---
ontology:
  id: trend-analysis
  version: "0.4.0"
  description: Strategic foresight and trend-analysis domain ontology — signals, drivers, trends, scenarios,
    forecasts
  extends:
  - mif-base
  - shared-traits
namespaces:
  semantic:
    children:
      foresight:
        description: Signals, drivers, trends, megatrends, uncertainties, and derived foresight artifacts
        type_hint: semantic
        children:
          curves:
            description: Adoption / maturity curves (S-curve, hype cycle)
            type_hint: semantic
          forecasts:
            description: Forecasts and projected future outcomes
            type_hint: semantic
          scenarios:
            description: Plausible future narratives and scenario sets
            type_hint: semantic
          horizons:
            description: Three-Horizons temporal planning zones
            type_hint: semantic
          implications:
            description: Cascading consequences mapped from change (futures wheel)
            type_hint: semantic
          visions:
            description: Normative preferred future states (backcasting)
            type_hint: semantic
  procedural:
    children:
      roadmaps:
        description: Time-sequenced strategic and technology roadmaps
        type_hint: procedural
entity_types:
- name: signal
  description: 'A weak signal: a concrete local artifact or event hinting at change'
  aliases:
    - "adoption signal"
    - "market signal"
    - "momentum signal"
    - "trend indicator"
  exemplars:
    - "A newly published open specification gains thousands of repository stars within weeks, signaling strong but still unproven practitioner interest"
    - "A vendor's AI-augmented feature entering open beta with claimed large time savings signals accelerating automation in its category"
    - "A community's chat-platform membership grows by a meaningful percentage within a year, evidencing accelerating mainstream adoption"
  base: semantic
  traits:
  - cited
  - dated
  schema:
    required:
    - name
    - observation
    properties:
      name:
        type: string
      observation:
        type: string
      source_url:
        type: string
        format: uri
      observed_date:
        type: string
        format: date
      steep_category:
        type: string
        enum:
        - social
        - technological
        - environmental
        - economic
        - political
      novelty:
        type: string
        enum:
        - weak
        - emerging
        - strengthening
      geographic_scope:
        type: string
      related_driver:
        type: string
  source_vocab: IFTF Foresight / EU JRC K4P
  source_class: Signal / Weak Signal
  prior_art: https://www.iftf.org/foresight-tools/
  disposition: mint
- name: driver
  description: 'A driver of change: a broad long-term force shaping the future'
  negative_examples:
    - "Sustained investment in carbon-neutral electricity infrastructure and policy mandates for zero-carbon new building construction are accelerating the transition away from fossil-fuel generation."
    - "The pace at which data protection regimes align globally, influenced by geopolitical competition and regulatory harmonization efforts, affects the feasibility of operating unified digital services."
    - "Autonomous vehicles are positioned at hype-peak on the adoption S-curve, with inflated expectations ahead of mainstream feasibility, creating investor excitement and regulatory experimentation."
    - "Last-mile delivery logistics are straining urban air quality through increased vehicle emissions, creating pressure for low-emission delivery infrastructure investment."
    - "Technological and economic pressures are driving exponential growth in workplace automation, fundamentally reshaping labor-force composition and employment categories across sectors."
    - "Early climate policy adoption is accelerating renewable energy scaling and circular-economy transitions, creating cascading benefits across industrial and agricultural sectors."
    - "Central banks are experimenting with digital currency pilots, a force catalyzing broader financial-system digitalization and competitive pressure among payment networks."
