FY 2021 CIO CDO SAOP Chief Information Officer

FY 2021 CIO, CDO, SAOP Chief Information Officer Chief Data Officer Senior Agency Official for Privacy Handbook 1 Version 11. 1 The Coloring Book Edition

Contents Driving Forces Innovation Strategy and Governance Workforce Data Technology Welcome to NSF Keep in Mind Appendices 2

Welcome to NSF Mission: “To promote the progress of science; to advance the national health, prosperity, and welfare; to secure the national defense…” The Federal Agency charged with funding research in nearly every scientific discipline. 3

Welcome to NSF 1, 800 NSF by the Numbers 11, 300 Awards Funded 303, 000 People NSF supported NSF-funded institutions $922 M 41, 000 STEM education and workforce development Proposals Evaluated $8. 1 B $33. 5 M FY 2019 budget enacted R&D funding through Small Business Programs 92% 242 Funds research, education and related activities NSF-funded Nobel Prize winners (since 1951) Numbers shown are based on fiscal year 2019 activities 4

Welcome to NSF National Science Board (NSB) Organization Chart Office of the Director Diane L. Souvaine Dr. Sethuraman Panchanathan Ellen Ochoa Chair Vice Chair Director F. Fleming Crim Chief Operating Officer Can you find the CIO? ? ? Office of the Inspector General (OIG) National Science Board Office Allison C. Lerner John J. Vesey II Executive Officer Inspector General Directorate for Biological Sciences (BIO) Directorate for Computer & Information Science & Engineering (CISE) Directorate for Education & Human Resources (EHR) Joanne S. Tornow Margaret Martonosi Karen A. Marrongelle Assistant Director Alan D. Tessier Deputy AD Office of Budget, Finance, & Award Management (BFA) Assistant Director Erwin Gianchandani Deputy AD Directorate for Engineering (ENG) Directorate for Geosciences (GEO) Directorate for Mathematical & Physical Sciences (MPS) Sean L. Jones Assistant Director Dawn Tilbury William E. Easterling Assistant Director Acting Assistant Director Sylvia M. James Linda G. Blevins Scott Borg Tie Luo Deputy AD Acting Deputy AD Office of Information & Resource Management (OIRM) Office of Diversity & Inclusion (ODI) Office of the General Counsel (OGC) Office of Integrative Activities (OIA) Office of International Science & Engineering (OISE) Office of Legislative & Public Affairs (OLPA) Chief Information Officer Teresa Grancorvitz Wonzie L. Gardner Office Head Rhonda Davis Lawrence Rudolph Suzanne Iacono Rebecca S. Keiser Amanda Greenwell Dorothy Aronson Office Head/CFO Janis Coughlin-Piester Peggy A. Gartner Deputy Office Head July 2020 Acting Deputy Office Head General Counsel Peggy Hoyle Deputy General Counsel Office Head Directorate for Social, Behavioral, & Economic Sciences (SBE) CIO/CDO Arthur W. Lupia Assistant Director Kellina M. Craig-Henderson Deputy AD Chief of Research Facilities Chief of Science Security Jim Ulvestad CORF Rebecca S. Keiser Samuel B. Howerton Deputy Office Head 5

Welcome to NSF Merit Review Process 0. *Intake Whitepapers, DCL 1. 2. a Solicitation (PIMS) Profile Managem ent(R. gov) ent 2. b Pre-Proposal Compliance Check (R. gov) Proposal Preparation & Submission (Fast. Lane/R. gov) Publish announcements on NSF. gov 16 b. *Recruit REUs, Post Award PO/PI Collaboration 17. Submit Notification/Req uest (Fast. Lane/R. gov) Download Proposal (Self-Service) 5. Proposal Administration (e. Jacket) 7. 6. *Find Reviewers, Invitation Mgnt. (My. NSF) Manual Compliance Check (e. Jacket) Assign Ad Hoc Reviewers, Create Panel (My. NSF) GRFP 15. 16 a. Submit Project Report (R. gov) Link Pubs (+ Data) NSF-PAR 4. 3. 2. c Approve Award (My. NSF) Recommen d Award/Non -Award (e. Jacket) Reimbursem ent Managemen t (Guest) $ Transaction (i. TRAK) 18. Approve Project Report (e. Jacket, My. NSF) 19. Approve Notification/Req uest (e. Jacket, My. NSF) 12. 13. 14. Grant Fund Req & Payments (R. gov/ACM$) Travel Requests (Fast. Lane Travel & Reimbursement) 20. Project Outcomes Report (R. gov) 10. 11 b. 11 a. Review Analysis (e. Jacket) Conduct Panel (Fast. Lane/ IPS) Obligate Panel Costs (Guest) Training NSF. gov $ Transaction (i. TRAK) 21. a Financially Close Award (i. TRAK) 21. b *Close Award (My. NSF) 22. Outcomes (R. gov, NSF. gov Award Search) 9. 8. Reviewer Requests & Panel Letters ( e. Jacket) Panel Management (My. NSF) 23. 24. Archive Jacket (e. Records) Evaluation Assess-ment Capabilities $ Transaction (i. TRAK) Public Access NSF-PAR Data Integration & Mining, Seamless Interface, NSF. gov Publications, Institution Color chart in appendix. 6 Last Updated: 7/08/2020

