NSF Support for Advanced Data 

and Software Research 

Cyberinfrastructure

Dr. Stefan Robila

Program Director

Office of Advanced Cyberinfrastructure (OAC)

Directorate for Computer & Information Science & 

Engineering (CISE)

National Science Foundation (NSF)

Dec 5, 2019 IWCPLMI-Workshop, Gaithersburg, MD
Outline • NSF Overview • CISE/OAC • BIO/DBI • ENG/DMREF

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Outline • NSF Overview • CISE/OAC • BIO/DBI • ENG/DMREF

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The National Science Foundation’s mission

“To promote the progress of science; to advance the national 

health, prosperity, and welfare; to secure the national defense...”

4
5
93%

funds research,

education and

related 

activities

$8.1B

FY 2019 

Enacted

50,000

Proposals

evaluated

11,000

awards

funded

2,000

NSF-funded

institutions

359,000

people NSF

supported

$1.2B

STEM

education

236

NSF-funded

Nobel

Prize winners

Most numbers based on FY 2018 activities.

$100M

to seed 

public/private

partnerships

NSF by the numbers

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Outline • NSF Overview • CISE/OAC • BIO/DBI • ENG/DMREF

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8

Alejandro 

Suarez 

Cooperative 

Agreements

Bob 

Chadduck

Ed 

Walker

Amy 

Walton

Vipin

Chaudhary

Kevin

Thompson

Bill Miller 

Science 

Advisor

Beth Plale 

Science 

Advisor

Public Access 

* IPA Appointment

Stefan 

Robila

* *

Micah 

Beck

*

Manish Parashar

Office Director 

Amy Friedlander

Deputy Office 

Director

*

*

Alan

Sussman

NSF Office of Advanced Cyberinfrastructure (OAC)

Directorate for Computer & Information Science & Engineering (CISE)

Mission: Foster a cyberinfrastructure ecosystem to transform science 

and engineering research ... through Research CI and CI research

*
• Lead interagency effort to build and support an expansive CI ecosystem driven by 

research priorities and the scientific process

• Leverage investments by universities, federal agencies, commercial sector

• Establish viable path forward for HPC systems in post-Moore’s Law era; and 

• Increase capacity, capability, and sustainability

• Support a diversity of computational resources to meet the growing demands of 

modern science and engineering 

• Align with the National Strategic Computing Initiative (NSCI) 

CISE/OAC Research Infrastructure Investments

NSF/OAC 

Update

OAC and the 

Research CI 

What’s 

next? 9
Office of Advanced Cyberinfrastructure (OAC)

$224M FY 2018 

research

budget

950

proposals

305

awards

32% Success 

Rate

Source: https://dellweb.bfa.nsf.gov/starth.asp

Foster a cyberinfrastructure ecosystem 

to transform science and engineering 

research...

... through Research CI and CI research

People, organizations, 

and communities

Data 

Infrastructure

Gateways, Hubs,

and Services

Cloud 

Resources 

& Services

CI-Enabled

Instrumentation

Computing

Resources

R&E Networks,

Security Layers

Coordination

& User support

Software and

Workflow Systems

Pilots,

Testbeds

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CI Contributors

Cyber Scientists

to develop

new capabilities

CI Users

Area Scientists

to exploit

new capabilities

CI Professionals

Professional Staff

to deploy & support

new capabilities

OAC

Learning and Workforce Development and Core Research 

Communities of Concern

CyberTraining

NSF 19-524

OAC-Core Research

NSF 19-589

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PI: Zichun Zhong, Co-PI: Jing Hua, Wayne State University [Award #OAC-1910469]

(Co-funded by CBET)

OAC Core: Small: Shape-Image-Text: A Data-Driven Joint Embedding Framework for 

Representing and Analyzing Large-Scale Brain Microvascular Data

A rigorous and scalable computing platform to construct a unified representation

and correlation for large sets of multimodal data (i.e., shape, image, and text)

through fully data-driven joint embeddings.

• Transform a 3D shape with heterogeneous imaging, textual, and other features from 

a large dataset to a novel high-dimensional isometric multi-view probability space. 

• Allow formal and diverse study of geometry scalability and variability in shape 

processing and measurement intensively involved in 3D multimodal data, especially 

the large-scale microvascular networks.

