A logic approach to modelling nomenclatural change.

Area of Science:

• Computational logic
• Taxonomy
• Bioinformatics

Background:

• Nomenclature principles govern biological classification.
• Current systems face challenges with large datasets and complex reclassifications.
• Automating nomenclatural changes is crucial for taxonomic databases.

Purpose of the Study:

• To demonstrate the tractability of nomenclature principles in computational logic.
• To develop and test an Answer Set Programming (ASP) model for nomenclatural emendations.
• To explore the implications of taxonomic reinterpretation on nomenclature.

Main Methods:

• Designed a 20-taxon use case based on the International Code of Zoological Nomenclature.
• Implemented an ASP transition system to model nomenclatural rules (Binomial Nomenclature, Priority, Homonymy, Typification, Gender Agreement).
• Simulated 36 scenarios involving type specimen reinterpretation and analyzed required emendations.

Main Results:

• The ASP system accurately inferred code-mandated nomenclatural changes for all simulated scenarios.
• Each scenario required 1-14 logically contingent emendations.
• The system visually outputted the resulting nomenclatural conditions.

Conclusions:

• Answer Set Programming is a viable approach for computational nomenclature.
• This work provides a foundation for logic-based services for nomenclatural optimization and validation.
• Logic-based exploration can reveal design biases in nomenclature and inform future identifier systems.