Driving Forces NSF Strategic Plan Building the Future: Investing in Discovery and Innovation Vision Mission “A Nation that is the global leader in research and innovation” “To promote the progress of science; to advance the national health, prosperity, and welfare; to secure the national defense” Colleges and Universities Teachers and Students Fellows External Trainees Conduct Budget, Conduct Finance & Business Award Support Manageme Conduct nt Manage Science and Information Engineering Technology Research Management Programs Conduct Perform People Legislative Management and Public Manage Affairs Legal Affairs NSF Offices Researchers i Non-profit Academic Organizations Stakeholders Small Businesses and Industry Laboratories, Ships, Planes, Research Platforms 7

Driving Forces RENEWING NSF THE CHARGE Transform NSF into an agile organization capable of responding to the evolving landscape so that we can enable the Nation’s continued global leadership in scientific research and innovation. THE STRATEGY Making information technology work even better for ALL Adapting the workforce and the work Streamlining, standardizing and simplifying processes and practices Expanding and deepening public and private partnerships A RENEWED NSF A culture of continuous learning, appreciation for the value and contributions of each staff member, timeliness and intentionality in responding to changes and strategic decision-making and centralization where appropriate. 8

Driving Forces NSB VISION 2030 This report lays out what the National Science Board believes the U. S. must do to achieve the vision and remain the world innovation leader in 2030. The U. S. has made the investments needed to fuel an innovation economy and remain preeminent in science and engineering. The U. S. remains a magnet for the world’s best talent. The U. S. has increased STEM skills in its workforce creating more opportunities for all Americans. U. S. scientists and engineers are modeling scientific values that are practiced throughout the world. VISION FOR THE FUTURE i The U. S. has created an accessible, attractive S&E enterprise that more closely reflects the nation’s demographic and geographic diversity. U. S. government, industry, and academic partners are working in coordination to realize national R&D priorities and accelerate the discovery-to-innovation cycle. NSF continues to drive U. S. innovation through fundamental research and led the evolution of the global practice of science and engineering. 9

Driving Forces White House Congress OMB OSTP NIST DHS Connect the dots! 10

Driving Forces President’s Management Agenda: Tools for Transformation Mission Service Stewardship People, Workforce of the Future Which way will I turn? IT Modernization i Data, Accountability and Transparency 11

12 Department of Labor • Department of Justice • Department of Interior • • • Small Business Administration • Office of Personnel Management • Nuclear Regulatory Commission • National Science Foundation • General Services Administration • Federal Emergency Management Agency • Agency for International Development • • Environmental Protection Agency • Department of Veterans Affairs • Department of Treasury • Department of Transportation • Department of State • • National Aeronautics and Space Administration Department of Agriculture Department of Commerce Department of Defense Department of Education Department of Energy Department of Health and Human Services Department of Homeland Security Department of Housing and Urban Development * How many can you name? * How many “CFO Act Agencies” are there? CFO Act of 1990 outlined standards of financial management and disclosure. Driving Forces

Driving Forces Brief History of CIO/CDO CFO Act NSF named a “CFO Act” Agency 1990 Govern IT Protect IT Increase CIO effectiveness Clinger. Cohen FISMA FITARA 2002 2014 1996 Information Technology Federal CIPSEA Open SAOP Evidence Data https: //nsf. zoomgov. com/j/1613027927? pwd=b. HZPNkh. LU 2 la. QUtu. REps. Y 3 p. MMCto. UT 09 Act Data Management Strategy 2002 2013 2016 Protect confidential information Share quality data Ensure privacy 2019 Use data to drive decision-making 13

