Dod digital engineering
Skill jgsystemsconsulting/jgs-se-knowledge-packs/packs/dod-digital-engineering
46 agent knowledge packs distilling vetted, licence-clean systems-engineering standards (NASA, DoD, FAA, NIST, GAO, SEBoK) into on-demand Claude skills.
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Knowledge base from the DoD Digital Engineering Strategy (2018, OUSD/ODASD(SE)). Use for the Department of Defense's five digital engineering goals — (1) formalize the development, integration, and use of models; (2) provide an enduring authoritative source of truth; (3) incorporate technological innovation; (4) establish supporting infrastructure and environments; (5) transform the culture and workforce — plus their focus areas, the document-to-model and design-build-test→model-analyze-build shifts, model formalisms/provenance, governance and access control of the authoritative source of truth, and the coordinate→plan→pilot→sustain rollout. A vision-and-policy strategy, deliberately non-prescriptive. Does NOT provide a how-to method, tool tutorials, MBSE/SysML mechanics, or implementation-plan content; thin on metrics, acquisition-policy detail, and step-by-step procedure. Excludes the CAC-gated Digital Engineering Body of Knowledge (DEBoK).
SKILL.md
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DoD Digital Engineering Strategy (2018)
Source: OUSD R&E / ODASD(SE) (US Government work, public domain) | Chapters: 7
When to use
Use this skill when you need to reason about the Department of Defense Digital Engineering Strategy (2018, OUSD/ODASD(SE)) and its five goals: (1) formalize the development, integration, and use of models; (2) provide an enduring authoritative source of truth; (3) incorporate technological innovation; (4) establish supporting infrastructure and environments; and (5) transform the culture and workforce. This pack also covers model formalisms, provenance, governance and access control of the authoritative source of truth, and the coordinate-plan-pilot-sustain rollout sequence. It is a vision-and-policy source, not a how-to method or tool tutorial.
Prerequisites: none, plain Markdown; no MCP server, API key, or licence tier needed at runtime.
How to Use This Skill
- Without arguments — load the Core Frameworks below: the definition of digital engineering, the five goals, and the central mental-model shifts.
- With a topic — ask about a goal or focus area (e.g. "authoritative source of truth", "model formalisms", "Goal 4 infrastructure", "culture and workforce"), a shift (document-to-model, model-analyze-build), or a cited example (USS Ford, A-10, ERS, NAVAIR, Army LPDM/ePDM).
- With a chapter —
ch01(intro/vision + the five goals),ch02–ch06(Goals 1–5),ch07(next steps + Appendix 1 summary). - Read it as intent, not procedure — the Strategy is a non-prescriptive "living document"; the concrete "how" lives in DoD Component implementation plans, which this pack does not contain.
Supporting files: glossary.md, patterns.md, cheatsheet.md.
Prerequisites: none — plain Markdown; no MCP server, API key, or licence tier needed at runtime.
Core Frameworks & Mental Models
What digital engineering is
Digital engineering is an integrated digital approach that uses authoritative sources of system data and models as a continuum across disciplines to support lifecycle activities from concept through disposal. The 2018 Digital Engineering Strategy — authored by ODASD(SE) with government, industry, and academia stakeholders — is the governing document. It is deliberately a vision and a compass, not a checklist: explicitly non-prescriptive and meant to evolve, it sets shared direction while the concrete execution lives in DoD Component / Service implementation plans.
The driver is mission urgency: deliver capability to the warfighter faster amid exponential technology change, rising complexity, tight budgets, and compressed schedules — problems the legacy linear, document-heavy, stove-piped process handles poorly. The system of interest is scoped broadly: systems of systems, systems, processes, equipment, products, and parts.
The Five Digital Engineering Goals
The entire Strategy is organized around five goals (Section IV summary; each expanded into focus areas in Section V):
- Formalize the development, integration, and use of models — making modeling deliberate practice that informs enterprise- and program-level decisions. → ch02
- Provide an enduring, authoritative source of truth — move the primary means of communication from documents to digital models and data. → ch03
- Incorporate technological innovation to improve the engineering practice (beyond traditional model-based methods). → ch04
- Establish a supporting infrastructure and environments so stakeholders can perform activities, collaborate, and communicate. → ch05
- Transform the culture and workforce — equipping the Department to adopt digital engineering, and sustain it, across the lifecycle. → ch06
Read goals 1–4 as building the machine (models, a trusted data backbone, infused technology, the environment to run them in) and goal 5 as building the people who run it. Adoption is the gating risk.
