SDCStudio Quick Start Guide

Welcome to SDCStudio!

SDCStudio is an AI-powered data modeling platform that helps you create, manage, and generate SDC4-compliant data models and applications. This guide will get you up and running in minutes with the React-based web interface.

What You'll Learn

  • How to navigate the React SPA interface
  • How to configure your Settings and upload ontologies
  • How to create your first data model
  • How to upload and process data files
  • How to generate XSD schemas and XML instances

Prerequisites

  • A modern web browser (Chrome, Firefox, Safari, Edge)
  • Data files to work with (CSV, Markdown, or other supported formats)
  • (Optional) Project/domain specific ontologies or vocabularies in Turtle (.ttl) format

Step 1: Access SDCStudio

  1. Open your browser and navigate to https://sdcstudio.axius-sdc.com
  2. Sign in with your account credentials
  3. Welcome to the React SPA! You'll see a modern single-page application interface

Step 2: Configure Your Settings (Important!)

Before creating models, configure your profile and upload ontologies:

  1. Click the Settings icon (gear/cog) in the top navigation bar
  2. You'll see three tabs: Profile, Ontologies, and Preferences

Why Upload Ontologies? - Improves AI understanding of your specific domain - Provides better semantic suggestions - Ensures consistency with your organization's vocabulary - Enhances data model quality

Important Note: - Standard ontologies (FHIR, NIEM, SNOMED, LOINC, schema.org) are already built into SDCStudio - Only upload your organization's custom or local domain ontologies - Upload vocabularies specific to your business that aren't in standard collections

How to Upload:

  1. Click the "Ontologies" tab in Settings
  2. Prepare your custom ontology files:
  3. Format: Turtle (.ttl) format
  4. Your organization's data dictionary
  5. Project-specific vocabulary
  6. Industry terminology not in standard ontologies
  7. Click "Upload Ontology"
  8. Select your .ttl file(s)
  9. Add metadata:
  10. Name: Descriptive name (e.g., "Company Product Catalog")
  11. Description: Purpose and scope
  12. Namespace: Your organization's namespace URI
  13. Click "Save"

Your custom ontologies are now available for AI processing and semantic enrichment!

Configure Your Profile

  1. Click the "Profile" tab
  2. Update your information:
  3. Display name
  4. Email preferences
  5. Organization details
  6. Save changes

Step 3: Navigate the Interface

The React SPA provides intuitive navigation:

  • Dashboard - Overview of your projects and recent activity
  • Projects - Create and manage projects
  • Data Sources - View uploaded files and processing status
  • Data Models - Browse and edit your data models
  • Components - Manage reusable data components
  • Settings - Configure profile, ontologies, and preferences

Key Interface Features

  • Real-time Updates: The interface refreshes automatically as AI processes your data
  • Status Indicators: Color-coded status badges show processing progress
  • Contextual Actions: Buttons and menus appear based on what you're viewing
  • Search and Filter: Quickly find models, components, and data sources

Step 4: Create Your First Project

  1. Navigate to "Projects" in the main navigation
  2. Click "Create New Project" button
  3. Fill in project details:
  4. Name: Choose a descriptive name (e.g., "Customer Analytics")
  5. Description: Brief description of your project's purpose
  6. Domain: Select relevant domain (Healthcare, Finance, etc.)
  7. Click "Create Project"

Step 5: Upload Your Data

  1. Open your project by clicking on it
  2. Navigate to "Data Sources" tab
  3. Click "Upload Data" button
  4. Choose your file:
  5. CSV files: Spreadsheet data with headers (recommended for first attempt)
  6. Markdown files: Structured text documents
  7. JSON/XML: Structured data files
  8. Click "Upload" and watch the magic happen!

Step 6: Watch AI Processing (The Two-Stage Pipeline)

SDCStudio processes your data in two intelligent phases:

Phase 1: Structural Parsing (Fast - 30 seconds to 2 minutes)

Status Badge: UPLOADING → PARSING → PARSED

What's Happening: - File format detected and validated - Columns/fields identified - Basic data types inferred (XdString, XdCount, XdTemporal, etc.) - Structure mapped for AI analysis

The interface updates automatically - you'll see the status badge change in real-time!

Phase 2: AI Enhancement (Comprehensive - 1-5 minutes)

Status Badge: AGENT_PROCESSING → COMPLETED

What's Happening: - Semantic Analysis: AI understands what each field represents - Pattern Recognition: Identifies email patterns, phone formats, etc. - Ontology Matching: Uses your uploaded ontologies for suggestions - Validation Rules: Recommends appropriate constraints - Relationship Detection: Finds logical groupings and connections

Your ontologies are working here! The AI uses them to make better suggestions.