Strategy and Governance Approach: Achieve operational excellence by first focusing on the core (providing smooth reliable operations) while gradually expanding (inserting new approaches and technologies). Technology X X X X Governance X X X X X nce E nab led I T sy stem s IT Vision c Asset X X llige X Data as a Strategi X X X Inte X X Workforce Data X X X FY 2023+ Dynamic and Agile Workforce nt Transpare ernance sive Gov and Inclu NSF’s cutting-edge IT solutions enable the agency to remain agile, thriving in this ever-evolving landscape. FY 2022 FY 2021 You are here Legend: X Color chart in appendix. Initiatives 14

Strategy and Governance People-Centric NSF Data Analytics Ecosystem Strategic Planning Research/Scientific & Education Planning Human Capital & Resources Planning Collaborations/ Partnerships Budget Planning Research Portfolio Analysis Tactical Planning Producers Daily Operations ENABLE NSF MISSION Consumers Program Evaluation & Assessment Data Calls & Budget Requests Communication Resource Management Community Engagement Ad. Com & COVs Workload Analysis Compliance Checking Finding Reviewers Conflict Checking Panel Assignment Proposal Binning Review Analysis Financial Tracking Admin/Financial Review HR IT $ Tools/Platforms/So. Ps Data Polic y 15 Color chart in appendix.

Strategy and Governance FY 21 -22 FY 20 Past, Present, Planned… FY 18 -19 16

Strategy and Governance Annual IT Governance Processes: The players The Public Congress GAO OD and Beyond DHS Capital Planning and Investment Control Enterprise Data Governance & Education (EDGE) Distributed IT Specialists Knowledge Outfit (DISKO) Division of Information Systems Change Control Board (DIS CCB) Maturity Assessment / Baseline Mgmt. Collaboration Tools Modernization Synchronous Meetings Enterprise Inventory Data / Open Data Graphics & Design Share. Point User Group Awards Staff Engagement Improving Science Delivery PARS Retirement Tools / Platform Mobile Apps Platform RAPA One. Drive Migration Proposal Management Efficiencies (PMEWG) Innovation Management (IMWG) Proposal Submission Working Groups OSTP Office of the Director CPIC Investment Owners OMB Financial Services Modernization* (FSMWG) RPA Community of Interest Public Access (PAWG) Web Governance Group* (WGG) Human Resources IT i. TRAK Change Control Board (External) Web Implementation Group (WIG)* Internal Web Group* Requirements Review Board (RRB) Developers * Team names under construction! 17

Strategy and Governance Annual IT Governance Processes OD and Beyond $ $. CPIC Investment Owners Working Groups Developers NY OCT DEC Color chart in appendix. MAR NY NY JUN SEP 18

Strategy and Governance Evidence Act 2018 says: Use data to drive decision-making! Formalize data governance lity Cap abi Eva lua i nt me tio na nd Agency Evaluation Officer ses s Program Representative den EA ce As C Chief Data Officer Evi Performance Officer Working Groups: 1) Maturity Assessment/Baseline Measurement 2) Enterprise Data Inventory/Open Data 3) Staff Engagement 4) Tools/Platform 5) Research and Program Analytics cs Agency Statistical Official Governance isti i e t Sta ES Scienc s c S NC ter for tatisti S Cen ing nal ineer tio Na Eng and Data Statistics Evi Da ta • • den ce 19

Data Identify and Describe Provision and Share Quality Data Acquisition Protect Open Data Management and Oversight Dimensions NSF Staff can find the data they need NSF staff can access data in a format they use NSF staff trust the data and consider it a business asset NSF manages and assimilates the data we have purchased NSF knows what data is made available publicly NSF meets Federal mandates while protecting NSF and its partner’s assets 20