    - "Global development priorities are pushing toward achievement of the UN Sustainable Development Goals, mobilizing international financing and policy coordination toward the 2030 targets."
  base: semantic
  traits:
  - cited
  schema:
    required:
    - name
    - description
    properties:
      name:
        type: string
      description:
        type: string
      steep_category:
        type: string
        enum:
        - social
        - technological
        - environmental
        - economic
        - political
      time_horizon:
        type: string
      impact_level:
        type: string
        enum:
        - low
        - medium
        - high
      evidence_signals:
        type: array
        items:
          type: string
      certainty_level:
        type: string
        enum:
        - low
        - medium
        - high
  source_vocab: IFTF / EU JRC
  source_class: Driver of Change
  prior_art: https://knowledge4policy.ec.europa.eu/foresight/glossary_en
  disposition: mint
- name: trend
  description: 'A trend: a currently visible direction of change (the canonical generic)'
  aliases:
    - "market trend"
    - "adoption trend"
    - "industry direction"
    - "forecast"
    - "trajectory"
    - "market signal"
  exemplars:
    - "An analyst firm predicts a technology category will reach half of deployments within three years"
    - "Survey data shows adoption rising year over year while trust declines"
    - "Global spending in a market segment exceeds a milestone with double-digit growth"
    - "Vendors consolidate through acquisitions as a product category matures"
  negative_examples:
    - "If a policy removes tariff barriers on renewable equipment, manufacturing costs for solar panels will decline, expanding adoption potential among manufacturers and reducing per-watt system costs over five years."
    - "Digital connectivity targets for developing economies aim toward universal broadband access by 2035, enabling digital service delivery and reducing the digital divide."
    - "Software-driven dynamic pricing is spreading across rental housing, e-commerce, and hospitality, with growing market penetration of algorithmic optimization tools in rate-setting decisions."
    - "Electricity generation from renewable sources is progressively increasing its share of global supply, displacing fossil-fuel generation in regional grids, particularly in Europe and East Asia."
    - "Technology companies are increasingly halting hiring in certain specialties, reflecting market shifts toward operational efficiency and disciplined headcount management across the sector."
    - "Generative AI capabilities are scaling rapidly in compute power and cost-efficiency, with improvements in model performance per dollar of infrastructure investment driving broader adoption."
    - "Global energy systems are progressively decarbonizing under climate-neutral pathways, with renewable generation expanding and fossil-fuel generation declining across economic sectors."
    - "Reserve-currency status is gradually shifting among major global currencies, with changing economic and geopolitical weight affecting international financial market composition."
  base: semantic
  traits:
  - cited
  - dated
  schema:
    required:
    - name
    - direction
    properties:
      name:
        type: string
      direction:
        type: string
      evidence:
        type: string
      maturity:
        type: string
        enum:
        - emerging
        - mainstream
        - mature
        - declining
      scope:
        type: string
      steep_category:
        type: string
        enum:
        - social
        - technological
        - environmental
        - economic
        - political
      strength:
        type: string
        enum:
        - weak
        - moderate
        - strong
      first_observed:
        type: string
        format: date
  source_vocab: IFTF / Gartner / EU JRC
  source_class: Trend
  prior_art: https://www.iftf.org/foresight-tools/
  disposition: mint
- name: megatrend
  description: 'A megatrend: a long-term structural transformation operating over a decade or more'
  negative_examples:
    - "Cities worldwide are concentrating population and economic activity at historically rapid rates, creating a persistent structural transformation of global geography and labor mobility."
    - "Urban density concentration is triggering heat-island effects in cities, creating cascading infrastructure stress and public-health challenges across dense metropolitan areas."
    - "Energy systems worldwide are transforming from fossil-fuel dependent to renewable-based infrastructure, a shift driven by cost curves, policy mandates, and technological maturity."
