Add dataset card, license, and Parquet shards (viewer)

LICENSE.md

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+# Licensing
+
+This dataset combines two layers under **different** licenses. Read both before reuse.
+
+## 1. Tooling and packaging — Apache-2.0
+
+The database schema, the FAISS index, the BM25 index, the embeddings, the Parquet packaging,
+and this dataset card are released under the **Apache License 2.0**, consistent with the
+canonical Zenodo record (DOI [10.5281/zenodo.20586256](https://doi.org/10.5281/zenodo.20586256)).
+
+## 2. Source snippets (the `code` field) — upstream free/open-source licenses
+
+The `code` values in `snippets.db` and in the Parquet shards are **excerpts derived from upstream
+MediaWiki / Wikimedia repositories**. Each excerpt remains under **the license of its origin
+repository** — predominantly **GPL-2.0-or-later**, with some MIT, BSD, Apache-2.0, and others.
+The Apache-2.0 grant in section 1 does **not** relicense this upstream code.
+
+There is **no per-row `license` column** in the data. Instead, **every entity carries a Software
+Heritage identifier (`swhid`)** with an `origin=` qualifier (and `lines=` range). This lets you
+resolve the exact upstream repository, revision, and file — and therefore the authoritative
+license and copyright — via:
+
+- Software Heritage: <https://archive.softwareheritage.org/>
+- the `origin=` repository URL embedded in each SWHID.
+
+## Caveats
+
+- Snippets are **fragments** (individual functions, types, or templates) and may not carry the
+  original file's license header or copyright notice. **Consult the origin repository before
+  redistributing or reusing** a snippet.
+- If you are a copyright holder and believe a snippet should not be redistributed here, please
+  open an issue on the GitHub repository
+  (<https://github.com/ftosoni/mediawiki-code2code-search>) or contact the author; it will be
+  removed promptly.
+
+## Summary
+
+| Layer | License |
+|---|---|
+| Schema, indexes, embeddings, packaging, card | Apache-2.0 |
+| `code` snippets | Upstream FOSS licenses (predominantly GPL-2.0-or-later); resolve per entity via `swhid` |