Data Executing a data maturity and evidence capacity assessment is more than just a compliance activity; it can provide sustainable value to help NSF become a more data-driven organization. NSF Integrated Data Maturity and Evidence Capacity Assessment Framework Themes High-level Outcomes Promoting Efficient and Appropriate Data Use Dimensions Assessed Access to the right data with the right analytical tools and data analyses to drive everyday decisionmaking and change based on insights from evidence Governing, Managing, and Protecting Data Building a Culture that Values Data and Promotes Public Use Analytics Capability____ Data Use____ Data Access____ Trusted, protected, understandable, and usable data that support businessdriven information needs Data Governance____ Data Protection____ Data Operations____ Data Quality____ Platform & Architecture____ Data Inventory____ Attitudes and beliefs related to managing and using data to promote advancement of data skills and public accountability Data Personnel____ Data Culture____ Accountability____ Each Dimension will be categorized as 1 -not initiated, 2 -in progress, 3 -implementing, 4 -completed, or 5 - optimizing. Where do you think we fall? (label dimensions from 1 -5) 21

Data Sep 24 th 2019 Color chart in appendix. 22

Technology Components of NSF IT Defined Activities such as vendor management, budgeting, governance, enterprise architecture, program management and reporting IT Management Security and Privacy Activities to prevent unauthorized access, use, disclosure, disruption, modification, inspection, recording or destruction of NSF information People Customers of NSF IT services Devices Computing equipment such as laptops, mobile devices, desktop phones, smartcards (PIV) used by NSF customers to access NSF IT services Suite of IT applications that enable people to interact with and support the accomplishment of NSF’s mission. Examples: merit review applications, financial applications, HR applications, email, desktop applications, mobile applications Data NSF’s digital assets such as electronic Research Proposals, Financial Transactions, Human Capital Information, documents, emails, shared files Infrastructure Collection of hardware, system software, facilities and related equipment used to develop, test, operate, monitor, manage and/or support NSF information technology services Network Collection of devices, including switches and routers, using a variety of protocols and algorithms to exchange information and to transport data to its intended NSF endpoints Color chart in appendix. 23

Technology Build your own action plan! FY 21 IT Action Plan What would you like to see happen next? Security and Privacy People Devices Services IT Management Data Infrastructure Network Submit your ideas through the CIO Home page inside. nsf! 24

Technology: People DISKO’s Objectives: IT people across NSF: • Speak the same language • Understand where to find answers • Understand where we are now and where we are going • Try something new * KO S I D 25 *Distributed IT Specialists Knowledge Outfit 25

Technology: Devices Secure End Point Devices Data stored on One. Drive and on C: drive backed up with DRUVA DO YOU HAVE YOUR SMART CARD? ile b o M ) C s s M e ml ing (S a e S put Com Token 1 04885849 25 Seconds remaining (Soft Token) Access NSF resources remotely using SMC or Virtual Desktop Infrastructure (VDI) (No more : R drive) 26

Technology: Infrastructure NSF’s Data Center 27

Technology: Network Change is coming… Phase III: (Post EIS) move TIC to Co-lo and drop Internet to Headquarters (in process) 28

Technology: IT Management A Look at the TBM Framework What is Technology Business Management (TBM)? ü A framework for managing IT… ü by standardizing and enabling cost transparency… ü and layering on metrics… ü to enable value-based conversations about where to invest in IT Let’s look at an example…Buying a Cake! Step 1: Applying the framework Defining Business / Services / Towers / Cost Pools Business Sheet Cake A Sheet Cake B $100 Step 2: Enabling cost transparency Services $$$ Step 3: Layering on metrics $50 Online Ordering Storefront Services $100 Online $50 Ordering Delivery “Flavor of the Week” Taste Trials Step 4: Enable value-based conversation Towers Sprinkles $5 NSF FY 2017 TBM model in appendix. Milk $5 Baking Powder $5 Cost Pools Flour $5 Vanilla $5 Baking Soda $5 Flour $5 Sugar $55 Oven $5 Eggs $5 Towers $5 $5 Eggs $5 Sprinkles $5 Milk $5 Baking Powder $5 Cost Pools $5 Vanilla $5 Baking Soda Freezer Oven $55 Sugar $55 Delivery “Flavor of the Week” Taste Trials Freezer Should we spend our full budget on the best cake or buy a good cake and use the remaining funds for cookies? Storefront $5 $5 29

Technology: Security and Privacy We take a balanced approach to security… …we want our IT security to be “just right”. 30