  base: semantic
  traits:
  - cited
  - dated
  schema:
    required:
    - name
    - description
    properties:
      name:
        type: string
      description:
        type: string
      temporal_scale:
        type: string
      scope:
        type: string
      sub_trends:
        type: array
        items:
          type: string
      related_megatrends:
        type: array
        items:
          type: string
      policy_domains_affected:
        type: array
        items:
          type: string
      last_reviewed:
        type: string
        format: date
  source_vocab: EU JRC Global Trends / IFTF
  source_class: Megatrend (long-term structural driver >10yr)
  prior_art: https://joint-research-centre.ec.europa.eu/scientific-activities-z/foresight/jrc-global-trends_en
  disposition: mint
- name: emerging-issue
  description: 'An emerging issue: a novel phenomenon gaining recognition before it becomes a trend'
  aliases:
    - "emerging risk"
    - "open research problem"
    - "unresolved technical issue"
    - "nascent challenge"
  exemplars:
    - "Provenance tracking and temporal validity remain the two hardest unsolved problems for a widely deployed category of AI system"
    - "A newly public specification differentiates on real technical grounds but is still building adoption against a better-funded competing standard"
    - "Contract explosion and organizational adoption friction are documented failure modes that drove an entire testing approach's evolution"
  negative_examples:
    - "Short-form video consumption patterns are reshaping media engagement and attention economics, shifting audience attention toward platforms optimized for sub-minute content."
    - "Singapore's digital infrastructure investments are creating challenges around data privacy, cybersecurity, and equitable technology access in urban development."
  base: semantic
  traits:
  - cited
  - dated
  schema:
    required:
    - name
    - description
    properties:
      name:
        type: string
      description:
        type: string
      novelty_stage:
        type: string
      recognition_level:
        type: string
      competing_issues:
        type: array
        items:
          type: string
      steep_category:
        type: string
        enum:
        - social
        - technological
        - environmental
        - economic
        - political
      first_identified:
        type: string
        format: date
      source_signal:
        type: string
      policy_relevance:
        type: string
  source_vocab: Molitor / EU JRC K4P Foresight
  source_class: Emerging Issue
  prior_art: https://knowledge4policy.ec.europa.eu/foresight/glossary_en
  disposition: mint
- name: wild-card
  description: 'A wild card: a low-probability, high-impact rupture event'
  negative_examples:
    - "Climate impacts on agriculture, water systems, and coastal infrastructure are creating systemic adaptation pressures that could trigger cascading economic shocks if tipping points are exceeded."
    - "Orbital debris populations are accumulating faster than removal rates can sustain, with collision-cascade risks creating potential systemic failure of satellite-dependent infrastructure."
  base: semantic
  traits:
  - cited
  - dated
  schema:
    required:
    - name
    - impact_domain
    properties:
      name:
        type: string
      description:
        type: string
      probability_estimate:
        type: string
        enum:
        - very-low
        - low
      impact_level:
        type: string
        enum:
        - high
        - very-high
        - extreme
      impact_domain:
        type: array
        items:
          type: string
      steep_category:
        type: string
        enum:
        - social
        - technological
        - environmental
        - economic
        - political
      trigger_conditions:
        type: string
      preparedness_notes:
        type: string
  source_vocab: EU JRC K4P Foresight / IFTF
  source_class: Wild Card (low-probability, high-impact event)
  prior_art: https://knowledge4policy.ec.europa.eu/foresight/glossary_en
  disposition: mint
- name: critical-uncertainty
  description: 'A critical uncertainty: a high-impact factor that is genuinely unpredictable, used as
    a scenario axis'
  negative_examples:
    - "The extent to which AI-driven control-system failures will cause cross-operator power-grid blackouts, versus remaining isolated incidents, depends on unmeasured deployment patterns and interdependency levels in infrastructure networks."
    - "Whether climate policy implementation favors early aggressive action versus delayed mitigation, conditional on political-economy constraints and carbon-cost trajectories, remains an unresolved policy uncertainty."
