@base . @prefix : <#> . @prefix schema: . @prefix rdf: . @prefix rdfs: . @prefix skos: . @prefix prov: . @prefix owl: . @prefix xsd: . ############################################################ # ONTOLOGY HEADER (enriched) ############################################################ :Ontology a owl:Ontology ; rdfs:label "FDE / IRE Enterprise Skills, Lifecycle, Capability, and Provenance Ontology" ; schema:description "A unified ontology modeling Forward Deployed Engineers (FDEs), Inward Redeployed Engineers (IREs), AI-native skills, lifecycle governance, and provenance of knowledge-to-skill transformation." ; schema:version "1.1" ; schema:dateCreated "2025-05-01"^^xsd:date ; schema:dateModified "2026-05-18"^^xsd:date ; schema:keywords "FDE, IRE, AI skills, enterprise AI, knowledge codification, skill lifecycle, provenance, linked data, agentic systems" ; schema:creator :Kidehen ; schema:encodingFormat "text/turtle" ; prov:wasAttributedTo :Kidehen . ############################################################ # SOURCE POST (X.com thread that originated this ontology) ############################################################ :SourcePost a schema:SocialMediaPosting ; rdfs:label "X.com Thread: FDE/IRE Ontology and Roles" ; schema:url "https://x.com/kidehen/status/2055725483535282591"^^xsd:anyURI ; schema:author :Kidehen ; schema:datePublished "2025-05-01"^^xsd:date ; schema:about :Ontology ; schema:headline "FDE and IRE: AI-Native Enterprise Engineering Roles and Skills Ontology" ; schema:description "Original X.com thread by Kingsley Idehen introducing the FDE/IRE role distinction and the 9-skill AI Literacy framework for AI-native enterprise engineering." . :Kidehen a schema:Person ; rdfs:label "Kingsley Uyi Idehen" ; schema:name "Kingsley Uyi Idehen" ; schema:url "https://x.com/kidehen"^^xsd:anyURI ; schema:jobTitle "CEO, OpenLink Software" ; schema:worksFor ; owl:sameAs . ############################################################ # CORE ROLE MODEL ############################################################ :EngineeringRole a rdfs:Class ; rdfs:isDefinedBy :Ontology ; rdfs:label "Engineering Role" ; skos:definition "A structured enterprise role responsible for engineering work across internal or external system boundaries." ; schema:description "The parent class for both FDE and IRE roles. Characterized by boundary-spanning technical work in AI-native enterprise contexts." . :ForwardDeployedEngineer a rdfs:Class ; rdfs:isDefinedBy :Ontology ; rdfs:subClassOf :EngineeringRole ; rdfs:label "Forward Deployed Engineer" ; skos:definition "An outward-facing engineering role embedded in customer environments to deploy and adapt AI systems in real-world contexts." ; schema:description "Acts as the execution and integration interface between enterprise systems and external customer environments. FDEs generate new operational knowledge through deployment that IREs subsequently codify." ; skos:altLabel "FDE" . :InwardRedeployedEngineer a rdfs:Class ; rdfs:isDefinedBy :Ontology ; rdfs:subClassOf :EngineeringRole ; rdfs:label "Inward Redeployed Engineer" ; skos:definition "An inward-facing engineering role focused on extracting tacit knowledge and transforming it into structured, reusable, AI-executable skills." ; schema:description "Acts as the internal knowledge compression layer converting organizational expertise into machine-usable form. IREs transform FDE deployment experience into reusable skill artifacts." ; skos:altLabel "IRE" . ############################################################ # SKILL MODEL ############################################################ :Skill a rdfs:Class ; rdfs:isDefinedBy :Ontology ; rdfs:label "Skill" ; skos:definition "A reusable, structured unit of operational capability executable by humans or AI agents." ; schema:description "Skills are the atomic unit of AI-native enterprise capability, replacing undocumented tribal knowledge with composable execution units. A skill encodes: trigger conditions, execution steps, expected outputs, and edge cases." . ############################################################ # LIFECYCLE MODEL ############################################################ :SkillLifecycleState a rdfs:Class ; rdfs:isDefinedBy :Ontology ; rdfs:label "Skill Lifecycle State" ; schema:description "Governance state tracking a skill artifact through its operational lifecycle from formation to retirement." . :ProposedSkill a rdfs:Class ; rdfs:isDefinedBy :Ontology ; rdfs:subClassOf :SkillLifecycleState ; rdfs:label "Proposed Skill" ; skos:definition "A skill under formation and not yet validated for production use." . :ValidatedSkill a rdfs:Class ; rdfs:isDefinedBy :Ontology ; rdfs:subClassOf :SkillLifecycleState ; rdfs:label "Validated Skill" ; skos:definition "A skill reviewed and approved for correctness and applicability." . :DeployedSkill a rdfs:Class ; rdfs:isDefinedBy :Ontology ; rdfs:subClassOf :SkillLifecycleState ; rdfs:label "Deployed Skill" ; skos:definition "A skill actively used in production or operational environments." . :DeprecatedSkill a rdfs:Class ; rdfs:isDefinedBy :Ontology ; rdfs:subClassOf :SkillLifecycleState ; rdfs:label "Deprecated Skill" ; skos:definition "A skill no longer recommended for use but retained for traceability." . :hasLifecycleState a rdf:Property ; rdfs:isDefinedBy :Ontology ; rdfs:domain :Skill ; rdfs:range :SkillLifecycleState ; rdfs:label "has lifecycle state" ; schema:description "Associates a skill artifact with its current governance lifecycle state." . ############################################################ # PROVENANCE MODEL ############################################################ :SkillGenerationActivity a rdfs:Class ; rdfs:isDefinedBy :Ontology ; rdfs:subClassOf prov:Activity ; rdfs:label "Skill Generation Activity" ; skos:definition "An activity that transforms tacit or explicit knowledge into structured skill artifacts." . :createdFromTacitKnowledge a rdf:Property ; rdfs:isDefinedBy :Ontology ; rdfs:domain :SkillGenerationActivity ; rdfs:range prov:Entity ; rdfs:label "created from tacit knowledge" . ############################################################ # CORE RELATIONSHIPS ############################################################ :hasSkill a rdf:Property ; rdfs:isDefinedBy :Ontology ; rdfs:domain schema:Person ; rdfs:range :Skill ; rdfs:label "has skill" . :requiresSkill a rdf:Property ; rdfs:isDefinedBy :Ontology ; rdfs:domain :EngineeringRole ; rdfs:range :Skill ; rdfs:label "requires skill" . ############################################################ # BASE SKILLS ############################################################ :FDE_AITooling a :Skill ; rdfs:label "AI Tooling Skill (FDE)" ; schema:category "FDE Skills" ; skos:definition "Ability to apply AI tools to real-world business and customer problems." ; schema:description "Enables translation of model capabilities into operational value in customer environments." ; :hasLifecycleState :DeployedSkill . :IRE_KnowledgeCodification a :Skill ; rdfs:label "Knowledge Codification Skill (IRE)" ; schema:category "IRE Skills" ; skos:definition "Ability to extract tacit knowledge and formalize it into structured systems." ; schema:description "Enables conversion of dispersed human expertise into reusable enterprise intelligence." ; :hasLifecycleState :ValidatedSkill . ############################################################ # DEPRECATED SKILL INSTANCE (lifecycle completeness) ############################################################ :ManualDocumentationSkill a :Skill ; rdfs:label "Manual Documentation Skill (Deprecated)" ; schema:category "Deprecated" ; skos:definition "Legacy approach to documenting enterprise processes through unstructured manual writing without machine-readable encoding." ; schema:description "Superseded by AI-assisted skill codification using structured ontologies and RDF. Retained for audit traceability." ; :hasLifecycleState :DeprecatedSkill . ############################################################ # ORGANIZATIONS ############################################################ :AI_Vendor_Org a schema:Organization ; rdfs:label "AI Vendor Organization" ; schema:description "An AI vendor organization that deploys Forward Deployed Engineers into customer environments." . :Enterprise_Business_Org a schema:Organization ; rdfs:label "Enterprise Business Organization" ; schema:description "An enterprise organization that employs Inward Redeployed Engineers for internal knowledge codification and AI-native transformation." . ############################################################ # PEOPLE (INSTANCES) ############################################################ :Alice a schema:Person, :ForwardDeployedEngineer ; rdfs:label "Alice" ; schema:name "Alice" ; schema:employeeOf :AI_Vendor_Org ; :hasSkill :FDE_AITooling . :John a schema:Person, :InwardRedeployedEngineer ; rdfs:label "John" ; schema:name "John" ; schema:employeeOf :Enterprise_Business_Org ; :hasSkill :IRE_KnowledgeCodification . ############################################################ # PROVENANCE INSTANCE ############################################################ :TacitKnowledge_001 a prov:Entity ; rdfs:label "Tacit Knowledge Fragment" ; skos:definition "Unstructured operational knowledge distributed across enterprise teams — undocumented processes, expert intuition, and tribal know-how awaiting codification." . :CodificationActivity_001 a :SkillGenerationActivity ; rdfs:label "Knowledge Codification Activity" ; prov:wasAssociatedWith :John ; prov:used :TacitKnowledge_001 ; :createdFromTacitKnowledge :TacitKnowledge_001 . :IRE_KnowledgeCodification_SkillArtifact_001 a :Skill ; rdfs:label "IRE Knowledge Codification Skill Artifact" ; prov:wasGeneratedBy :CodificationActivity_001 ; :hasLifecycleState :ProposedSkill . ############################################################ # SHARED AI-AGENTIC CAPABILITY LAYER (9 skills) ############################################################ :AILiteracySkill a rdfs:Class ; rdfs:isDefinedBy :Ontology ; rdfs:subClassOf :Skill ; rdfs:label "AI Literacy Skill" ; skos:definition "Core capabilities required to build, operate, and govern AI systems." ; schema:description "Defines whether an enterprise can move from AI consumption to AI-native operational design. Mastery of all 9 literacy skills distinguishes AI-native engineers from AI-adjacent users." . :LLMMasterySkill a :AILiteracySkill ; rdfs:label "LLM Mastery" ; schema:category "Shared AI Literacy" ; skos:definition "Mastery of frontier LLMs across vendors including model selection, prompt engineering, context management, and output evaluation." ; schema:description "Without this, AI systems become opaque black boxes instead of controllable reasoning systems. The foundation of all AI-native engineering work." ; :hasLifecycleState :DeployedSkill . :AgentEngineeringSkill a :AILiteracySkill ; rdfs:label "AI Agent Engineering" ; schema:category "Shared AI Literacy" ; skos:definition "Design of modular agents composed of skills, tools, and memory systems with defined boundaries and interfaces." ; schema:description "Enables transition from prompt-based usage to autonomous, composable AI systems. Required by both FDEs (deployment) and IREs (knowledge infrastructure)." ; :hasLifecycleState :DeployedSkill . :SkillEngineeringSkill a :AILiteracySkill ; rdfs:label "Skill Engineering" ; schema:category "Shared AI Literacy" ; skos:definition "Design of reusable skills decoupled from tools and data spaces, with clear trigger conditions and execution contracts." ; schema:description "Transforms tribal knowledge into reusable enterprise execution units. The IRE's core competency — turning what people know into what machines can do." ; :hasLifecycleState :ValidatedSkill . :DataSpaceToolingSkill a :AILiteracySkill ; rdfs:label "Data Space Tooling (CRUD)" ; schema:category "Shared AI Literacy" ; skos:definition "Building tools for CRUD operations across heterogeneous data spaces including databases, APIs, and file systems." ; schema:description "Without this, AI cannot act on real enterprise data systems. Bridges the gap between AI reasoning and enterprise data reality." ; :hasLifecycleState :DeployedSkill . :APIInteroperabilitySkill a :AILiteracySkill ; rdfs:label "API Interoperability (OpenAPI + MCP)" ; schema:category "Shared AI Literacy" ; skos:definition "Design and consumption of interoperable APIs including OpenAPI specifications and Model Context Protocol (MCP) interfaces." ; schema:description "Provides the connective tissue enabling cross-system AI orchestration. MCP in particular is becoming the standard protocol for AI-to-tool communication." ; :hasLifecycleState :DeployedSkill . :HTTPIntegrationSkill a :AILiteracySkill ; rdfs:label "HTTP Protocol Mastery" ; schema:category "Shared AI Literacy" ; skos:definition "Deep understanding of HTTP semantics, REST principles, content negotiation, authentication, and distributed communication patterns." ; schema:description "HTTP is the universal transport layer for AI-enabled distributed systems. Mastery enables reliable, secure, and efficient AI system integration." ; :hasLifecycleState :DeployedSkill . :LinkedDataSkill a :AILiteracySkill ; rdfs:label "Linked Data & Semantic Web" ; schema:category "Shared AI Literacy" ; skos:definition "Modeling structured