Innovation Recipe: Successful Innovation Ingredients: • 1 important problem • Confidence that the problem can be solved Before you begin: State your problem as a hypothesis to either prove or disprove. Directions: 1. 2. 3. 4. Commit yourself (Management buy-in is nice) Ensnare Engage Volunteers (With a taste for this issue) Try something tiny (Bite-sized pieces) Share, compare and combine (Repeat steps 3 and 4 until success is achieved) Serves: Your Agency Created by: You 31

Innovation Local Innovator Tools Classification Model EXPERIMENTATION Experiments in categories such as: a. Experiments in the R&D Lab; or b. Local innovator tool not validated c. Products from Data Scientists Desktop NASCENT Tool has been reviewed and deemed secure to be placed on NSF network; Published on Portal; Follows maintenance and patch sequence MATURE Tool has adequate documentation and training resources Tool has been reviewed by Policy and OGC and approved for wider use ENTERPRISE Tool has wide usage across the Foundation; integral for business use; maintained by voluntary peers INTEGRATED Analysis on business impact and use; user base; metrics on tool usage benefits (such as reduced admin burden); Integrated into: a. Merit review processes and/or b. Enterprise Systems 32

Innovation Implement Vertically Sustainable Innovation • Data driven program management and portfolio analysis, integrated data collection/analytics/reporting • Automate proposal processing (Artificial Intelligence, Machine Learning, etc. ) • Support evidence-based policy-making, strategic planning, and human capital management Tools • Portal (Repository, Reporting) • Collaboration Tools Infrastructure • Secure • Scalable • Accessible People • Training & Education • Workforce Planning & Development Data • NSF Administrative Staff • External Data • Social Media 5. Identify Potential Conflicts 1. Recommend Reviewers • Analytics Innovation Management and Measurement Leadership and Governance (Vision, Objectives & Goals, Alignment to NSF Strategic priorities) 33

Innovation 34 34

Innovation I wish… Imagine this: Digital Intelligence powers NSF websites… 1 Researcher 2 Researcher I can create profiles on NSF. gov to track NSF initiatives and link my social media profiles such as Linked. In, ORCi. D, Google! 6 R 2 D 2 You I can connect with other researchers and collaborate on science topics (like Linked. In)! I can register as a virtual mentor for emerging researchers! I can choose a virtual mentor to coach me in creating highquality research proposals! 3 Public I can use NSF. gov to answer any science & technology-related questions. NSF. gov is the global gateway for science & technology - an intelligent website that harnesses public science contents and can answer any science-related questions (like google). NSF has a behind-the-scene robot (AI) to continuously monitor the direct and indirect influences to assess science security. 5 Staff 4 Researcher I can use advanced analytics to harness the portal data to conduct strategic analysis to help predict future trends and new research investments on an ongoing basis (Idea Machine? ). I can submit a 2 -page research idea to identify relevant research topics, publications, funding opportunities, like-researchers, and possible industry partners. 35

Innovation I wish… Imagine this: Augmented Intelligence facilitates Merit Review… 1 Staff 2 PO I have an AI-enabled risk assessment tool to continuously evaluate the risks for the submitted proposals to help make the right funding decision(s). 6 BFA You In my in-box, I have a set of proposals assigned to me based on my expertise, and in addition, indicates other NSF program(s) it overlaps with! 3 PO After reviewing the assigned proposals, I task the AI tool to bin proposals by science topics, identify reviewers with prescreened conflicts, and suggest the best panel combinations. I can trace every dollar spent in the grant's food chain and help identify opportunities to reduce overheads and mitigates external influences. 5 PO 4 Staff I can asynchronously collaborate with the awardees (PIs)and help them succeed in the NSF funded research. I have predictive and prescriptive tools to analyze overlapping research, diversity and inclusions, external influences, forecast closeouts, and more. 36

Innovation DA TA NSF Digital Twin Replicate – Simulate – Predict! 37

Workforce NSF people drive the mission leveraging IT & Data Mission NSF ata & D IT People 38

Workforce Equitable Human-Centered Design Let’s use the principles of human-centered design to develop equitable solutions. HCD encompasses five practices: empathize, define, ideate, prototype, and test. Iterate… Equality Equity 39

Workforce Categories of data acumen: I use NSF’s data, analytics tools and visualizations I am a strategic leader working to advance use of data agency wide. I code solutions with NSF data and create content for others I use Enterprise Reporting to help answer questions I’d like to learn more but don’t know much yet! I create solutions for my office to advance my office’s strategic priorities Where do you fit in? 40