Goal → focus-area structure
Each goal decomposes into numbered focus areas (Appendix 1 is the full map):
- Goal 1: 1.1 plan for models · 1.2 develop/integrate/curate models · 1.3 use models in decisions.
- Goal 2: 2.1 define the authoritative source of truth · 2.2 govern it (access, controls, governance) · 2.3 use it across the lifecycle.
- Goal 3: 3.1 establish an end-to-end digital engineering enterprise · 3.2 use technological innovations to improve the practice.
- Goal 4: 4.1 IT infrastructures · 4.2 methodologies · 4.3 secure infrastructure & protect IP.
- Goal 5: 5.1 improve the knowledge base · 5.2 lead & support transformation · 5.3 build & prepare the workforce.
Key constructs
- Authoritative source of truth (AST) — the single, trusted central reference for models and data; captures the current state and history of the technical baseline, gives traceability as the system evolves, and propagates changes downstream. Its authority comes from governance: governance → data quality → stakeholder confidence → data-driven decisions.
- Model formalisms — the quality rules (syntax, semantics, lexicons, standards) that let independently authored models combine into one coherent digital representation.
- Provenance and pedigree — recorded model origin and lineage that, with V&V-based reviews, make a model trustworthy and reusable. Trust is engineered, not assumed.
- Continuum of models — the same authoritative models carried and reused concept→disposal, not rebuilt at each phase boundary.
The mental-model shifts
- Documents → models/data as the primary means of communication; documents become generated views, and stakeholders shift from accepting documents to accepting models.
- Design-build-test → model-analyze-build — analyze and prove decisions in a virtual environment before physical build and fielding (virtual-first).
- Many copies → one source of truth — ask "is this traced from the AST?" not "which copy is current?"
- Stove-piped IT → a consolidated, collaborative, trusted environment (Goal 4's diagnosis and target).
- Lock-in → standards & interfaces — bet on the seams between tools (standards, data, formats, interfaces), not a vendor product.
- One-time rollout → sustained socio-technical change — culture is the operating system (Goal 5).
Rollout: coordinate → plan → pilot → sustain
The Strategy sequences four next steps: coordinate (ODASD(SE) convenes a summit and runs the standing Digital Engineering Working Group), develop implementation plans (owned by the DoD Components), implement pilot programs (learn/measure/optimize before scaling into major programs), and sustain (policy, guidance, training, continuous improvement). Ownership is distributed (Components own plans); coordination is central (ODASD(SE) is a gap-closer, not a gatekeeper).
Chapter Index
| # | Section | Key content |
|---|---|---|
| ch01 | Introduction, Purpose & Vision | What digital engineering is; why now; the five goals introduced; the non-prescriptive "living document"; design-build-test→model-analyze-build; system of interest |
| ch02 | Goal 1 — Formalize Models | Plan/develop/use models (1.1–1.3); model formalisms; provenance & pedigree; model-based reviews; the authoritative source of truth foundation; USS Ford example |
| ch03 | Goal 2 — Authoritative Source of Truth | Define/govern/use the AST (2.1–2.3); governance, access & controls; technical baseline; document-to-model acceptance shift; Army LPDM/ePDM example |
| ch04 | Goal 3 — Technological Innovation | End-to-end digital enterprise (3.1); use of data, human-machine interaction, technology insertion (3.2); evolving digital representation; A-10 digital thread |
| ch05 | Goal 4 — Infrastructure & Environments | IT infrastructure (4.1); methodologies (4.2); cybersecurity & IP protection (4.3); standards-over-tools; modular/cloud; ERS example |
| ch06 | Goal 5 — Culture & Workforce | Culture as shared values/behaviors; knowledge base & standards gap (5.1); transformation as change management (5.2); preparing the workforce (5.3); enablers; NAVAIR example |