• Significantly increase system’s automation, reduce human’s interventions, and 

discover new knowledge in vascular diseases in the joint embedding space, e.g., 

Microvascular-Multimodal-Embedding.

• Offer an accurate and robust approach for geometric reasoning and quantitative 

assessment of multi-heterogeneous and multimodal data features across a large 

number of objects.

• Provide several educational activities for undergraduate, graduate, and local middle 

school students. Slide Provided by PI
FRONTERA

 New NSF “Flagship” system at TACC/UT-Austin, 

available NOW for large users

 Frontera is the #5 ranked system in the world – and the fastest at any university in the world. 

 Fastest primarily Intel-based system

 Highest ranked Dell system ever. 

 Dell Servers, Intel Processors, provide 39PF peak (double 

precision)

 800+ GPUs for single precision/ML

 50+ PB of storage, 1.5TB/sec I/O 

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Slide Provided by PI
OAC Data and Software Investments

Serves an important and diverse set of research applications and users

• Supports research projects in every NSF science and engineering discipline / Enables new areas of research.

• Cyberinfrastructure for Sustained Scientific Innovation (CSSI). Supports CI/discipline collaborations, cross-disciplinary 

infrastructure, builds on recognized capabilities, tangible products, Cross directorate investments. NSF 19-548 Deadline: 

November 1, 2019

• CSSI Institutes. Focuses on the establishment of long-term hubs of excellence in software infrastructure and technologies, 

which will serve a research community of substantial size and disciplinary breadth.

• CC* (Campus Cyberinfrastructure) - Multi--institution collaborations, cloud resources, sharing mechanisms, innovative 

storage.

Science 

Portals

...

Applications,

Frameworks

Research 

Facilities

campus, national 

resources

NSF-supported 

resources

international

National/International Research and Education Networks, Commercial Networks

private, commercial 

clouds

Federated Storage

OSG Authentication HPC access, 

community

Open system 

software

Resources Integrative

Services

Discipline 

–

specific 

Environments

• Science-driven

• Innovation

• Close collaborations among 

stakeholders

• Building on existing, recognized 

capabilities

• Project plans, and system and process 

architecture

• Clear deliverables

• Measurable outcomes

• Sustained and sustainable impacts

Guiding Principles
• Supports the development and deployment of robust, reliable and 

sustainable data and software cyberinfrastructure

• Brings innovative capabilities towards sustained scientific innovation and 

discovery 

• Provides a cross-directorate opportunity to advance common approaches 

to sustain and innovate research cyberinfrastructures.

• Follows accepted data management and software development practices

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Cyberinfrastructure for Sustained Scientific 

Innovation (CSSI) - Data and Software: 

Elements and Frameworks - NSF 19-548
• Web-based Hydrologic Information System operated by the 

Consortium of Universities for the Advancement of Hydrologic 

Science, Inc. (CUAHSI)

• Gateway for web based computational analysis and modeling 

functionality to overcome desktop compatibility, dependency and 

capacity limitations

• Gives users a way to share datasets, models, and other research 

products

• Provides permanent publication of data and models with citable 

digital object identifiers that can link to literature

http://www.hydroshare.org

OAC-1664061

OAC-1664018

OAC-1664119

2017-2021

ACI-1148453 

ACI-1148090

2012-2017

Better hydrologic forecasting that quantifies effects and consequences 

of land surface change on hydrologic processes and conditions 

by enabling access to and organizing data for integrated analysis and 

modeling Example: Collection of Data 

from 2017 US Hurricanes

OAC Data and Software Programs

OAC – 1835677

2018 - 2023

• Data framework for materials discovery through physics-based 

modeling and machine learning. Create a Materials Knowledge 

Graph (MKG) as a materials data framework by developing an 

extensible semantic infrastructure with ontology-enabled design 

and analysis tools

• Develop broad use and integration with industry, national labs, 

and materials research community

• Drastically reduce deployment time of new materials with 

targeted properties, expand prior work in nanocomposites and 

metamaterials

• Support an all women research team

• Transdisciplinary Education: mechanics, materials science, 

engineering design, computer science, and machine learning

Nanocomposites to 

Metamaterials: A Knowledge 

Graph Framework
Framework: Software: Next-Generation Cyberinfrastructure for Large-Scale 

Computer-Based Scientific Analysis and Discovery 

Forge a collaboration between domain and computing 

experts to build cyberinfrastructure that enables the next 

generation of computer-based scientific analysis/discovery. 