Keep in mind… The Mental Model A “mental model” is a kind of internal symbol or representation of external reality, hypothesized to play a major role in cognition, reasoning and decision making. Kenneth Craik suggested in 1943 that the mind constructs "small-scale models" of reality that it uses to anticipate events. Wikipedia! • • • My INTERPRETATION A “mental model” is one way of thinking about how people think “Mental models” help me understand describe human behavior and concepts like “meeting expectations” When “reality” matches our “mental model”, our “expectations have been met” DID SOMEONE SAY ICE CREAM PARTY? ? ? Results can be surprising & can lead to emotional responses. (How can anyone be sad about an ice 41 cream party? !)

Keep in mind… No one person has access to all the information necessary to solve the problem. 42

Keep in mind… (Start Here) The Parachute Analogy You are flying at 13, 000 ft. Your target on the ground is not perfectly clear… …you jump from the plane… . . . as you near the ground, be ready for last minute surprises! 43

Keep in mind… Measuring and Accepting Risk Impact Taking risk is like “flying without a net. ”* Very Low little or no impact on achieving outcome objectives Ask yourself: • • “What’s the worst thing that can happen if I try this? “What’s the best thing? ” Probability Very High (81 -100%) Low Mitigation/Contingency Optional, if risk impacts accepted Low minor impact on achieving desired results, to the extent that one or more stated outcome objectives will fall below goals but well above min acceptable levels Medium Mitigation/Contingency Required, unless risk impacts accepted Medium moderate impact on achieving desired results, to the extent that one or more stated outcome objectives will fall below goals but above min acceptable levels High Mitigation/Contingency Required, no option to accept risk impacts High significant impact on achieving desired results, to the extent that one or more stated outcome objectives will fall below acceptable levels High Mitigation/Contingency Required, no option to accept risk impacts Very High severe impact on achieving desired results, to the extent that one or more critical outcome objectives will not be achieved. High Mitigation/Contingency Required, no option to accept risk impacts Then leap. High (61 -80%) Medium (41 -60%) Low (21 -40%) Coloring Scale: • Low = Green • Medium = Yellow • High = Red Very Low (0 -21%) Low Mitigation/Contingency Optional, if risk impacts accepted Medium Mitigation/Contingency Required, unless risk impacts accepted Low Mitigation/Contingency Optional, if risk impacts accepted Coloring Scale: Low • Low = Green Mitigation/Contingency if risk impacts Optional, if risk • impacts Medium Optional, = Yellow accepted • High = Red Low * This is a reference to trapeze performers working up high without a safety net to catch them if they fall. High Mitigation/Contingency Required, no option to accept risk impacts Medium Mitigation/Contingency Required, unless risk impacts accepted Low Mitigation/Contingency Optional, if risk impacts accepted High Mitigation/Contingency Required, no option to accept risk impacts Medium Mitigation/Contingency Required, unless risk impacts accepted 44

Keep in mind… Coordinating Plans U It’s critical to keep everchanging plans aligned to a common goal, and in sync… 2018 Me 2018 2026 Both projects must complete at the same time in order to have value. 2118 45

Keep in mind… Why is work/life balance so important? Our most basic needs are satisfied outside of NSF… …but others might be realized at work. Altruism Fulfilling potential Selfactualization Family Physical safety Physical health Maslow’s Hierarchy of Needs Esteem Feeling respected Love/belonging Friendship Safety Financial safety Physiological 46

Draw yourself here. * NSF * 47

So, what do U think? Thank you U From the CIO, CDO, SAOP, the Office of the Director, the National Science Foundation, the Executive Branch of the Federal Government of the United States of America, the continent of North America, The Coloring Book Edition the planet Earth, the Milky Way Galaxy , the Universe… 48

Appendices • Components of NSF IT Defined • FY 19 Action Plan • IT Vision • Governance – Annual IT Governance Process • So what does TBM look like for NSF? (An example) • NSF Merit Review Process by System (June 2019) • NSF Business Enterprise Information Model (Sep 2019) • FY 19 NSF Career Compass Challenge • Seven possible FY 2020 Workforce Modernization Efforts • Possible future access to research results 49