    - "As water and energy systems compete for finite resources in arid regions, the degree to which agricultural production can sustain population growth without triggering resource conflicts remains deeply uncertain."
  base: semantic
  traits:
  - cited
  - dated
  schema:
    required:
    - name
    - description
    properties:
      name:
        type: string
      description:
        type: string
      impact_level:
        type: string
        enum:
        - low
        - medium
        - high
      uncertainty_level:
        type: string
        enum:
        - low
        - medium
        - high
      axis_pole_low:
        type: string
      axis_pole_high:
        type: string
      related_drivers:
        type: array
        items:
          type: string
      scenarios_generated:
        type: array
        items:
          type: string
  source_vocab: Shell / GBN Scenario Planning
  source_class: Critical Uncertainty
  prior_art: https://www.shell.com/news-and-insights/scenarios.html
  disposition: mint
- name: adoption-curve
  description: An adoption / maturity curve positioning a subject on an S-curve or hype cycle
  negative_examples:
    - "Branch-based retail banking is moving from early-maturity to decline-phase adoption as digital-first financial services capture market share from traditional in-branch interactions."
    - "5G network deployment is progressing through early commercial availability into growth-phase adoption, with mainstream consumer and enterprise uptake driving infrastructure expansion."
    - "Passenger vehicles are transitioning from internal-combustion dominance through early hybrid adoption into battery-electric maturity, following classic S-curve diffusion dynamics."
    - "DNA synthesis capabilities are entering early commercial availability, with adoption growing among biotech researchers, while screening frameworks remain insufficient to prevent dual-use misuse."
    - "Cashierless retail technology is progressing through pilot deployments toward early commercial viability, with customer acceptance and merchant adoption determining market penetration."
  base: semantic
  traits:
  - cited
  - dated
  schema:
    required:
    - subject
    - model
    properties:
      subject:
        type: string
      model:
        type: string
        enum:
        - rogers-s-curve
        - gartner-hype-cycle
      current_phase:
        type: string
      adopter_segment:
        type: string
        enum:
        - innovators
        - early-adopters
        - early-majority
        - late-majority
        - laggards
      time_to_plateau:
        type: string
      critical_mass_reached:
        type: boolean
      evidence:
        type: string
  source_vocab: Rogers Diffusion of Innovations / Gartner Hype Cycle
  source_class: S-Curve / Technology Maturity Level
  prior_art: https://en.wikipedia.org/wiki/Diffusion_of_innovations
  disposition: mint
- name: forecast
  description: 'A forecast: a projected future outcome grounded in signals, drivers, and trends'
  base: semantic
  traits:
  - cited
  - dated
  - timeline
  schema:
    required:
    - statement
    - horizon
    properties:
      statement:
        type: string
      horizon:
        type: string
      confidence_level:
        type: string
        enum:
        - low
        - medium
        - high
      basis_signals:
        type: array
        items:
          type: string
      basis_drivers:
        type: array
        items:
          type: string
      scenario_type:
        type: string
        enum:
        - baseline
        - alternative
        - wildcard
      created_date:
        type: string
        format: date
      author:
        type: string
  source_vocab: IFTF Foresight
  source_class: Forecast
  prior_art: https://www.iftf.org/foresight-tools/
  disposition: mint
- name: scenario
  description: 'A scenario: a plausible, internally consistent future narrative'
  base: semantic
  traits:
  - cited
  - versioned
  schema:
    required:
    - name
    - horizon
    properties:
      name:
        type: string
      narrative:
        type: string
      horizon:
        type: string
      scenario_type:
        type: string
        enum:
        - baseline
        - alternative
        - aspirational
        - collapse
      critical_uncertainties_used:
        type: array
        items:
          type: string
      key_drivers:
        type: array
        items:
          type: string
      plausibility_rationale:
