Team Sentinel

● Team members:○ Jared Dunnmon○ Darren Hau○ Atsu Kobashi○ Rachel Moore

● Cumulative # of interviews: 73 + 12○ Users: 3 Experts: 9

● What we do: Enable rapid, well-informed decisions by establishing a common maritime picture from heterogeneous data

○ Open and automated data aggregation (i.e. incorporate open source data)○ Flexible layering and filtering with improved UI/UX○ Enhanced intel through contextualization and easily accessible, common database○ Identifying deviations from baseline by utilizing historical data

● Why it matters:○ Information overload○ A2/AD prevents deployment of traditional ISR in a timely manner○ Data aggregation platforms and database access in PACOM appear extremely manual

● Military Liaisons○ --- (Colonel, US Army)○ --- (Commander, US Navy)

● Problem Sponsor○ --- (Lieutenant, US Navy 7th Fleet)

● Tech Mentors include:○ --- (Palantir)

QUOTE OF THE WEEK

“THAT’S CLASSIFIED.”

Contents

1. Customer Discovery

2. Mission Model Canvas

3. Value Props

4. Mission Achievement

5. MVP

Hypotheses Experiments Results Action

Significant data about many data fusion programs available at the unclass level

IN PROGRESS

- Interviews with a variety of stakeholders at PACOM-MVP from last week: asking our contacts to fill out a spreadsheet indicating their awareness of different data fusion tools

- Suboptimal response levels on ask from last week (possibly due to major 7th Fleet operations)-Will continue this week

- Visit to San Diego- Continue pushing this efforts this week

IUU fishing problem is a good proxy problem for 7th Fleet MDA with more widely available data sources

PARTIALLY VALIDATED

- Interviews with PACOM COP and GCCS expert-Interviews with IUU fishing stakeholders with previous Navy experience-Research on existing IUU fishing tools

- Access to open-source visualization/analysis tool from UN Fishing and Agriculture Organization- Understanding of ship behavior patterns (AIS on buoys, insights on ship tracking/movements)-Won’t be able to understand everything Navy does on MDA analytics, but a good start

- Working with nonprofits to get access to marine ship data

-Use IUU fishing problem to demonstrate rapid development of flexible data fusion/analytics capability

Customer Discovery

Hypotheses Experiments Results Action

Physical “sensors” are the only way to add new data feeds for 7th Fleet

INVALIDATED

- Interviews with NPS researchers-Interview with PACOM SME on GCCS and COP-Interview with MFIC personnel

- Distributed marine sensors are one possible way to think about this capability-Drones + ship recognition emerging-Social media an emerging data source

-Considering integration of these additional future/non-traditional data sources into our MVP

Flexible integration of available sensor feeds into both COP and intel functions would be a useful capability

VALIDATED

-Interviews with NPS personnel researching applicability of UAVs to MDA-Interviews with IUU (Illegal, Unreported, Unregulated) fishing stakeholders on analog problem-Interview with PACOM SME on GCCS and COP

- Right now, a key general problem (exacerbated by A2/AD) is that data feeds that are available can change rapidly- COP and intel systems that allow for flexibility in visualization and analysis enable new sensor prototyping and effective use of existing data

- Focusing MVP on a way to flexibly and seamlessly use whatever data is available (algorithms and visualization)

Customer Discovery

Research- Interviews to assess needs, organizational dynamics, procurement strategy- Site visits to see current practices-Understanding current workflow

Connecting People and Programs- Ensuring tool developers and users are aware of one another- Finding functional gaps to fill

Prototype- Compile existing data resources- Create representative “fake” datasets- Evaluate relevant ML algorithms for prediction/rules for push alerts-Create demo of flexible data fusion/analytics for IUU fishing

Strategic Decision Makers

Analysts (N/J2)

Operators (N/J3)

Planners (N/J5)

IUU People (working on it)

- Timely operational decisions

-Common and consistent view of the Area of Responsibility (AOR)

-Flexible integration of new feeds into COP and analytics

- Decreased time to predict hot spots, ID & differentiate threats

- Reduced time for analysts to find information and draw conclusions

- Prototype operability + demonstrated scalability

Data Fusion/Sensor Integration Software

- Build solution that integrates with current systems (e.g. GCCS, QUELLFIRE, FOBM, EWBM, INSIGHT)

- Work with PMs and key influencers to determine optimal funding/dissemination avenues and integration with current tool pipeline

- Deploy prototype, confirm buy-in and update features

- Scale deployment, improve product as necessary

Fixed- Buying proprietary data- Software tools- Evaluation of commercial products

Prototyping- Existing sensor platforms and feeds- Academic research- Existing data fusion platforms

Scaling- Available commercial + military data- Existing database tools (Palantir, AWS)

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 and operators from N3 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if we want to leverage their platforms

