Introduction

Wellcome to the Danube Data Cube documentation.

Contents:

• Danube Data Cube Platform
  • Concept
• Platform Services
  • Dynamic Data Cube
    • Service logic
    • Create and access Data Cubes
  • Algo Hosting
• API
  • AOI Manager
    • Create AOI
    • Get AOI
  • Crop Model
    • Run model
  • Crop
    • Crop Type
    • Crop Variety
    • List available phenological models
• Python package
  • Submodules
  • ddc_utility.auth module
    • OAuth2BearerHandler
  • ddc_utility.client module
    • BaseClient
    • DdcClient
    • authorize_request()
    • authorize_s3_access()
  • ddc_utility.constants module
  • ddc_utility.cube module
    • open_cube()
  • ddc_utility.errors module
    • BadRequest
    • DdcClientError
    • DdcConfigurationError
    • DdcException
    • DdcRequestError
    • Forbidden
    • HTTPException
    • NotFound
    • ServerError
    • TooManyRequests
    • Unauthorized
  • ddc_utility.logger module
  • ddc_utility.utils module
    • Geometry
    • IrrigationSchedule
    • TimeRange
  • Module contents
• Data onboarding
  • Free and open data
  • Commercial data providers
  • Data specification guidelines
  • Draft agreement
  • Contact
• Information Product onboarding
• Onboarding Algorithms to the Information Factory
  • Overview
  • Architecture
    • Result Management Options
  • Algorithm Registry
  • Execution Parameters
    • Example Parameter:
  • Execution Lineage and Logging
  • Steps to Publish Your Algorithm
  • Steps to Update Your Algorithm
• Information Factory Algorithm Hosting
  • Key Features
    • Integrated Data Access
    • Algorithm Execution and Monitoring
    • Example: Harshness Map
    • Flexibility in Onboarding Algorithms
    • Visualization and Analysis
  • Architecture Overview
  • Getting Started
  • Information Factory Value

Indices and tables

• Index

• Module Index

• Search Page