrocco

29. The Institute allows us to expand our focus
beyond HPC
• Sensor-­‐based
gateways
• Interfaces
to
instruments
– Telescopes,
microscopes,
ultracentrifuges,
more
• Gateways
that
access
data
collections
• Citizen
science
• Gateways
that
use
clouds
or
campus
resources
There is a whole wide world of gateways
out there

30. Sage Bionetworks developing predictors of
disease
• Synapse
is
an
open
computational
platform
used
by
Challenge
teams
spread
across
the
globe
to
crowdsource
questions
in
biology
and
medicine
http://sagebase.org/challenges/

32. The examples are endless

33. How do you find a gateway?
We plan to design a marketplace
One that would interact with other marketplaces

34. Vision for SGCI success
5-­10 years from now
• Science
gateways
form
a
vibrant
community
– Inter-­‐agency,
international,
collegial
• Creating
gateways
is
easier
– Created
with
more
thoughtfulness,
so
they
are
more
sustainable
• Gateway
developers
have
stable
career
paths
– More
efficient
environments
on
campuses
• Students
are
excited
to
stay
in
the
sciences
• Radical
changes
in
how
research
is
conducted

35. Beyond the institute
• The
effects
of
the
democratization
on
science
• Gateways’
role
in
reproducibility

36. Benefits of democratization
New areas of study
• Breakthroughs
don’t
always
come
from
assembling
the
best
and
the
brightest
in
a
closed
room
• Lowering
barriers
to
resources
encourages
experimentation
– 2010
study
from
MIT
and
UCSD
compared
research
from
the
National
Institutes
for
Health
(NIH)
and
the
non-­‐profit,
Howard
Hughes
Medical
Institute
(HHMI)
• Riskier
HHMI
grants
produced
more
innovative
and
influential
research

37. Gateways’ role in reproducibility
Exploring collaboration between SGCI and Whole Tale
• How
can
we
design
gateways
in
support
of
reproducible
science?
With
ties
to
publishing?

38. Continually changing technologies
• Jupyter notebooks
• Gateways
interfacing
to
other
gateways

39. Jupyter notebooks
Wonderful examples of interactive gateway development
https://anaconda.org/jbednar/nyc_taxi/notebook
• Additional
work
needed
to
support
very
large
user
communities?
Very
large
data?

40. Gateways interfacing with
other gateways
Science
Gateway
Platform
as
a
Service
(SciGaP)
provides
application
programmer
interfaces
(APIs)
to
hosted
generic
infrastructure
services
that
can
be
used
by
domain
science
communities
to
create
Science
Gateways.
RDF:
a
directed,
labeled
graph
data
format
for
representing
information
in
the
Web
SPARQL:
query
language
for
RDF
across
diverse
data
sources

41. • US
workshops
– Gateway
Computing
Environments
workshops
since
2005
• European
workshops
– International
Workshop
on
Science
Gateways
since
2009
• Australian
workshops
– IWSG-­‐A
since
2015
• Joint
special
issue
journals
combine
submissions
from
all
of
the
above
Final note: International collaborations

42. • Provide
leadership
on
future
directions
for
science
gateways
• Facilitate
awareness
and
international,
regional
and
national
developments
in
science
gateways
• Identify
and
share
best
practice
in
the
field
• Science
Gateways
Community
Institute (USA)
• NeCTAR (Australia)
• NESI (New
Zealand)
• Sci-­‐GaIA (Africa)
• Academia
Sinica
Grid
Computing
Center (Taiwan)
• Software
Sustainability
Institute (UK)
• VRE4E1C (Europe)
• IWSG (Europe)
• CANARIE (Canada)
• Research
Data
Canada (Canada)
• IEEE
Technical
Area
on
Science
Gateways (International)
International Coalition on Science Gateways
Michelle Barker, Nectar providing leadership
http://www.icsciencegateways.org/

43. Thank you
• I’m
looking
forward
to
a
great
program
today