🇬🇧 English | 🇫🇷 Français

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DSCA — Dynamic System Causal Analysis

From observations to understanding.

DSCA is an open-source project dedicated to the explainable understanding of dynamic systems through causal reasoning.

Rather than creating another diagnostic tool, DSCA aims to build a generic reasoning engine capable of transforming heterogeneous observations into coherent, explainable technical understanding.

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Why DSCA?

Modern systems generate thousands of measurements every second.

Today's diagnostic tools can:

• read fault codes;
• display live data;
• record logs.

However, they rarely explain why systems behave as they do.

DSCA starts where traditional diagnostic tools stop.

Its objective is not simply to analyze data.

Its objective is to understand dynamic systems.

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Project Objectives

DSCA aims to:

• acquire heterogeneous observations;
• normalize measurements into a common language;
• reconstruct system context;
• detect meaningful events;
• identify behavioral patterns;
• generate explainable causal hypotheses;
• accumulate validated knowledge;
• assist human reasoning without replacing it.

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Documentation

Document	English	Français
README	✅	🇫🇷
Manifesto	📖	📖
Lexicon	📖	📖
Fundamental Laws	📖	📖
Data Model	📖	—
Development Roadmap	📖	—
Reasoning Roadmap	📖	—

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Current Status

🚧 Version 0.1.0-dev — Observation

Genesis has been completed.

DSCA is now entering its first development milestone: Observation.

Current work focuses on:

• Signal model
• Canonical Signal model
• DSCA Signal Registry
• Observation model
• Generic CSV importer

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High-Level Architecture

External Data Sources
        │
        ▼
Importers
        │
        ▼
DSCA Signal Registry
        │
        ▼
Observation Model
        │
        ▼
Context Engine
        │
        ▼
Event Engine
        │
        ▼
Behavior Engine
        │
        ▼
Reasoning Engine
        │
        ▼
Knowledge Engine
        │
        ▼
Human Understanding

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Core Principles

DSCA is built upon several fundamental principles:

• Observations always precede hypotheses.
• Context gives meaning to observations.
• Every hypothesis must remain explainable.
• Every hypothesis must remain falsifiable.
• Knowledge is built through validation.
• Human expertise always remains central.

For the complete philosophy of the project, please read the Manifesto.

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Repository Structure

DSCA/

├── README.md
├── README.fr.md
├── MANIFESTO.md
├── MANIFESTO.fr.md
├── LEXICON.md
├── LEXICON.fr.md
├── DSCA_LAWS.md
├── DSCA_LAWS.fr.md
├── DATA_MODEL.md
├── ROADMAP.md
├── REASONING_ROADMAP.md
├── LICENSE
└── src/
    └── dsca/

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Development

The complete development roadmap is available in ROADMAP.md.

The evolution of DSCA's reasoning capabilities is described in REASONING_ROADMAP.md.

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Contributing

DSCA welcomes contributions from:

• software developers;
• automotive engineers;
• diagnostic specialists;
• researchers;
• students;
• enthusiasts interested in dynamic systems.

If you share the project's philosophy, contributions are welcome.

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Motto

Create the future, not simply tomorrow.