构件：与介质正交的那一层

图示与数据图不属于任何一格——同一张架构图可以出现在幻灯里、 文档里、网页里。所以它们单列一层，共 52 型：图示 27 型 + 数据图 25 型。

每一型写明什么时候该用它与画法约定。

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  图示

  Architecture

  system overviews, data-flow diagrams, integration maps, infra topology

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  图示

  Bar / Column Chart

  comparing discrete quantities across categories or time intervals — sprint velocity, monthly revenue, feature adoption, cohort counts. Use when each category has a single numeric value and the comparison between bars is the primary message

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  Data Flow

  visualising how data moves through a pipeline *across organisational roles* — who initiates, who processes, who publishes, and who consumes. The canonical use case is a multi-role data platform (Admin → Engineers → Scientists → Consumers) with 4–6 process steps. Use when the reader needs to understand who does what at each stage, not just the technical components

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  DP integration

  the integration topology of a data platform — which source systems plug in, which consumer surfaces plug out, and which protocol each one speaks. Hub-and-spoke layout wrapped in an explicit Data platform layer; no time/phase axis

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  DP security matrix

  documenting per-role / per-component access permissions for a data platform — a grid where each row is a platform component (Keycloak, MinIO bucket, Trino catalog, JupyterHub, NiFi, …) and each column is a role / AD group (Data Administrators, Data Engineers, Data Scientists, Data Consumers, …). Each intersection cell holds a permission value (Admin / Full / R/W / Read / SELECT / Login / No access) with a visual category that matches the permission level. One cell may be marked focal to flag a critical access rule (e.g., "Data Consumers can ONLY `SELECT` from the aggregated catalog — sole consumer access")

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  ER / Data Model

  database schemas, API resource relationships, domain models

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  Flowchart

  decision logic, algorithms, user-facing branching flows ("Should I…?"), onboarding routing, support-triage trees

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  Gantt Chart

  project plans and roadmaps — tasks with explicit start and end dates, grouped into phases. Use when the reader needs to see temporal overlap, parallel tracks, and milestone sequencing at a glance

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  High-Level

  end-to-end data stack overviews — ingestion → storage → query → analytics → visualization — deployed on a container orchestrator (Kubernetes, ECS, Nomad). Combines a phase chevron banner, deployment boundary, orchestration bar, identity footer, and (optionally) a right-side vertical chevron strip for cross-cutting concerns (Orchestration, Security, Observability)

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  IT current-state

  documenting the *before* picture of a modernization proposal — the legacy IT landscape grouped by phase or department (Collection → Processing → Dissemination, or Frontend / Backend / Storage, or Survey → Analysts → Reports), with pain-points flagged, file-based hand-offs labelled (CSV / Excel / Email / Copy), and pre-platform tooling visible. The companion to `type-dp-integration.md`: this type shows the gap that a data-platform proposal is going to close

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  Layer Stack

  OSI model, CSS cascade, context hierarchy, tech stack, abstraction layers, memory hierarchy

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  Line Chart

  continuous trends over time or a sequential index — signups over weeks, revenue by month, latency over releases. Use when the direction and rate of change between points is the primary message

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  Loop

  reinforcing cycles, flywheels, feedback loops, and operating loops — anything where the last step feeds the first and a shared hub accumulates state. Use Loop when the reader must see both motions at once: work advances clockwise around the ring, while each pass writes durable state back to one common center

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  Medallion

  documenting a multi-tier data-storage layout where each tier is a distinct *quality / access level* of the same dataset — typically raw landing zone, anonymised, staging/cleaned, aggregated business indicators, and cold archive. Used when the reader needs to see at a glance *what each bucket contains*, *who writes it*, *with what tool and format*, and *how data is promoted between tiers*

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  Nested Containment

  hierarchy through containment — scope boundaries, CLAUDE.md cascade, trust zones, folder nesting, blast radius. Outer = broader, inner = more specific

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  Org Chart / Responsibility Map

  human teams, agent teams, support escalation maps, role ownership, routing maps, and any hierarchy where the reader needs to know *who owns what* rather than just parent → child structure

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  Process

  sequential business processes with multiple actors/divisions where the reader needs to see *who* does *what*, *what data* enters and leaves each step, and *which tools* are used — not just the step order. Covers responsibility audits, data-quality gate reviews, cross-divisional handoff maps, and end-to-end workflow documentation

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  Pyramid / Funnel

  hierarchy of needs, prioritization ranks, value pyramids, conversion funnels, content importance stacks

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  Quadrant

  prioritization (Impact × Effort), positioning (Reach × Frequency), portfolio maps, 2×2 decision frames

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  Radar / Spider

  comparing 3–5 entities across 3–5 quantitative criteria on a single normalized 0–N scale. Capability matrices, product or backend evaluations, framework/team scorecards. Where a comparison table starts running out of horizontal room, radar makes the shape of each option legible at a glance

