|
|
--- |
|
|
language: |
|
|
- fr |
|
|
tags: |
|
|
- france |
|
|
- public-sector |
|
|
- embeddings |
|
|
- directory |
|
|
- open-data |
|
|
- government |
|
|
- etalab |
|
|
pretty_name: French Local Administrations Directory |
|
|
size_categories: |
|
|
- 10K<n<100K |
|
|
license: etalab-2.0 |
|
|
--- |
|
|
|
|
|
# 🇫🇷 French Local Administrations Directory Dataset |
|
|
|
|
|
This dataset is a processed and embedded version of the public data **Annuaire de l’administration - Base de données locales** (French Local Administrations Directory), published on [data.gouv.fr](https://www.data.gouv.fr/datasets/service-public-fr-annuaire-de-l-administration-base-de-donnees-locales/). |
|
|
This information is also available on the official directory website of Service-Public.fr: https://lannuaire.service-public.fr/ |
|
|
|
|
|
The dataset provides semantic-ready, structured and chunked data of French **local** public entities, including organizational details, missions, contact information, and hierarchical links. Each chunk of text is vectorized using the [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3) embedding model to enable semantic search and retrieval tasks. |
|
|
|
|
|
--- |
|
|
|
|
|
## 🗂️ Dataset Contents |
|
|
|
|
|
The dataset is provided in **Parquet format** and contains the following columns: |
|
|
|
|
|
| Column Name | Type | Description | |
|
|
|------------------------|-----------------------------|-----------------------------------------------------------------------------| |
|
|
| `chunk_id` | `str` | Unique source based identifier of the chunk | |
|
|
| `types` | `str` | Type(s) of administrative entity. | |
|
|
| `name` | `str` | Name of the organization or service. | |
|
|
| `mission_description` | `str` | Description of the entity's mission. | |
|
|
| `addresses` | `list[dict]` | List of address objects (street, postal code, city, etc.). | |
|
|
| `phone_numbers` | `list[str]` | List of telephone numbers. | |
|
|
| `mails` | `list[str]` | List of contact email addresses. | |
|
|
| `urls` | `list[str]` | List of related URLs. | |
|
|
| `social_medias` | `list[str]` | Social media accounts. | |
|
|
| `mobile_applications` | `list[str]` | Related mobile applications. | |
|
|
| `opening_hours` | `str` | Opening hours. | |
|
|
| `contact_forms` | `list[str]` | Contact form URLs. | |
|
|
| `additional_information` | `str` | Additional information. | |
|
|
| `modification_date` | `str` | Last update date. | |
|
|
| `siret` | `str` | SIRET number. | |
|
|
| `siren` | `str` | SIREN number. | |
|
|
| `people_in_charge` | `list[dict]` | List of responsible persons. | |
|
|
| `organizational_chart` | `list[str]` | Organization chart references. | |
|
|
| `hierarchy` | `list[dict]` | Links to parent or child entities. | |
|
|
| `directory_url` | `str` | Source URL from the official state directory website. | |
|
|
| `chunk_text` | `str` | Textual content of the administrative chunk. | |
|
|
| `embeddings_bge-m3` | `str` (stringified list) | Embeddings of `chunk_text` using `BAAI/bge-m3`. Stored as a JSON array string. | |
|
|
|
|
|
--- |
|
|
|
|
|
## 🛠️ Data Processing Methodology |
|
|
|
|
|
### 📥 1. Field Extraction |
|
|
|
|
|
The following fields were extracted and/or transformed from the original JSON: |
|
|
|
|
|
- **Basic fields**: `chunk_id`, `name`, `types`, `mission_description`, `additional_information`, `siret`, `siren`, `directory_url`, `modification_date` are directly extracted from JSON attributes. |
|
|
- **Structured lists**: |
|
|
- `addresses`: list of dictionaries with `adresse`, `code_postal`, `commune`, `pays`, `longitude`, and `latitude`. |
|
|
- `phone_numbers`, `mails`, `urls`, `social_medias`, `mobile_applications`, `contact_forms`: derived from their respective fields with formatting. |
|
|
- **People and structure**: |
|
|
- `people_in_charge`: list of dictionaries representing staff members or leadership (title, name, rank, etc.). |
|
|
- `organizational_chart`, `hierarchy`: structural information within the administration. |
|
|
- **Other fields**: |
|
|
- `opening_hours`: built using a custom function that parses declared time slots into readable strings. |
|
|
|
|
|
### ✂️ 2. Generation of `chunk_text` |
|
|
|
|
|
A synthetic text field called `chunk_text` was created to summarize key aspects of each administrative body. This field is designed for semantic search and embedding generation. It includes: |
|
|
|
|
|
- The entity’s name : `name` |
|
|
- Its mission statement (if available) : `mission_description` |
|
|
- Key responsible individuals (formatted using role, title, name, and rank) : `people_in_charge` |
|
|
|
|
|
There was no need here to split characters here. |
|
|
|
|
|
### 🧠 3. Embeddings Generation |
|
|
|
|
|
Each `chunk_text` was embedded using the [**`BAAI/bge-m3`**](https://huggingface.co/BAAI/bge-m3) model. |
|
|
The resulting embedding vector is stored in the `embeddings_bge-m3` column as a **string**, but can easily be parsed back into a `list[float]` or NumPy array. |
|
|
|
|
|
## 📌 Embeddings Notice |
|
|
|
|
|
⚠️ The `embeddings_bge-m3` column is stored as a stringified list (e.g., `"[-0.03062629,-0.017049594,...]"`). |
|
|
To use it as a vector, you need to parse it into a list of floats or NumPy array. For example: |
|
|
|
|
|
```python |
|
|
import pandas as pd |
|
|
import json |
|
|
|
|
|
df = pd.read_parquet("local-administrations-directory-latest.parquet") |
|
|
df["embeddings_bge-m3"] = df["embeddings_bge-m3"].apply(json.loads) |
|
|
``` |
|
|
|
|
|
## 📚 Source & License |
|
|
|
|
|
## 🔗 Source : |
|
|
- [Lannuaire.Service-Public.fr](https://lannuaire.service-public.fr/) |
|
|
- [Data.Gouv.fr : Service-public.fr - Annuaire de l’administration - Base de données locales](https://www.data.gouv.fr/datasets/service-public-fr-annuaire-de-l-administration-base-de-donnees-locales/) |
|
|
|
|
|
## 📄 Licence : |
|
|
**Open License (Etalab)** — This dataset is publicly available and can be reused under the conditions of the Etalab open license. |
