ICZNIPNIIndex

ICZNIPNIIndex is a proposed integrative taxonomic index intended to unify nomenclatural data from two major nomenclature communities: the International Code of Zoological Nomenclature (ICZN) and the International Plant Names Index (IPNI). The project envisions cross-linking zoological and botanical names to aid researchers, librarians, and biodiversity informaticians in resolving ambiguities arising from homographs and related nomenclatural acts.

Scope and goals: The index would provide a centralized, cross-kingdom reference that aggregates primary data on names, authors, publication details, ranks, and type information, and would include links to the official registries such as ZooBank for zoological nomenclature and IPNI records for plants. It would facilitate cross-referencing across kingdoms and support bibliographic discovery.

Data sources and content: Core data would draw from ICZN databases (ICZN acts, ZooBank registrations, type specimens when available) and IPNI datasets (plant names, authors, bibliographic citations). It would also document synonymies and cross-references between equally spelled names across kingdoms, aiding disambiguation for researchers.

Identifiers and mapping: The system would assign or map to unified identifiers and establish cross-kingdom mappings for coincident names while respecting each code's nomenclatural rules. It would handle homonyms, basionyms, and later-rank acts with carefully documented provenance.

Status and governance: As of now, ICZNIPNIIndex is a conceptual proposal under discussion by biodiversity informatics communities. Governance would require collaboration among ICZN, IPNI, ZooBank, and other stakeholders to set standards and update procedures.

Access and licensing: The resource would ideally be open data with machine-readable formats and an API to enable programmatic access, subject to licenses of contributing databases and attribution requirements.

Applications and challenges: Potential benefits include improved cross-domain search, bibliographic reconciliation, and enhanced data quality. Challenges include reconciling different nomenclatural rules, maintaining synchronization, and ensuring data quality across two distinct codes.