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Upload Dataset Workflow

The Upload Dataset Workflow on the Gesund.ai platform provides a structured, intuitive path for managing datasets—from initial upload to metadata entry and eventual deletion. This guide walks users through each step to ensure a streamlined and secure experience.

Upload Dataset Workflow

What Does This Workflow Cover?​

This module allows you to:

  • Upload datasets from your local system or cloud
  • Enter meaningful metadata and organize datasets
  • Store and index datasets for search and filtering
  • Delete datasets safely when no longer needed

Workflow Steps​

1. Upload Dataset​

  • Start by selecting your dataset file.
  • Upload can be done via:
    • Direct file upload
    • Cloud connection (e.g., AWS S3)
  • The dataset is then processed and made ready for platform operations.

2. Add Dataset Information​

  • After upload, provide structured metadata:
    • Name
    • Description
    • Tags
    • Custom metadata fields
  • The interface guides users with clear input fields and validation rules.
  • This step ensures datasets are well-documented and easily searchable.

3. Store Dataset Metadata​

  • All dataset metadata is securely stored in the platform’s backend.
  • This enables:
    • Fast retrieval
    • Filtering by tags or other metadata
    • Linking datasets with annotation, analysis, or validation modules

4. Delete Dataset​

  • Datasets can be deleted if they’re no longer needed.
  • The delete process includes:
    • Dataset selection
    • Confirmation modal to avoid accidental deletions
  • Clean removal ensures storage efficiency and data hygiene.

Why Use This Workflow?​

  • Easy drag-and-drop or API-based dataset registration
  • Structured metadata input for better organization
  • Full control over dataset lifecycle
  • Seamless integration with annotation, analysis, and validation pipelines

The Upload Dataset Workflow ensures all your datasets are clearly defined, accessible, and ready for use across the Gesund.ai ecosystem.