FY 20 Action Plan q Update NSF IRM Plan licenses and tools ü Implement regular IT investment reporting to CPIC q Complete refresh of IT governance charters q Ø ü ü Complete annual operating system upgrades Begin implementation of Enterprise Mobile Apps Platform Select primary and secondary Next Generation collaboration meeting tools Rollout MS Teams* Mission & Mission Support Services ü Implement the ACS thematic code into NBA applications ü Continue retiring client/server applications from NSF staff desktops (e. g. , UPM, Awards) q Continue check and track enhancements to begin positioning NSF for PRIM ü ü q Ø ü decommissioning Implement Document Routing System (DRS – formally known as Form 10) Expand presence of beta. nsf. gov by migrating additional content Complete Duplicate PI Account Reconciliation Continue development of a Review Analysis Solution Support new Performance Management system pilot* Data & Analytics Services q ü ü q Implement data lake prototype Expand capability of data scientist desktop Roll out enterprise Tableau for HR data visualization Expand Suggest Reviewer pool by adding external data ü Begin setup of lab environment to experiment with emerging technologies ü Develop migration plan and begin moving files from R: Drive to One. Drive q Begin implementation of Self-Service Portal for Local Innovations Ø ü ü Ø Ø ü ü ü Continue expanding NSF Public Access Repository Address high priority special character related system issues Prepare for federally mandated changes for UEI Prepare for federally mandated changes for G-Invoicing Pilot NASA e. Books on an NSF Panel Enable Collaborative Proposals from Multiple organizations in Research. gov Continue expanding proposal submission capabilities in Research. gov Begin accepting the new NSF approved Bio Sketch and Current and Pending Support formats ü Implement additional BOTS q Begin development of a MOU creation and routing tool* ü q ü ü Incorporate text analytics search in Suggest Reviewer Dashboard Build Merit Review Reporting (MRR) on Cloud architecture Add new data sources, reports and dashboards (e. g. , COV & VACS) Complete UTF-8 character set conversion for Sybase Infrastructure ü Begin migrating Merit Review applications to the Cloud q Continue retirement of end-of-life software (e. g. , Glassfish, Java 1. 6 Windows Server 2008, RHEL 6, Solaris 10) Network ü Upgrade network components (F 5 s, switches) q Begin relocation of TIC to co-location site q Planned ü Completed * Added during FY 20 ü Continue automation of software testing and deployment ü Begin migrating the Dev. Ops tools to the NSF Cloud ü Increase capacity of VDI* q Increase capacity of VPN* Ø Moved to FY 21 28/59 Develop approach for preventing Internet access from Servers Implement a solution to control and monitor WADM user access Pilot break and inspect for encrypted network traffic Develop approach for data loss prevention on NSF workstations Strengthen definition and implementation for secure configurations Pilot enterprise data masking utility Ø Provide mechanism for centralized purchase of enterprise democratize IT governance q Continue IT workforce planning efforts ü Deploy CIO collaboration site to further Devices & Enterprise Services ü q Ø Ø ü Ø IT Management q Begin to implement next phase of Customer Relationship Management tool Continue adding Cloud Security Tools Implement Encryption for Data in Transit Implement Encryption for Database Connections Complete deployment of advanced malware protection on NSF workstations q Provide Robotic Process Automation (Bots) training materials to staff Ø Conduct review and analysis of agency IT service offerings Security & Privacy ü q Ø ü People 47% complete July 7, 2020 50

CIO/CDO Role Approach: Achieve operational excellence by first focusing on the core (providing smooth reliable operations) while gradually expanding (inserting new approaches and technologies). Technology X X X X Governance X X X FY 2023+ FY 2021 nce E nab led I T sy stem s IT Vision c Asset X X llige X Data as a Strategi X X X Inte X X Workforce Data X Dynamic and Agile Workforce nt Transpare ernance sive Gov and Inclu NSF’s cutting-edge IT solutions enable the agency to remain agile, thriving in this ever-evolving landscape. FY 2022 You are here Legend: X Initiatives 51

Annual IT Governance Processes OD and Beyond $ $. CPIC Investment Owners Workin g Groups Developers OCT DEC MAR JUN SEP 52

