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A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

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Taxonomy as an eScience.

Benjamin R Clark¹, H Charles J Godfray, Ian J Kitching

¹Department of Zoology, University of Oxford, Oxford OX1 3PS, UK.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences

|December 18, 2008

Summary

This summary is machine-generated.

The CATE project offers a Web-based system for consolidating biological taxonomy, enabling community input and peer review for taxonomic updates. This approach enhances access to fragmented taxonomic knowledge.

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Area of Science:

Biological Taxonomy
Bioinformatics
Computational Biology

Background:

Biological taxonomy is fragmented across numerous historical publications.
The Internet offers potential for wider access to this dispersed knowledge.
Current taxonomic information lacks a centralized, accessible platform.

Purpose of the Study:

To propose a Web-based system (CATE project) for consolidated biological taxonomies.
To facilitate community contributions and peer review for taxonomic updates.
To improve accessibility and management of taxonomic data.

Main Methods:

Development of the CATE (Consolidated Approaches to Taxonomic Editing) project system.
Implementation of a workflow for online submission of taxonomic proposals (e.g., new species, synonymies).
Integration of online peer review for quality control within the editorial process.

Main Results:

A functional CATE system architecture designed for collaborative taxonomic revision.
A workflow enabling community-driven additions and changes to consolidated taxonomies.
Emphasis on expert judgment over automated aggregation for taxonomic accuracy.

Conclusions:

The CATE project provides a framework for a dynamic, community-curated biological taxonomy.
Web-based revisions and peer review can overcome fragmentation of taxonomic knowledge.
The system supports expert-driven consensus building in biological classification.