knowledge using RDF, ontologies, and semantic graphs with dereferenceable IRIs and SPARQL querying." ; schema:description "Enables machine-readable enterprise knowledge and cross-domain reasoning. The IRE's primary knowledge representation tool." ; :hasLifecycleState :ValidatedSkill . :DataAccessProtocolSkill a :AILiteracySkill ; rdfs:label "Data Access Protocols" ; schema:category "Shared AI Literacy" ; skos:definition "Database connectivity via ODBC, JDBC, ADO.NET, and equivalent protocols across relational, graph, and document stores." ; schema:description "Ensures AI systems can access complete enterprise datasets rather than fragments exposed through higher-level APIs." ; :hasLifecycleState :DeployedSkill . :QueryLanguageMasterySkill a :AILiteracySkill ; rdfs:label "Declarative Query Languages" ; schema:category "Shared AI Literacy" ; skos:definition "Mastery of SQL, SPARQL, GraphQL, GQL, and openCypher for structured retrieval across heterogeneous data systems." ; schema:description "Enables structured retrieval of truth from heterogeneous enterprise data systems. The universal language of data access for AI-native engineers." ; :hasLifecycleState :ValidatedSkill . ############################################################ # ROLE SKILL REQUIREMENTS ############################################################ :ForwardDeployedEngineer :requiresSkill :LLMMasterySkill, :AgentEngineeringSkill, :APIInteroperabilitySkill, :HTTPIntegrationSkill, :DataSpaceToolingSkill . :InwardRedeployedEngineer :requiresSkill :LLMMasterySkill, :SkillEngineeringSkill, :LinkedDataSkill, :DataAccessProtocolSkill, :QueryLanguageMasterySkill, :AgentEngineeringSkill . ############################################################ # FAQ ENTITIES ############################################################ :FAQ_Q1 a schema:Question ; rdfs:label "What is a Forward Deployed Engineer (FDE)?" ; schema:name "What is a Forward Deployed Engineer (FDE)?" ; schema:acceptedAnswer :FAQ_A1 ; schema:about :ForwardDeployedEngineer . :FAQ_A1 a schema:Answer ; schema:text "A Forward Deployed Engineer is an outward-facing engineering role embedded in customer environments. FDEs deploy and adapt AI systems to real-world business contexts, acting as the execution interface between an AI vendor's systems and the customer's operations. They require LLM mastery, agent engineering, API interoperability, HTTP protocols, and data space tooling skills." . :FAQ_Q2 a schema:Question ; rdfs:label "What is an Inward Redeployed Engineer (IRE)?" ; schema:name "What is an Inward Redeployed Engineer (IRE)?" ; schema:acceptedAnswer :FAQ_A2 ; schema:about :InwardRedeployedEngineer . :FAQ_A2 a schema:Answer ; schema:text "An Inward Redeployed Engineer is an inward-facing role focused on extracting tacit knowledge from enterprise teams and transforming it into structured, reusable, AI-executable skill artifacts. IREs act as the internal knowledge compression layer. They require skill engineering, linked data, data access protocols, query languages, and agent engineering skills." . :FAQ_Q3 a schema:Question ; rdfs:label "What is the skill lifecycle?" ; schema:name "What is the skill lifecycle?" ; schema:acceptedAnswer :FAQ_A3 ; schema:about :SkillLifecycleState . :FAQ_A3 a schema:Answer ; schema:text "The skill lifecycle has four governance states: Proposed (under formation, not yet validated), Validated (reviewed and approved), Deployed (actively used in production), and Deprecated (retired but retained for traceability). Every skill artifact progresses through these states to ensure governance, auditability, and organisational trust." . :FAQ_Q4 a schema:Question ; rdfs:label "What is tacit knowledge and how is it codified?" ; schema:name "What is tacit knowledge and how is it codified?" ; schema:acceptedAnswer :FAQ_A4 ; schema:about :TacitKnowledge_001 . :FAQ_A4 a schema:Answer ; schema:text "Tacit knowledge is unstructured operational expertise distributed across enterprise teams — undocumented processes, expert intuition, and tribal know-how. IREs codify it through a SkillGenerationActivity: identify tacit knowledge sources, extract the expertise, structure it as an RDF-backed skill artifact, validate with domain experts, and deploy for reuse by AI agents and engineers." . :FAQ_Q5 a schema:Question ; rdfs:label "What is AI Literacy and why does it matter?" ; schema:name "What is AI Literacy and why does it matter?" ; schema:acceptedAnswer :FAQ_A5 ; schema:about :AILiteracySkill . :FAQ_A5 a schema:Answer ; schema:text "AI Literacy comprises 9 core capabilities: LLM mastery, agent engineering, skill engineering, data space tooling, API interoperability, HTTP protocol mastery, linked data and semantic web, data access protocols, and declarative query languages. Together they determine whether an enterprise can move from passively consuming AI to designing AI-native operational systems." . :FAQ_Q6 a schema:Question ; rdfs:label "How do FDEs and IREs complement each other?" ; schema:name "How do FDEs and IREs complement each other?" ; schema:acceptedAnswer :FAQ_A6 ; schema:about :EngineeringRole . :FAQ_A6 a schema:Answer ; schema:text "FDEs face outward — they deploy AI in customer environments and generate new operational knowledge through that work. IREs face inward — they capture that knowledge and codify it into reusable skills. This creates a virtuous cycle: FDE deployments surface new tacit knowledge, IREs encode it as validated skills, and those skills make subsequent FDE deployments more effective and consistent." . :FAQ_Q7 a schema:Question ; rdfs:label "What makes a skill AI-executable?" ; schema:name "What makes a skill AI-executable?" ; schema:acceptedAnswer :FAQ_A7 ; schema:about :Skill . :FAQ_A7 a schema:Answer ; schema:text "An AI-executable skill is structured, deterministic, and composable. It must encode: (1) trigger conditions — when should this skill be invoked; (2) execution steps — a precise, ordered procedure; (3) expected outputs — what a successful execution produces; (4) edge cases — known failure modes and their resolutions; and (5) provenance — who created it, from what knowledge source, and when." . ############################################################ # HOW-TO: IRE SKILL CODIFICATION PROCESS ############################################################ :IRE_Codification_HowTo a schema:HowTo ; rdfs:label "How to Codify Tacit Knowledge as a Skill Artifact" ; schema:name "How to Codify Tacit Knowledge as a Skill Artifact" ; schema:description "A step-by-step process for Inward Redeployed Engineers to transform organisational tacit knowledge into structured, AI-executable skill artifacts with full lifecycle governance." ; schema:step :HowToStep1, :HowToStep2, :HowToStep3, :HowToStep4, :HowToStep5 . :HowToStep1 a schema:HowToStep ; rdfs:label "Identify Tacit Knowledge Source" ; schema:name "Identify Tacit Knowledge Source" ; schema:text "Locate and interview subject-matter experts, review undocumented workflows, and inventory processes that exist only in team members' heads. Use discovery interviews and process shadowing to surface hidden expertise. Output: a mapped inventory of tacit knowledge fragments." ; schema:position 1 . :HowToStep2 a schema:HowToStep ; rdfs:label "Extract and Structure the Knowledge" ; schema:name "Extract and Structure the Knowledge" ; schema:text "Convert raw expertise into structured form using RDF, schema.org, and skill definition templates. Capture: trigger conditions, execution steps, expected outputs, edge cases, and failure modes. Mint a document-local IRI for the skill artifact and encode it as Turtle or JSON-LD." ; schema:position 2 . :HowToStep3 a schema:HowToStep ; rdfs:label "Validate with Domain Experts" ; schema:name "Validate with Domain Experts" ; schema:text "Review the structured skill artifact with the original knowledge holders and peer engineers. Verify accuracy, completeness, and generalisability. Record the validation as a prov:Activity. Transition the skill artifact to ValidatedSkill state on approval." ; schema:position 3 . :HowToStep4 a schema:HowToStep ; rdfs:label "Deploy as a Reusable Skill" ; schema:name "Deploy as a Reusable Skill" ; schema:text "Register the validated skill in the enterprise skill registry. Configure it for execution by AI agents and human engineers. Transition to DeployedSkill state. Publish the RDF artifact with a dereferenceable IRI for discovery via Linked Data." ; schema:position 4 . :HowToStep5 a schema:HowToStep ; rdfs:label "Maintain Lifecycle Governance" ; schema:name "Maintain Lifecycle Governance" ; schema:text "Continuously monitor skill effectiveness. Update skills as domain knowledge evolves using prov:wasRevisionOf to link versions. Deprecate skills that become obsolete, assigning DeprecatedSkill state and retaining the artifact for audit traceability. Never delete — deprecate." ; schema:position 5 .