Ethnomycological Data on Psilocybe spp. (2022–2024)

Overview

This dataset is part of the PsiloSoma Project, an independent research initiative focused on ethnomycology, fungal ecology, and biogeography. It provides a curated and georeferenced collection of occurrence records for species within the genus Psilocybe, collected between 2022 and 2024, and integrates both original field observations and verified literature records.

The dataset is structured according to the Darwin Core (DwC) standard to ensure interoperability with global biodiversity infrastructureres

The PsiloSoma Project aims to document the distribution, ecology, and ethnomycological relevance of Psilocybe species and other psychotropic fungi. The project combines field research, literature review, and data curation to contribute to biodiversity knowledge and open science.

This dataset represents a hybrid data resource integrating:

• Original field observations (new records)

• Literature-based occurrences from published studies

• Ecological and habitat data

• Ethnomycological context where available

Dataset Description

The dataset includes:

• Georeferenced occurrence records

• Taxonomic identification based on morphological analysis

• Ecological metadata (habitat, elevation)

• Temporal data (eventDate in ISO 8601 format)

• Distinction between field observations and literature records

• Source attribution for each record

Coordinates were obtained via GPS or derived from reliable sources and validated during curation.

Methodology

Data collection and validation followed these principles:

• Field observations conducted between 2022–2024

• Morphological identification based on macroscopic and microscopic features

• Comparison with peer-reviewed mycological literature

• Integration of published records from scientific sources

• Georeferencing using GPS devices or validated geospatial tools

• Assignment of coordinate uncertainty values based on data source

• Standardization using Darwin Core terms

• Internal quality control and consistency checks

Records are categorized as:

• HumanObservation → original field data

• MaterialCitation → literature-derived records