Contributions: 

• Design and implementation of new programming language 

abstractions to allow close integration of high-level 

language features with low-level compiler optimizations. 

• Build upon the Julia programming language and the Juliabased JuMP modeling language for mathematical 

optimization. 

• Focus on three target scientific applications related to 

• (i) the deep decarbonization of electrical power networks, 

• (ii) image analysis of extreme scale astronomical data, and 

• (iii) pharmacometric models for drug analysis and discovery. 

Alan Edelman and Juan Pablo Vielma Centeno, MIT (1835443)

• Over 2532 registered packages

• 7.6M downloads 

• 78% annual growth

OAC Programmatic Highlights - ACCI April 10, 2019 19

Slide Provided by PI
NSF 20-015, Request for Information (RFI) on Data-Focused 

Cyberinfrastructure Needed to Support Future Data-Intensive 

Science and Engineering Research

 Motivation: The challenges of growing volumes of scientific data – their availability, 

transmission, accessibility, management, and utilization – have become urgent and 

ubiquitous across NSF-supported science, engineering, and education disciplines. 

Follow on to NSF CI 2030 RFI, towards further development of the OAC CI “vision” 

(https://www.nsf.gov/cise/oac/vision/blueprint-2019/) 

 Goal: To update NSF on their data-intensive scientific questions and challenges and 

associated needs specifically related to data-focused cyberinfrastructure.

 Emphasis on “cross-disciplinary and domain-agnostic solutions”

Q1: Current or emerging data-intensive/data-driven research challenge(s)

Q2: Data-oriented CI needed to address the research questions/challenge(s)

Q3: Other considerations.

https://www.nsf.gov/pubs/2020/nsf20015/nsf20015.jsp

Please disseminate to your colleagues!
Outline • NSF Overview • CISE/OAC • BIO/DBI • ENG/DMREF

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Division of Biological Infrastructure (BIO/DBI)

Peter McCartney (pmccartn@nsf.gov)

Jean Gao (jgao@nsf.gov)

Empowers biological discovery

• Research Resources (development of informatics and cyberinfrastructure resources; new instrumentation; 

the curatorial improvement and digitization of research collections, including living stock collections; and the 

improvements of research facilities at biological field stations and marine laboratories)

• Human Resources (development of the biology scientific workforce - support fellowships for postdoctoral 

research, sites for research experiences for undergraduates, and research coordination networks in 

undergraduate biology education)

• Centers and Other Mid-to-Large-Scale Infrastructure (Addresses targeted biological questions focused 

toward the needs of a particular research and education community in the biological sciences through 

managing synthesis centers, science and technology centers, nanoscale science and engineering centers, and 

other activities)
Infrastructure Innovation

NSF 18-595 Infrastructure Innovation 

for Biological Research (IIBR):

Bioinformatics Research Program

• Support for research on novel methods, 

approaches, and technologies for 

capturing, representing, and analyzing 

biological phenomena in digital form.

• High emphasis on innovation and 

potential; high tolerance for risk. 

• Success measured by the outcomes of 

the project’s research.

• Most closely related to Computational 

and Data Enabled Science and 

Engineering (CDS&E) but with a focus on 

biological applications.

• T.M. Murali & Jean Peccoud: Automated Prioritization 

and Design of Experiments to Validate and Improve 

Mathematical Models of Molecular Regulatory System. 

(https://peccoud.org/automated_design_experiments/)

• Dannie Durand: Domain Architecture simulator. 

(http://www.cs.cmu.edu/~durand/Lab/research.html)

• Christopher Topp: Algorithms for recovering root 

architecture from 3D imaging. 

(https://www.danforthcenter.org/scientistsresearch/principal-investigators/chris-top)
Infrastructure Capacity

NSF 18-594 Infrastructure Capacity for Biology (ICB):

Cyberinfrastructure for Biological Research 

Program

• Development of robust cyberinfrastructure 

such as databases, software, knowledge bases, 

and other computational resources to enable 

biological research.