| ch07 | Next Steps & Appendix 1 | Coordinate→plan→pilot→sustain; ODASD(SE) coordination & DoD Components; DEWG; the goal/focus-area summary table |
Topic Index
- A-10 example / digital thread → ch04
- Access and controls → ch03
- Appendix 1 (goal/focus-area summary) → ch07
- Authoritative source of truth (AST) → ch03, ch02
- Continuum of models → ch02, ch01
- Culture (shared values and behaviors) → ch06
- Cybersecurity (in digital engineering) → ch05
- Define / govern / use the AST (2.1–2.3) → ch03
- Design-build-test → model-analyze-build → ch01
- Digital artifacts → ch03
- Digital engineering (definition) → ch01
- Digital Engineering Strategy (2018) → ch01, ch07
- Digital Engineering Working Group (DEWG) → ch07
- Document-to-model shift → ch03
- End-to-end digital enterprise → ch04, ch01
- Engineered Resilient Systems (ERS) → ch05
- Evolving digital representation → ch04
- Five goals (summary) → ch01, ch07
- Focus areas (structure) → ch07
- Formalize models (Goal 1) → ch02
- Governance (of the AST) → ch03
- Human-machine interaction → ch04
- Infrastructure and environments (Goal 4) → ch05
- Intellectual property protection → ch05
- LPDM / ePDM (Army example) → ch03
- Methodologies (Goal 4.2) → ch05
- Model formalisms (syntax/semantics/lexicons) → ch02
- Model provenance and pedigree → ch02
- Model-based reviews and audits → ch02
- NAVAIR SE Transformation → ch06
- Next steps (coordinate/plan/pilot/sustain) → ch07
- ODASD(SE) / DoD Components → ch07, ch01
- Pilot programs → ch07
- Standards and interfaces (over tools) → ch05
- System of interest → ch01
- Technical baseline → ch03
- Technological innovation (Goal 3) → ch04
- Technology insertion / infusion → ch04
- Transformation as change management → ch06
- USS Ford (CVN-78) example → ch02
- Workforce (build and prepare) → ch06
Supporting Files
- glossary.md — key terms from the Strategy, alphabetical, with chapter references
- patterns.md — practitioner patterns (plan models first, engineer model trust, define→govern→use the AST, open-but-guarded access, standards-over-tools, managed technology infusion, transform the people, pilot before scaling) with When/How/Trade-offs
- cheatsheet.md — decision rules, the five goals, goal→focus-area map, the mental-model shifts, the four next steps, cited examples, tells & smells
Scope & Limits
Covers: the DoD Digital Engineering Strategy (2018) in full — the definition and vision of digital engineering; the five goals and their focus areas; the document-to-model and design-build-test→model-analyze-build shifts; model formalisms, provenance/pedigree, and model-based reviews; the authoritative source of truth (define/govern/use, governance, access control, technical baseline); the end-to-end digital enterprise, data-driven decisions, human-machine interaction, and technology insertion; supporting infrastructure, methodologies, cybersecurity, and IP protection; the culture/workforce transformation and its enablers; and the coordinate→plan→pilot→sustain rollout with its cited Service examples (USS Ford, Army LPDM/ePDM, A-10, ERS, NAVAIR).
Does not cover: this is a vision-and-policy strategy, deliberately non-prescriptive — it provides no step-by-step method, tool tutorials, or implementation procedure. It is thin on quantitative metrics, detailed acquisition-policy mechanics, and the contents of DoD Component implementation plans (which it points to but does not contain). For MBSE/SysML mechanics use the sebok pack and SysML v2 / Cameo tooling; for SE process detail use dau-se-guidebook; for systems-security-engineering depth use nist-sse; for open/modular architecture see dod-mosa. The CAC-gated Digital Engineering Body of Knowledge (DEBoK) is intentionally excluded (not public).
Source version: DoD Digital Engineering Strategy, OUSD R&E / ODASD(SE), June 2018 (Distribution Statement A — approved for public release; distribution unlimited).
Jurisdiction: US Government public-domain work (17 U.S.C. 105). Freely reproducible, including commercially; attribution to the DoD is a courtesy, not an obligation, and the DoD does not endorse this pack.