-Need support of existing PMOs/S&T personnel to make sure we’re not duplicating work

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key PartnersMilitary- 7th Fleet + designated sponsor- NPS/ONR- Acquisition Personnel- Existing PMOs/PORs- Other Fleets

Commercial- Distributed sensor platform companies (i.e. Saildrone, AMS)- Data analytics (i.e. Palantir, Google)

Academic- Universities (i.e. University of Hawaii)- National Labs (Lincoln Labs, Sandia)

Other- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)- Disaster relief agencies

Mission: Enabling Rapid, Well-Informed Decisions from Heterogeneous Data

Testing- 7th Fleet assets for pilot- Research barge- Access to model analyst data interface and in-development tools- Access to sample incoming sensor feeds

Variable- Travel for site visits, pilots- R&D personnel-Development

IMPROVE TACTICAL AND STRATEGIC DECISION

MAKING VIA BETTER DATA HANDLING

(1) Rapid Strategic Decisionmaking via Improved Reporting and Coordination

(2) Improved Tactical Decision Making via Timely, Accurate, Information Sharing

(3) More Effective Analysis via Searchable, Visualizable, Source-Flexible Data Integration (Layering & Filtering)

(4) Predictive Intel and Alerts (e.g. Machine Learning) Flexibly Applied to Available Data and Rapidly Updateable to Account for New Sources

ENHANCE INCOMING DATA STREAMS

(1) Improved Collection of Existing Data Streams (e.g. Fishing Broadcasts)

(2) Painless Incorporation of Multiple New Sensing Modalities

(3 Integration of Incoming Data Streams with Existing Object-Oriented Database

Products& Services- Timely data- Good UI/UX

for presenting data

- Streamlined reporting process

- Improved coordination across ranks

- Utilizes current tool pipeline

Customer Jobs

Gains

Pains

Gain Creators

Pain Relievers

- Good UI/UX- Platform

incorporates more data streams

- Platform is robust and can handle drop out of data streams

- Allocate assets- Identify,

eliminate threats

- Predict hot spots

- Safety of team- Projecting

peace, stability in region

- More informed decisions

- Faster decisions- Decisions made

on most up-to-date info

- Poor quality/lack of data

- Latency of data -> insight

Admiral/Strategic Decision Maker

Value Proposition Canvas

Customer persona:

● 3 or 4 star admiral● Born in late 1950’s● Have their own office on-base● Gives out challenge coins

● 30,000 ft view thinker● Spent entire professional career

in Navy (deeply ingrained culture)

Products& Services

- Contextualized, object-oriented database

- Algorithms for processing, analyzing data

- Ability to search for trends across database

- Integration of disparate data sources

- Automation of data analysis- Improved UX/UI- Predictive notifications- Filtering and layering

features- Tool architecture is flexible

and intelligent

Customer Jobs

Gains

Pains

Gain Creators

Pain Relievers

- Compatible data format

- Incorporate multiple data streams with existing object-oriented database

- Integration into current processes is simple

- Collect & analyze data

- Communicate findings

- Piece together contextualized awareness

- More actionable insights- Faster identification & response times- Easy-to-use- Information continues to be processed

and visualized even if data streams are added/dropped (no Christmas Light effect)

- Incorporation of context is manual/mental

- Poor quality / lack of data- Latency of data -> insight- Long onboarding processes

Analyst (N2)

Value Proposition Canvas

Customer persona:● Sits in front of computer all day● Job is normally boring with bursts

of excitement● Some may have constantly

varying hours/schedules

● “19 year old from Oklahoma”● Regimented schedule● May or may not like what they do

Products& Services

- N/A

- Actually a common operating picture!

- Data is actually synced across databases

- Tool architecture is flexible and intelligent

Customer Jobs

Gains

Pains

Gain Creators

Pain Relievers

- No hardware to deploy so no risk of asset or personnel loss

- Fewer change orders- Training and integration

with current processes is simple

- Utilize assets and human capital in order to obtain ISR data on adversary or regions of interest

- Timely and enhanced allocation and deployment of assets

- Information continues to be processed and visualized even if data streams are added/dropped (no Christmas Light effect)

- High manpower, time- Operator error- Safety concern for

deploying in unfriendly territory

- Struggle to redeploy systems on short notice (<12 hours) = frustration

- Long onboarding processes

Operations (N3)

Value Proposition Canvas

Customer persona:

● General sense that N2 and N6 “work” for them

● “19 year old from Oklahoma”● Regimented schedule

● May or may not like what they do

(green indicates that validation is still needed)

Beneficiary Mission Achievement

Intelligence Analysts

- Decreased time to aggregate data, classify and differentiate surface vessel activity, and present conclusions.