Step 7: Review Your Generated Data Model

Once status shows COMPLETED:

  1. Navigate to "Data Models" tab in your project
  2. Click on your generated model (named after your file)
  3. Explore what the AI created:
  4. Data Model: Top-level structure
  5. Clusters: Logical groupings of related fields
  6. Components: Individual data elements with types and validation

What the AI Generated

The AI created SDC4-compliant components with: - Appropriate Data Types: XdString for text, XdCount for integers, XdTemporal for dates, etc. - Validation Rules: Pattern matching, range constraints, required fields - Semantic Enrichment: Descriptions and labels based on your ontologies - Relationships: Logical groupings in clusters

Step 8: Customize Your Model (Optional)

You can refine the AI's work:

  1. Click on a component to edit it
  2. Modify properties:
  3. Data type
  4. Validation rules
  5. Labels and descriptions
  6. Required/optional status
  7. Save changes
  8. Repeat for other components as needed

Step 9: Publish Your Model

Publishing makes your model available for schema generation:

  1. In your Data Model view, click "Publish" button
  2. Review the model summary
  3. Confirm publication
  4. Status changes to PUBLISHED

Step 10: Generate Outputs

Now you can generate various outputs:

Available Outputs

  • XSD Schema: XML Schema Definition for validation
  • XML Instance: Example XML document
  • JSON Schema: JSON Schema Definition
  • JSON-LD: Linked data schema
  • HTML Documentation: Human-readable documentation
  • RDF Triples: Semantic web integration
  • SHACL: Schema validation constraints
  • GQL: Graph database queries

How to Generate

  1. Click "Generate" dropdown in your model view
  2. Select output type
  3. Configure options (if applicable)
  4. Click "Generate"
  5. Download your generated file

Common File Types and Processing

  • Best for: Tabular data, spreadsheets, database exports
  • Processing: Column-by-column analysis with intelligent type detection
  • AI Strength: Excellent at pattern recognition and validation

Markdown Files

  • Best for: Documentation, specifications, requirements
  • Processing: Hierarchical structure analysis
  • AI Strength: Good at understanding relationships and context

JSON/XML Files

  • Best for: Structured data with existing schema
  • Processing: Direct structure parsing
  • AI Strength: Fast processing with schema preservation

Tips for Success

🎯 Start with Settings

  • Upload ontologies before your first data model
  • Better ontologies = better AI suggestions
  • Update ontologies as your domain knowledge grows

📊 Start Simple

  • Begin with a small CSV file (5-10 columns)
  • Understand the workflow before tackling complex data
  • Experiment with different file types

🔄 Iterate

  • The AI learns from your corrections
  • Customize generated components to teach the system
  • Build a library of reusable components

🏷️ Use Meaningful Names

  • Clear project names help organization
  • Descriptive component labels improve usability
  • Good documentation makes collaboration easier

Troubleshooting

Upload Issues

  • File Too Large: Break into smaller files (< 10MB recommended)
  • Unsupported Format: Convert to CSV or Markdown
  • Encoding Errors: Ensure UTF-8 encoding

Processing Issues

  • Stuck in PARSING: Refresh the page, check file format
  • AGENT_ERROR: Click "Retry" button, check error log
  • Slow Processing: Large files take longer - be patient

Interface Issues

  • Page Not Updating: The interface auto-refreshes every 60 seconds
  • Missing Buttons: Ensure model is in correct state (e.g., published)
  • Navigation Confusion: Use breadcrumbs at top to track location

Next Steps

Now that you've completed your first workflow:

  1. Explore More Features
  2. Data Modeling Guide - Advanced modeling techniques
  3. Semantic Enhancement - Ontology best practices

  4. Generating Outputs - All output formats

  5. Upload More Ontologies

  6. Add domain-specific vocabularies
  7. Use standard ontologies (FHIR, NIEM, etc.)

  8. Create custom ontologies for your organization

  9. Try Different Data Types

  10. Temporal data with XdTemporal
  11. Quantified data with XdQuantity (includes units!)

  12. Complex structures with nested clusters

  13. Build Your Component Library

  14. Create reusable components
  15. Share components across projects
  16. Establish organization standards

Getting Help

  • Documentation: User Guides for detailed features
  • Troubleshooting: Troubleshooting Guide
  • Support: support@axius-sdc.com
  • Community: Join user discussions and share experiences

Success Checklist

You're ready to move forward when you can:

✅ Navigate the React SPA interface confidently ✅ Configure Settings and upload ontologies ✅ Create projects and upload data files ✅ Understand the two-stage AI processing pipeline ✅ Review and customize generated data models ✅ Publish models and generate outputs ✅ Troubleshoot common issues

Ready for a detailed walkthrough? Check out Your First Data Model for a step-by-step tutorial with example data.