Executive summary — Supply Chain is an interactive market-cap landscape for 100 public companies, with company-level dependency profiles where source material has been reviewed. The global overview has no company-to-company relationship edges because the repository has no verified global edge list. Profiles distinguish cited company disclosures, source-backed sector context, and companies still awaiting relationship research. The browser-served market-cap snapshot is rebuilt from the public CSV by the scheduled workflow.
- Interactive D3 company landscape of 100 public companies, organised by economic layer (semiconductors → materials → industrials → finance → consumer demand) and country. Overview layout proximity does not imply a supplier relationship.
- Per-company profile cards mapping each anchor company's upstream inputs, services & risk, channels, and demand relationships.
- Visible evidence labels — profile relationships show a source reference where available and a confidence band (e.g. high (company disclosure), medium (source-backed)). An unresolved reference is explicitly lower confidence.
- Credit-rating overlay generated from a dedicated ratings dataset for additional risk context.
- Auto-updating market caps — a scheduled GitHub Actions workflow rebuilds the browser-served map and rankings weekly from the public CSV. The displayed timestamp belongs to that served snapshot.
- Zero-backend, static delivery — vanilla JavaScript + D3 served from GitHub Pages; nothing to provision, fast to load.
- Test-guarded data integrity — a Node test suite enforces provenance wiring, confidence scoring, country-code hygiene, and UI integrity before anything ships.
Supply Chain pairs a ranked company landscape with source-labelled company profiles. The overview is a way to find companies; the profile is where a documented relationship or sector dependency can be examined.
Global map. The landing view is a force-directed D3 layout of 100 anchor companies positioned across ten economic layers and coloured by country of domicile. Node size and labels carry rank and market cap. It has no relationship edges: spatial proximity and layer adjacency are visual layout, not evidence of trade between two firms.
Company profiles. Selecting a company opens a focused sub-graph centred on that firm, decomposed into tiers — Upstream Inputs, Services & Risk, the Company anchor, Channels, and Demand. Each node states what it represents and why it matters to the anchor.
Risk context. A credit-ratings overlay adds rating context on top of the structural map, helping analysts weigh exposure alongside topology.
Trust signals. Confidence bands and source references are first-class — surfaced in the UI rather than buried in a data file — so an analyst can see how much to trust a given relationship at a glance.
Per Monarch Castle doctrine — evidence before assertion. Supply Chain is built so that no number stands alone:
- Market-cap rankings are sourced from
companiesmarketcap.com(public CSV export). The dataset'smetablock records the originatingsourceURL and alastUpdated/generatedAttimestamp on every regeneration. - Credit ratings are generated from a dedicated ratings pipeline (Fitch public search endpoint) into
data/credit-ratings.*, with the source endpoint recorded in the data. - Relationship-level provenance. Each profile node and link carries a
sourceIdand aconfidencelabel (for examplehigh (company disclosure),medium (source-backed),medium (structural)), so collection method and trust level travel with the datum. - Auditability. The auto-update workflow timestamps backups and commits, and validation tests run before any refreshed data is published — keeping the source → extraction → store → dashboard chain intact and reproducible.
Lawful collection only: data is drawn from open, publicly accessible sources and official-style endpoints; provenance and confidence are preserved end-to-end as the product's core value.
- Frontend / visualisation: Vanilla JavaScript + D3.js 7 (CDN-loaded), modular
js/packages —viz,ui,data,trust,analytics. - Styling: Hand-authored CSS (
styles/base,layout,components,theme). - Data tooling: Node.js 20+ ES-module scripts (
scripts/) for generation, market-cap updates, ratings fetch, macro data, and verification. - Testing: Node's built-in test runner (
node --test) plus Playwright for mobile/keyboard and UI integrity checks. - Automation: GitHub Actions —
auto-update-data.yml(weekly market-cap refresh) anddeploy-pages.yml(static build & deploy). - Hosting: GitHub Pages (static
_siteartifact).
Live site: https://monarchcastletech.github.io/supplychain/
Run locally
npm install
npx http-server . -p 8080
# open http://localhost:8080Regenerate / refresh data
node scripts/generate-top100-data.mjs # build the top-100 company map
node scripts/update-marketcap-data.mjs # refresh market caps and merge profiles
node scripts/fetch-fitch-ratings.mjs # build the credit-ratings dataset
node scripts/verify-data.mjs # run data verification checksTest
npm test # full data + UI integrity suite
node --test tests/profile-link-metadata.test.mjs # focused runDeploy. Pushing to master triggers deploy-pages.yml, which assembles the static site (index.html, data/, js/, styles/, assets/) and publishes it to GitHub Pages. Market-cap data refreshes automatically every Monday via auto-update-data.yml, committing only when values change.
A product of Financial Intelligence · Monarch Castle Technologies — an operating company of Monarch Castle Holdings. Sister companies: Monarch Castle Technologies · Strategic Data Company of Ankara
See LICENSE. © 2026 Monarch Castle Holdings · Ankara, Türkiye.
Interactive market-cap & supply-chain intelligence map for the top 100 public companies — D3 dashboard with source-linked provenance, auto-updated weekly.
Lifecycle: Active. The badge and this statement describe maintenance status, not service availability.
The preview is maintained as a repository asset; the live interface or generated output remains authoritative.
These repository-specific sources define the methodology or provenance boundary. Source dates, transformation steps, and known gaps must travel with analytical outputs.
The published data workflow targets a weekly refresh and records source-linked provenance.
npm cipython -m http.server 8080Run only in a trusted development environment and review repository-specific prerequisites before using networked or hardware features.
js/— repository-specific implementation, data, or configuration boundary.data/— repository-specific implementation, data, or configuration boundary.scripts/— repository-specific implementation, data, or configuration boundary.
npm testOriginal software history is maintained in Git. External datasets, reports, trademarks, screenshots, and assets are not relicensed by this repository; see THIRD_PARTY_NOTICES.md before reuse.
This repository does not publish a guaranteed forecast. Any scenarios, scores, or forward-looking language are analytical aids, not facts or advice; review source dates and methodology before use.
Do not publish vulnerabilities in an issue. Use GitHub's private vulnerability-reporting flow when available, or follow the organization security policy.
Original repository code and documentation are available under MIT; see LICENSE. That license does not override third-party terms documented in THIRD_PARTY_NOTICES.md.
Use the machine-readable CITATION.cff. Cite the specific commit and, for analytical use, record the data or model snapshot date.
Supply Chain Intelligence is a Monarch Castle Technologies project. Part of Monarch Castle Technologies.