- Flexible integration of new feeds into analytics

Operators - Real-time (no lags of 2-6 hours!) common operational picture (COP) of surface vessel activity with notifications of abnormal activity based on algorithms and analyst conclusions.

- Flexible integration of new feeds into COP

Strategic Decision-maker

- Up-to-date information on activity in AOR- Better understanding of what data contributed to analysis in CUB.

Mission Achievement

MVP

Pew Charitable Trusts Virtual Watch Room

MVP

Global Fishing Watch

MVP: Modular Intake, Algorithm, and Display

MVP: Modular Intake, Algorithm, and Display

MVP: Modular Intake, Algorithm, and Display

MVP: Modular Intake, Algorithm, and Display

Thank you!

Any questions?

Customer Discovery - Get/Keep/Grow Diagram

Awareness Interest Consideration Purchase Keep Unbundling Up-sell Cross-sell Referral

Activity & People

- Evangelist & advocate from originator Flt- ???

Corey Hesselberg, CDR Jason Schwarzkopf, MIOC watch standers

- Buy-in from flag officers- ADM Swift, VADM Aucoin, RADM Piersey

- N8/9- Dave Yoshihara (PacFlt N9)- 7th Fleet ???

- Maintainers (N6)- Bob Stevenson (PacFlt N6)- 7th Fleet ???

N/A Expanding COP & intel extensions / functionality within 7th Fleet

Expanding user base within 7th Fleet

Expanding tool set to other fleets

Metrics % people who have heard of program before vs after *how to reassess?

# people who say “we want this”

Seems binary… any recommendations?

# Systems outfitted

?? ?? ?? # users within 7th Fleet using tool

# fleets using tool

Map of System Functions and Needs

QUELLFIRE

GCCS (1)

FOBM

STORAGE/COMMS

CST

GCCS (3)GCCS (2)

STORAGE/COMMS

STORAGE/COMMS

Sensors Sensors Sensors

.oth-.json Translator

Visualization

Analytics

Ship-to-Ship Sharing

Long-Term Storage

KEY NEEDSFUNCTIONS

& PROGRAMS

SHIP 2 SHIP 3SHIP 1

MVP: Software Domain Awareness

Program POC OrganizationFunction & Goals

To be used by whom?

Security Level Status Contract History Inputs

Technical Details

CSII

Insight

MTC2

Quellfire

DCGS-N Increment 2

C2PC

HAMDD

SeaVision

GCCS

EWBMRC2 (Resilient C2)

Sample In-Development Product: ONR/CTI EWBM Tool

MVP (3 weeks ago)

MVP (3 weeks ago)

MVP (3 weeks ago)

MVP (4 weeks ago)

AIS Weather

MVP (4 weeks ago)

AIS Weather

MVP (4 weeks ago)

AIS Weather

Customer Workflow

N2

N3

N2(“owns”

the intel)

N3(“owns”

the assets)

Ready-To-Use DataDeployment

Data Acquisition

Data Analysis

Data

Order/Decision

Customer Workflow

Key Acquisition Paths

● Several potential deployment strategies

○ Linking in with an existing POR (PMW-150, etc.)

■ Pros: Allocated funding, long-term integration plans

■ Cons: Long timescale, getting in the door

■ POCs: ONI, SPAWAR (Stan Kowalski), Primes

■ Source of Excitement: TBD

○ Rapid Acquisition Pathways (Limited Objective Experiments, Rapid Reaction Technology Office)

■ Pros: Speed, Close to user, Don’t have to go through Navy (other services work)

■ Cons: Limited spending authority

■ POCs: 7th Fleet (Jason Knudson), DHS (Chuck Wolf)

■ Source of Excitement: Rapid deployment, changed acquisition model

○ DARPA

■ Pros: Development mindset, existing programs (Insight) that are well-aligned, deployment authority/capability to pay for deployment to end-users

■ Cons: stepping on toes, limited number of PMs

■ POCs: Craig Lawrence (ADAPT)

■ Source of Excitement: Directly solving a problem as opposed to many-year process

Sample Deployment Path (Software, POR Path)

1. Operational testing to make sure meets military specs (engage SPAWAR for this)a. Ensure NSA-standard Information Assurance (IA)

i. Lock down system and codeii. Make sure no category 1,2,3 in code - backdoors, exceptions, etc.

b. Observe appropriate NIST protocols (TBD)2. First, limited deployment to evaluate functionality (on testbed system or specific asset)3. Then, if integrated into a POR:

a. Deployed on whatever platform is neededb. Moves into sustainment phasec. Think about disposal & replacement--we want continuous improvement!

4. IT installs where requireda. Technical support install software and make sure up and runningb. Maintains communications systems and networks

5. Personnel training for system operation and maintenancea. CTMs focus on maintaining classified systems & special collections abilities

WE WILL BE GETTING MORE DETAIL ON THIS GOING FORWARD!