So what does TBM look like for NSF? If NSF invested $100 on Information Technology Business How does NSF want to view the “business layer”? $100 Services $9 Bus Apps End User Platform $66 Infrastructure $25 Delivery Emerging End User $9 Application $46 Platform $7 Delivery $14 Output $1 Storage $2 Compute $2 Data Center Network $6 Cost Pools $3 IT Security $2 IT Management IT Towers $8 $100 53

NSF Merit Review Process (DRAFT) 0. 2. a 1. Profile Manage ment (R. gov) Solicitation (PIMS) *Intake Whitepapers, P DCL T P Pre. Proposal Compliance Check T (R. gov) *Recruit REUs, Post Award P PO/PI Collaboration 3. Proposal Preparation & Submission (FL/R. gov) Download Proposal (Self. Service) T T Publish announcements on NSF. gov T 16 b. 2. c 2. b 15. 14. 13. Approve Award (My. NSF) Recomm end Award/ Non. T Award (e. Jacket) T Reimburs ement Manage ment (Guest) $ Transaction (i. TRAK) T $ Transaction (i. TRAK) 17. Submit Notification/ Request (Fast. Lane/R. gov) T 18. T Approve Project Report (e. Jacket, My. NSF) Approve Notification/ Request (e. Jacket, T My. NSF) $ Transaction (i. TRAK) 5. Post. Submission Compliance Check Proposal Administration (e. Jacket) T P LEGEND 7. 6. *Find Reviewers, Invitation Mgnt. (My. NSF) Assign Ad Hoc Reviewers, Create Panel (My. NSF) T P GRFP Submit Project Report (R. gov) T 4. T T 16 a. Link Pubs (+ Data) T NSF-PAR Last Updated: 8/10/2020 12. Travel Requests (FL Travel & Reimbursement) T 11 b. Review Analysis, Context P Statement , Panel Summary 11 a. 10. Conduct Panel (Fast. Lane/ IPS) Obligate Panel Costs (Guest) T P T Training NSF. gov 19. 20. Grant Fund Req & Payments (R. gov/AC T M$) Project Outcomes Report (R. gov) T T $ Transaction (i. TRAK) 22. *Close Award (My. NSF) T T 8. Panel Management (My. NSF) No immediate technology risks T Technology will be outdated in 1 to 2 years T At risk, outdated technology P Process gaps that adds burden P Process gaps that adds significant burden T $ Transaction (i. TRAK) 21. a 21. b Financially Close Award (i. TRAK) 9. Reviewer Requests & Panel Letters ( e. Jacket) T T Outcomes (R. gov, NSF. gov Award Search) 23. 24. Archive Jacket (e. Records) Evaluation Assessment Capabilities T P Public Access NSFT PAR Data Integration & Mining, Seamless Interface, NSF. gov Publications, Institution Investment Owners : Financial Services Modernization (FSM) Proposal Management Efficiencies (PME) Public Access Working Group Web Implementation Group (WIG) Enterprise Data Governance (EDGE) Innovation Management Group (IMG) Part - PME 54

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FY 19 NSF Career Compass Challenge Imagine a Federal workforce that is a model for other governments and for industry. Imagine a Federal workforce that functions as an agile integrated team within and between Agencies. Imagine that employees move freely in-and-out of the Federal workforce. U Today Imagine that you, a Federal employee, have the power to chart the path of your own career, and dedicate time (each day) to both executing your current job functions and building skills needed for your next job. Imagine that you carry on a continuous conversation with your leadership. Imagine an app that: • knows your skills, strengths and preferences, • recommends possible future careers, • suggests growth paths (class-work, detail opportunities, work experience, advanced degrees, and more. . . ) Imagine that. Future 56

Seven possible FY 2020 Workforce Modernization Efforts 1. Liberate HR Data 2. Data Science Upskill Experiment 7. Focus on Underrepresented Groups 6. Create Reskilling Roadmap Skills Bank * Growth Mindset * Ever-ready Workforce * Universal Message *… 3. Develop introductory courses for “New” skills 4. Conduct RPA Upskilling Pilot 5. Analyze what has already been done January 2020 57

Data Workflow including Possible Future “Results ID” University 2 1 Investigator Proposal 3 Proposal ID 5 Experiment Publication ID 4 Reviews Results ID* 6 Award Research Results 7 Report 8 Publication Publisher Public 58

People-Centric NSF Data Analytics Ecosystem Consumers Producers 59