        type: string
      world_state:
        type: string
  source_vocab: Shell Scenario Planning / EU JRC
  source_class: Scenario (plausible future narrative)
  prior_art: https://www.shell.com/what-we-do/scenarios.html
  disposition: mint
- name: horizon
  description: 'A horizon: a Three-Horizons temporal planning zone (H1/H2/H3)'
  base: semantic
  traits:
  - cited
  - dated
  schema:
    required:
    - label
    - horizon_type
    properties:
      label:
        type: string
      horizon_type:
        type: string
        enum:
        - h1
        - h2
        - h3
      time_span:
        type: string
      description:
        type: string
      dominant_system:
        type: string
      key_innovations:
        type: array
        items:
          type: string
      mindset_type:
        type: string
      transition_triggers:
        type: array
        items:
          type: string
  source_vocab: Three Horizons (Sharpe/Curry/Leicester)
  source_class: Horizon (H1/H2/H3)
  prior_art: https://en.wikipedia.org/wiki/Three_Horizons
  disposition: mint
- name: implication
  description: 'An implication: a cascading consequence of a change (futures wheel ring)'
  base: semantic
  traits:
  - cited
  schema:
    required:
    - name
    - parent_change
    properties:
      name:
        type: string
      description:
        type: string
      order:
        type: integer
      parent_change:
        type: string
      impact_domain:
        type: string
      steep_category:
        type: string
        enum:
        - social
        - technological
        - environmental
        - economic
        - political
      valence:
        type: string
        enum:
        - positive
        - negative
        - neutral
        - mixed
      probability_estimate:
        type: string
        enum:
        - low
        - medium
        - high
  source_vocab: Futures Wheel (Jerome Glenn)
  source_class: Implication / Consequence Ring
  prior_art: https://www.toolshero.com/decision-making/futures-wheel-jerome-glenn/
  disposition: mint
- name: vision
  description: 'A vision: a desired or preferred future state used as a backcasting anchor'
  base: semantic
  traits:
  - cited
  - stakeholders
  schema:
    required:
    - name
    - description
    properties:
      name:
        type: string
      description:
        type: string
      target_horizon:
        type: string
      normative_basis:
        type: string
      stakeholders:
        type: array
        items:
          type: string
      backcasting_pathway:
        type: string
      key_milestones:
        type: array
        items:
          type: string
      values_underpinning:
        type: array
        items:
          type: string
  source_vocab: OECD-OPSI Futures / Backcasting (Robinson)
  source_class: Vision / Preferred Future State
  prior_art: https://oecd-opsi.org/guide/futures-and-foresight/
  disposition: mint
- name: roadmap
  description: 'A roadmap: a time-sequenced action plan working backward from a vision'
  negative_examples:
    - "Companies are establishing multi-year plans for deploying autonomous systems, with staged rollouts of robotics and automation technologies across supply chains and production facilities."
    - "Urban planners are designing 15-minute-neighborhood infrastructure with distributed services and reduced transport-dependency, progressively rolling out in European and North American cities."
  base: procedural
  traits:
  - cited
  - versioned
  - timeline
  schema:
    required:
    - name
    - scope
    properties:
      name:
        type: string
      scope:
        type: string
      target_vision:
        type: string
      milestones:
        type: array
        items:
          type: string
      time_horizon:
        type: string
      technology_areas:
        type: array
        items:
          type: string
      resource_requirements:
        type: string
      dependencies:
        type: array
        items:
          type: string
      last_updated:
        type: string
        format: date
  source_vocab: Technology Roadmapping (Phaal/Farrukh)
  source_class: Technology / Strategic Roadmap
  prior_art: https://en.wikipedia.org/wiki/Technology_roadmap
  disposition: mint
relationships:
  causes:
    description: 'A driver causes a trend (IFTF: drivers produce trends/signals)'
    from:
    - driver
    to:
    - trend
    symmetric: false
  matures_into:
    description: 'A signal matures into a trend (IFTF: weak signal strengthens into a visible trend)'
