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Tagged: Architecture

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Architecture
65 pages
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System design, architecture decisions, and data flow

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Ch 12 deliverable B: Beyond the known engine landscape — long-horizon directions

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Fresh-agent research deliverable that expanded well beyond Challenge 12's narrow Datalog-vs-SQL scope into a long-horizon architectural survey. Identifies engines absent from Challenges 10/11 (Stoolap, Minigraf, HelixDB, Comunica, sqlite-vec, cr-sqlite, Ascent, Percival, declarative-dataflow, Feldera/DBSP), proposes LinkML as canonical schema substrate (auto-generates JSON Schema, OWL, SHACL, Pydantic, TypeScript), proposes IPLD content-addressed crosswalk distribution, and proposes a Tier 1.5 compilation pipeline producing Parquet/HDT/JSON-LD/OSCAL/IPLD-CAR artifacts.

Ch 19 deliverable: Over-engineering stress test — radically simplify with narrow tiered escape hatch

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Fresh-agent adversarial research deliverable for Challenge 19. Bottom line: the architecture has lost the property of 'simpler thing becomes default because it's more adoptable.' Five concrete arguments: (1) competitive landscape (Hyperproof/Drata/Vanta hide crosswalk complexity from users; Excel + SharePoint baseline is what Crosswalker actually competes with); (2) SSSOM has zero GRC adoption (~50K downloads/month all biomedical); STRM (NIST IR 8477) + OSCAL is what NIST OLIR / SCF actually use; (3) audit trail wildly over-specified vs FRE 902(13)/(14) requirements (hash + qualified-person cert + git is the legal floor); (4) 5 MB three-engine WASM bundle is 10–50× Obsidian plugin median; SCF (1,400 controls × 261 frameworks) ships as one Excel file; recursive CTEs handle 3-hop closures over 10K edges in single-digit ms; (5) concrete 'simple default' proposal: markdown + YAML frontmatter (STRM) + git + signed releases + Dataview + STRM-TSV/OSCAL export, under 500 KB. Layered engines as separate opt-in companion plugins.

Consistency models

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ACID, CAP theorem, eventual consistency, and BASE — applied to Obsidian vaults and Crosswalker imports.

Embedded vs server substrates — the file-IS-the-database pattern

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SQLite's quiet revolution was bringing database semantics into the file-based world — "the library, not the server." Crosswalker's three-tier architecture leans hard into that philosophy. This page maps the embedded-database landscape across every data model (relational, RDF, property graph, document, key-value, vector, Datalog, multi-model) and shows which engines are file-based, which are server-only, and which Crosswalker has evaluated.

File-based graph databases

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How markdown vaults function as property graph databases — formal model, trade-offs, and patterns for storing structured relationships in files.

Institutional landscape

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The entities, relationships, and dynamics of who creates, maintains, maps, mandates, and consumes structured ontologies — the human side of ontology management.

Ontology lifecycle

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The lifecycle of an ontology within the Crosswalker ecosystem — from acquisition through import, enrichment, maintenance, and sharing.

Operational landscape

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Who does what work across the ontology ecosystem — institutions × components × resources. The combined view of effort, ownership, and sustainability.

System architecture — components, tiers, and data flow

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One-page canonical view of Crosswalker's architecture. Three storage tiers (source, canonical Markdown, derived SQLite); six logical layers (import, storage, projection, query, export, audit); the components inside each layer; what reads what; where to look in code + docs. Simplified TL;DR up front, progressively more detail below.

What makes Crosswalker unique

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The core differentiators and novel contributions — why this isn't just another importer, and what the short vs long term vision looks like.

Architecture

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Core components, data flow, and system design.

Config selection

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How Crosswalker matches and suggests saved configurations.