A semi-automated workflow for biodiversity data retrieval, cleaning, and quality control

Area of Science:

• Biodiversity Informatics
• Computational Biology
• Ecological Modeling

Background:

• Species distribution analyses require extensive data compilation and cleaning.
• Understanding diverse data formats and service APIs from biodiversity infrastructures is challenging.
• Existing processes are time-consuming and require specialized knowledge.

Purpose of the Study:

• To design and implement an automated workflow for refining biodiversity data.
• To simplify the integration of taxonomic data retrieval, cleaning, and selection.
• To create a user-friendly system that masks the complexity of underlying informatics infrastructures.

Main Methods:

• Development of a Taverna-based workflow.
• Integration of multiple data processing steps including taxonomic data retrieval and cleaning.
• Implementation of a standards-based system for data management.

Main Results:

• A functional Data Refinement Workflow was created.
• The workflow integrates disparate data sources and processing steps seamlessly.
• The system effectively hides the complexity of biodiversity informatics service APIs.

Conclusions:

• The Taverna-based workflow significantly streamlines the preparation of data for species distribution studies.
• The system enhances accessibility for researchers by simplifying data handling.
• The workflow is available for local use and via a web portal, requiring no additional software installation.