    from:
    - signal
    to:
    - trend
    symmetric: false
  indicates:
    description: 'A signal indicates a driver (IFTF: signals are symptoms of drivers)'
    from:
    - signal
    to:
    - driver
    symmetric: false
  placed_on:
    description: 'A trend is placed on an adoption-curve (Rogers/Gartner: a trend is positioned on an
      S-curve or hype cycle)'
    from:
    - trend
    to:
    - adoption-curve
    symmetric: false
  projected_as:
    description: A trend is projected as a forecast
    from:
    - trend
    to:
    - forecast
    symmetric: false
  shaped_by:
    description: A megatrend is shaped by a driver (a megatrend aggregates structural drivers)
    from:
    - megatrend
    to:
    - driver
    symmetric: false
  contains:
    description: A megatrend contains a trend (near-term trends express a megatrend)
    from:
    - megatrend
    to:
    - trend
    symmetric: false
  synthesizes:
    description: A scenario synthesizes its driving forces (built from drivers and megatrends)
    from:
    - scenario
    to:
    - driver
    - megatrend
    symmetric: false
  incorporated_in:
    description: A wild-card is incorporated in a scenario (wild-card scenarios are a planning technique)
    from:
    - wild-card
    to:
    - scenario
    symmetric: false
  disrupts:
    description: A wild-card disrupts a trend or megatrend (it ruptures established trajectories)
    from:
    - wild-card
    to:
    - trend
    - megatrend
    symmetric: false
  constrains:
    description: A critical-uncertainty constrains and differentiates the scenario space (Shell/GBN 2x2
      axis)
    from:
    - critical-uncertainty
    to:
    - scenario
    symmetric: false
  generates:
    description: 'A driver produces a trend (IFTF: drivers precipitate visible trends)'
    from:
    - driver
    to:
    - trend
    symmetric: false
  grounds:
    description: 'A driver grounds a forecast (IFTF: drivers/trends are building blocks of forecasts)'
    from:
    - driver
    to:
    - forecast
    symmetric: false
  informs:
    description: 'A scenario informs a vision (OECD-OPSI: scenarios reveal futures from which a preferred
      future is selected)'
    from:
    - scenario
    to:
    - vision
    symmetric: false
  operationalizes:
    description: A vision operationalizes into a roadmap (backcasting works backward from a vision to
      a time-sequenced roadmap)
    from:
    - vision
    to:
    - roadmap
    symmetric: false
  produces:
    description: 'A trend produces an implication (Futures Wheel: a trend produces cascading implications)'
    from:
    - trend
    to:
    - implication
    symmetric: false
  specializes:
    description: A megatrend specializes a trend (rdfs:subClassOf — megatrend is a structural subtype
      of trend)
    from:
    - megatrend
    to:
    - trend
    symmetric: false
  intensifies:
    description: A wild-card intensifies a critical-uncertainty (rdfs:subClassOf — a wild card is a low-probability,
      very-high-impact subtype of critical uncertainty)
    from:
    - wild-card
    to:
    - critical-uncertainty
    symmetric: false
discovery:
  enabled: true
  confidence_threshold: 0.8
  patterns:
  - content_pattern: \b(weak signal|signal of change|early indicator)\b
    suggest_entity: signal
    suggest_namespace: _semantic/foresight
  - content_pattern: \b(driver of change|STEEP|long-term force)\b
    suggest_entity: driver
    suggest_namespace: _semantic/foresight
  - content_pattern: \b(trend|direction of change|trend radar)\b
    suggest_entity: trend
    suggest_namespace: _semantic/foresight
  - content_pattern: \b(hype cycle|trough of disillusionment|crossing the chasm|S-curve|early adopter)\b
    suggest_entity: adoption-curve
    suggest_namespace: _semantic/foresight/curves
  - content_pattern: \b(forecast|projected (future|to)|expected to reach)\b
    suggest_entity: forecast
    suggest_namespace: _semantic/foresight/forecasts
  - content_pattern: \b(megatrend|mega[- ]trend|structural transformation|decade[- ]long trend)\b
    suggest_entity: megatrend
    suggest_namespace: _semantic/foresight
  - content_pattern: \b(scenario|plausible future|strategic uncertainty|world in 20\d\d)\b
    suggest_entity: scenario
    suggest_namespace: _semantic/foresight/scenarios
  - content_pattern: \b(wild[- ]?card|black swan|low[- ]probability.*high[- ]impact|rupture event)\b
    suggest_entity: wild-card
    suggest_namespace: _semantic/foresight