• High emphasis on design, engineering, and 

community impact; low tolerance for risk. 

• Success measured by outcomes of the user 

community.

• Most closely related to Cyberinfrastructure for 

Sustained Scientific Innovation (CSSI) but with a 

focus on biological applications.

Galaxy genome analysis software 

(www.galaxyproject.org)

Predictive Ecosystem Analyzer 

(pecanproject.github.io/)

Movebank database for animal 

tracking data. 

(www.movebank.org)
Infrastructure Sustainability

NSF 19-569 Sustained Availability of 

Biological Infrastructure(SABI):

• Limited support for costs of ongoing 

operations and maintenance of mature, 

critical cyberinfrastructure.

• Main emphasis on community impact; 

zero risks because only mature resources 

with established user communities are 

considered. 

• “Criticality” measured by magnitude and 

productivity of the user community.

• Most closely related to Operations & 

Maintenance portion of Major Research 

Equipment and Facilities Construction 

projects (MREFC) such as NEON or OOI.

CyVerse computational infrastructure (formerly iPlant) (www.cyverse.org)

DataDryad repository for research data (www.datadryad.org)

Protein Data Bank repository for 

3D structural biology data 

(www.rcsb.org)
Outline • NSF Overview • CISE/OAC • BIO/DBI • ENG/DMREF

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Designing Materials to 

Revolutionize and Engineer our Future (DMREF)

• DMREF is NSF’s Response to and participation in the Materials 

Genome Initiative

NSF is interested in activities that accelerate materials discovery and development

by building the fundamental knowledge base needed to progress towards designing 

and making a material with a specific and desired function or property from first 

principles.

The DMREF goal is to control material properties through design: this is to be 

accomplished by understanding the interrelationships of composition, processing, 

structure, properties, performance, and process control.
Materials Design: 

Theory, Computation and Experiment

• For DMREF Awards, Theory, Computation and 

Experiment must guide one another in a closed, 

iterative feedback loop

• This loop must accelerate materials design, discovery 

and deployment

• Conventional “Predict – Synthesize – Test” approach is 

linear; the loop must be “closed” by improving models, 

theories or algorithms based on experimental 

measurements

Theory Compu

tation

Experi

ment

Linear path to Materials Discovery

Iterative feedback loop for Materials Discovery
Open Access to Data and Codes

• In the spirit of the MGI, Open Access to data and codes developed in 

DMREF proposals is a key criterion

• Proposals must make data accessible (not simply available), including 

codes, software and algorithms.

• Numerous Open Access/Open Science activities are underway at NSF-

• Keep an eye out for upcoming opportunities!
• Community Study: Creating the Next-Generation Materials Genome Initiative Workforce

• The final report will address the current state of the academic curriculum and training approaches of 

the U.S. workforce to accomplish MGI goals, identify the key MGI skill requirements and needs for 

individuals entering the workforce, and outline curricula development and training guidelines to

improve readiness of current students and the existing professional workforce.

• Led by the Minerals, Metals and Materials Society (TMS)

• Publication: Fall 2019

• Available for free download at www.tms.org/studies

DMREF Focus: Workforce Development
Example Project: DMREF

• DMREF: Data-Driven Integration of Experiments and Multi-Scale Modeling for Accelerated 

Development of Aluminum Alloys

CMMI-1921959

Hufnagel et al, Johns Hopkins University

Co-funded by the Division of Civil, Mechanical 

and Manufacturing Innovation, Division of 

Materials Research and Office of Advanced 

Cyberinfrastructure

3D Characterization

EBSD + Serial Sectioning

High Energy Diffraction 

Microscopy

Automated feedback through 

Materials Semantic Infrastructure

(OpenMSI)

Image-based Modeling

of Deformation
Conclusion

• Science and society are being transformed by compute and data – a 

connected, robust and secure cyberinfrastructure ecosystem is 

essential

• Rapidly changing application requirements; resource and technology 

landscapes

• Our cyberinfrastructure ecosystem must evolve in response

• NSF strives to build a cyberinfrastructure ecosystem aimed at 

transforming science

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Thank You!

Stefan Robila srobila@nsf.gov

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