# GBIF Taxonomy Intelligence (`wakey7dev/gbif-taxonomy-normalizer`) Actor

Resolve species names to accepted GBIF taxonomy — taxon keys, classification hierarchy, occurrence data. Biodiversity research, ecology, conservation.

- **URL**: https://apify.com/wakey7dev/gbif-taxonomy-normalizer.md
- **Developed by:** [Chris Wakefield](https://apify.com/wakey7dev) (community)
- **Categories:** AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

![Chris The Dev](https://raw.githubusercontent.com/chriswakefield87/appstore-screenshot-translator/main/assets/actor-banner.png)

## GBIF Taxonomy & Occurrence Normalizer

Turn the Global Biodiversity Information Facility (GBIF) into clean, analysis-ready biodiversity data. This Actor resolves a searched name to GBIF's accepted taxonomy, fetches occurrence records worldwide, flattens useful Darwin Core fields, preserves raw names for auditability, and removes duplicate records.

### Why this is useful

- **Biodiversity and conservation teams:** build species distribution datasets.
- **Environmental consultants:** prepare evidence for surveys and impact assessments.
- **Researchers and data teams:** obtain reproducible, normalized occurrence data without writing API pagination code.
- **AI and analytics pipelines:** consume stable JSON through Apify's dataset and output URLs.

### Input parameters

| Parameter | Type | Required | Description |
|---|---:|---:|---|
| `scientificName` | string | no | Species or taxon, e.g. `Panthera leo`. |
| `maxResults` | integer | no | 1-300 unique records; default 20. |
| `country` | string | no | Optional ISO country code, e.g. `KE`. |
| `basisOfRecord` | string | no | Optional GBIF record type filter. |

#### Example input

```json
{"scientificName":"Panthera leo","country":"KE","maxResults":10,"basisOfRecord":"HUMAN_OBSERVATION"}
```

### Example output

Each dataset item includes `gbifKey`, cleaned location/date/observer fields, a `taxon` object with accepted taxonomy and `scientificNameRaw`, and a reproducible `sourceUrl`. A readable table is also saved to the `OUTPUT` key-value record; machine-readable `STATS` and the complete `RESULTS` array are saved alongside it.

```json
{"gbifKey":6129864876,"countryCode":"KE","eventDate":"2024-01-01","taxon":{"scientificName":"Panthera leo","taxonKey":5219404,"family":"Felidae"}}
```

### Data source and attribution

Data is retrieved live from the [GBIF API](https://api.gbif.org/), the Global Biodiversity Information Facility. GBIF data is provided under the licences and attribution requirements attached to each contributing dataset; review source metadata before redistribution.

# Actor input Schema

## `scientificName` (type: `string`):

Species or taxon name, for example Panthera leo.

## `maxResults` (type: `integer`):

Maximum unique occurrence records to return (1-300).

## `country` (type: `string`):

Optional two-letter ISO country code, for example KE or GB.

## `basisOfRecord` (type: `string`):

Optional GBIF filter: HUMAN\_OBSERVATION, MACHINE\_OBSERVATION, PRESERVED\_SPECIMEN, or OBSERVATION.

## Actor input object example

```json
{
  "scientificName": "Panthera leo",
  "maxResults": 20
}
```

# Actor output Schema

## `dataset` (type: `string`):

Occurrence records with cleaned fields and normalized taxonomy.

## `summary` (type: `string`):

Human-readable run summary.

## `stats` (type: `string`):

Machine-readable run statistics.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("wakey7dev/gbif-taxonomy-normalizer").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("wakey7dev/gbif-taxonomy-normalizer").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call wakey7dev/gbif-taxonomy-normalizer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,wakey7dev/gbif-taxonomy-normalizer"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/riw2EM2FUeLbrFwwc/builds/4GvrM4BCELRkIEl7v/openapi.json