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  Scatter Plot

  correlation and distribution — two continuous variables plotted against each other. Use when the relationship (or lack of one) between variables is the message, or when you need to identify clusters, outliers, and high/low performers

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  Sequence

  request/response flows, protocol exchanges, multi-actor interactions over time, API call traces, incident reconstructions, auth/token refresh paths with branching

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  State Machine

  finite state logic — order status, auth state, connection lifecycle, form wizard, job queue status

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  Swimlane

  cross-functional processes, RACI-style flows, vendor handoffs, multi-team shipping workflows

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  Timeline

  release history, project milestones, incident timelines, roadmaps, changelog visualizations

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  Tree / Hierarchy

  org charts, dependency trees, taxonomy, file trees, decision breakdowns, skill trees

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  Venn / Set Overlap

  intersection of concepts/domains, shared attributes between categories, "where A meets B", ikigai-style frames (desirable × feasible × viable)

• 数据图

  Trend Over Time

  首选 Line Chart｜Data has a time axis; user needs to observe rise/fall trends or rate of change over a continuous period

• 数据图

  Compare Categories

  首选 Bar Chart (Horizontal or Vertical)｜Comparing discrete categories by magnitude; ranking or ordering is the core insight; categories ≤ 15

• 数据图

  Part-to-Whole

  首选 Pie Chart or Donut｜≤5 categories; one dominant segment vs rest; emphasis on visual proportion over exact values

• 数据图

  Correlation / Distribution

  首选 Scatter Plot or Bubble Chart｜Exploring relationship between two continuous variables; identifying clusters or outliers in a dataset

• 数据图

  Heatmap / Intensity

  首选 Heat Map or Choropleth｜Showing intensity/density across a 2D grid; time-based patterns (e.g., activity by hour × day)

• 数据图

  Geographic Data

  首选 Choropleth Map or Bubble Map｜Data has a regional/location dimension; spatial distribution is the core insight for the user

• 数据图

  Funnel / Flow

  首选 Funnel Chart or Sankey｜Sequential multi-stage process; showing conversion or drop-off rates between defined stages

• 数据图

  Performance vs Target

  首选 Gauge Chart or Bullet Chart｜Single KPI measured against a defined target or threshold; dashboard summary context

• 数据图

  Time-Series Forecast

  首选 Line with Confidence Band｜Historical data + model predictions; communicating uncertainty range to non-technical stakeholders

• 数据图

  Anomaly Detection

  首选 Line Chart with Highlights｜Monitoring a time-series for outliers; alerting users to unexpected spikes or dips in operational data

• 数据图

  Hierarchical / Nested Data

  首选 Treemap｜Showing size relationships within a hierarchy; overview of proportional structure (e.g., budget breakdown)

• 数据图

  Flow / Process Data

  首选 Sankey Diagram｜Showing how quantities flow between nodes; multi-source multi-target distribution

• 数据图

  Cumulative Changes

  首选 Waterfall Chart｜Showing how individual positive/negative components add up to a final total (e.g., P&L, budget variance)

• 数据图

  Multi-Variable Comparison

  首选 Radar / Spider Chart｜Comparing multiple entities across the same fixed set of attributes (e.g., product feature comparison)

• 数据图

  Stock / Trading OHLC

  首选 Candlestick Chart｜Financial time-series with Open/High/Low/Close data; trading or investment product context only

• 数据图

  Relationship / Connection Data

  首选 Network Graph｜Mapping connections between entities; network topology or social graph exploration context

• 数据图

  Distribution / Statistical

  首选 Box Plot｜Showing spread, median, and outliers of a dataset; comparing distributions across multiple groups

• 数据图

  Performance vs Target (Compact)

  首选 Bullet Chart｜Dashboard with multiple KPIs side by side; space-constrained contexts where a gauge is too large

• 数据图

  Proportional / Percentage

  首选 Waffle Chart｜Showing what fraction of a whole is filled; percentage progress in a visually engaging and accessible format

• 数据图

  Hierarchical Proportional

  首选 Sunburst Chart｜Exploring nested proportions where both hierarchy and relative size matter (e.g., org spend breakdown)

• 数据图

  Root Cause Analysis

  首选 Decomposition Tree｜Decomposing a metric into contributing factors; AI-assisted analysis or BI drill-down scenarios

• 数据图

  3D Spatial Data

  首选 3D Scatter / Surface Plot｜Scientific/engineering context where Z-axis carries essential info not expressible in 2D

• 数据图

  Real-Time Streaming

  首选 Streaming Area Chart｜Live monitoring dashboards; IoT/ops data updating at ≥1 Hz; user needs current value at a glance

• 数据图

  Sentiment / Emotion

  首选 Word Cloud with Sentiment｜NLP output visualization; exploratory analysis of text corpus sentiment; frequency-weighted keyword overview

• 数据图

  Process Mining

  首选 Process Map / Graph｜Analyzing event logs to visualize actual process flows; identifying bottlenecks and deviations in ops/product funnels