README.md

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+---
+pretty_name: MediaWiki Code2Code Search
+license: other
+license_name: apache-2.0-tooling-plus-upstream-foss
+license_link: LICENSE.md
+language:
+- code
+task_categories:
+- text-retrieval
+- sentence-similarity
+- feature-extraction
+tags:
+- code
+- code-search
+- code-retrieval
+- semantic-search
+- neural-retrieval
+- mediawiki
+- wikimedia
+- faiss
+- embeddings
+- bm25
+- swhid
+- software-heritage
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*.parquet
+---
+
+# MediaWiki Code2Code Search — Dataset
+
+Pre-computed retrieval artifacts for **MediaWiki Code2Code Search**, a neural system for the
+semantic discovery of open-source software entities (functions, types, templates) across the
+MediaWiki / Wikimedia ecosystem.
+
+This Hugging Face dataset is a **complementary mirror** of the pre-computed artifacts archived on
+Zenodo. **The canonical, citable record is the Zenodo deposit** — please cite that DOI:
+
+> **Zenodo DOI (canonical): [10.5281/zenodo.20586256](https://doi.org/10.5281/zenodo.20586256)**
+
+The Hugging Face copy exists to make the corpus **browsable in the dataset Viewer** and easy to
+pull with the `datasets` / `huggingface_hub` libraries. It does not supersede Zenodo.
+
+- **Code / system:** <https://github.com/ftosoni/mediawiki-code2code-search>
+- **Paper:** *MediaWiki Code2Code Search: Neural Retrieval for the Semantic Discovery of
+  Open-Source Software Entities* — Francesco Tosoni, Sant'Anna School of Advanced Studies, Pisa.
+  Peer-reviewed version **forthcoming in *SoftwareX*** (ms. SOFTX-D-26-00628). See
+  [Citation](#citation).
+
+---
+
+## Contents
+
+| File | Size | Format | Description |
+|---|---|---|---|
+| `data/train-*.parquet` (9 shards) | ~172 MiB | Parquet (zstd) | The full `snippets` table, exposed for the **dataset Viewer** and `load_dataset`. Same 1,289,452 rows as `snippets.db`. |
+| `snippets.db` | 1.74 GiB | SQLite | Serving metadata + code for every entity (single `snippets` table). |
+| `embeddings.npy` | 4.92 GiB | NumPy `float32` | Dense embeddings, shape `(1289452, 1024)`, **L2-normalised**, from `Qwen/Qwen3-Embedding-0.6B`. Row *i* aligns with `snippets.db` row `id = i`. |
+| `mediawiki.index` | 168.6 MiB | FAISS | `IndexIVFPQ` (L2) with an `IndexFlatL2` coarse quantizer, 128 sub-quantizers × 8 bits, dim 1024. Built over the embeddings above. |
+| `bm25_index.pkl` | 423.6 MiB | Pickle | BM25 lexical baseline built over the `code` field (identifier tokeniser; keywords and tokens shorter than three characters dropped). |
+
+> **Note on `.npy` / `.index` / `.pkl`:** these binary artifacts do not render in the Viewer by
+> design; the Parquet shards provide the browsable view of the same underlying rows.
+
+### Data fields (`snippets` table / Parquet)
+
+| Column | Type | Description |
+|---|---|---|
+| `id` | int64 | Row id; aligns with the corresponding row of `embeddings.npy`. |
+| `original_id` | string | Upstream extraction id (content hash). |
+| `swhid` | string | **[SWHID](https://www.swhid.org/)** of the source content, with `origin=` and `lines=` qualifiers — resolvable on [Software Heritage](https://archive.softwareheritage.org/) for exact provenance and upstream licensing. |
+| `sha1` | string | SHA-1 of the source blob. |
+| `repo_name` | string | Upstream repository name. |
+| `repo_group` | string | Repository group / namespace. |
+| `filepath` | string | Path of the source file within the repository. |
+| `name` | string | Entity name / signature (e.g. `check_dumps_log_path(path)`). |
+| `type` | string | One of `function`, `type`, `template`. |
+| `code` | string | Source snippet text for the entity (see [Licensing](#licensing-important)). |
+
+### Corpus statistics
+
+- **1,289,452** structural entities:
+  - `function`: 1,050,748
+  - `type`: 237,653
+  - `template`: 1,051
+- **2,242** active repositories (distinct `(repo_group, repo_name)` pairs) across the MediaWiki /
+  Wikimedia ecosystem.
+- **12** programming languages extracted via language-specific structural parsing.
+- Embedding model: **`Qwen/Qwen3-Embedding-0.6B`** (1024-dim). Retrieval is nearest-neighbour by
+  **Euclidean (L2) distance** over L2-normalised vectors.
+
+---
+
+## Usage
+
+Browse the corpus in the **Viewer** above, or load it programmatically.
+
+**Tabular rows (Parquet) with `datasets`:**
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("ftosoni/mediawiki-code2code-search", split="train")
+print(ds)
+print(ds[0]["name"], ds[0]["type"])
+print(ds[0]["swhid"])
+```
+
+**Raw serving artifacts with `huggingface_hub`:**
+
+```python
+from huggingface_hub import hf_hub_download
+
+repo = "ftosoni/mediawiki-code2code-search"
+db    = hf_hub_download(repo, "snippets.db",      repo_type="dataset")
+emb   = hf_hub_download(repo, "embeddings.npy",   repo_type="dataset")
+index = hf_hub_download(repo, "mediawiki.index",  repo_type="dataset")
+bm25  = hf_hub_download(repo, "bm25_index.pkl",   repo_type="dataset")
+
+import numpy as np, faiss
+X = np.load(emb, mmap_mode="r")        # (1289452, 1024) float32, L2-normalised
+faiss_index = faiss.read_index(index)  # IndexIVFPQ (L2)
+```
+
+`embeddings.npy` row `i` corresponds to `snippets.db` row `id = i` and to FAISS vector `i`.
+
+---
+
+## Licensing (important)
+
+This dataset combines two distinct layers, and they carry **different licenses**:
+
+1. **Tooling / packaging** (schema, indexes, embeddings, this card): **Apache-2.0**, matching the
+   canonical [Zenodo record](https://doi.org/10.5281/zenodo.20586256).
+2. **The `code` snippets** in `snippets.db` / the Parquet shards are **derived from upstream
+   MediaWiki / Wikimedia repositories**, each under **its own free/open-source license**
+   (predominantly **GPL-2.0-or-later**, with some MIT / BSD / Apache-2.0 and others). These
+   upstream licenses govern the snippet text; redistribution here relies on their permission to
+   redistribute.
+
+There is **no per-row `license` column**. Instead, **every entity carries an `swhid`** with an
+`origin=` qualifier, so the exact upstream repository — and therefore its authoritative license and
+copyright — can be resolved on [Software Heritage](https://archive.softwareheritage.org/) and at
+the origin repository. Snippets are fragments and may not carry their file's original license
+header; consult the origin before reuse.
+
+See [`LICENSE.md`](LICENSE.md) for the full statement.
+
+---
+
+## Citation
+
+Please cite the **canonical Zenodo dataset**:
+
+```bibtex
+@dataset{tosoni2026mediawiki_c2c_data,
+  author    = {Tosoni, Francesco},
+  title     = {Pre-computed {FAISS} Vector Index and {SQLite} Metadata Database
+               for {MediaWiki} {Code2Code} Search},
+  year      = {2026},
+  publisher = {Zenodo},
+  doi       = {10.5281/zenodo.20586256},
+  url       = {https://doi.org/10.5281/zenodo.20586256}
+}
+```
+
+The accompanying paper is **forthcoming in *SoftwareX*** (this entry will be updated with the
+published DOI once available):
+
+```bibtex
+@article{tosoni2026mediawiki,
+  author  = {Tosoni, Francesco},
+  title   = {{MediaWiki} {Code2Code} Search: Neural Retrieval for the
+             Semantic Discovery of Open-Source Software Entities},
+  journal = {SoftwareX},
+  year    = {2026},
+  note    = {To appear; under review (ms. SOFTX-D-26-00628)}
+}
+```
+
+---
+
+## Acknowledgements
+
+Corpus derived from the MediaWiki / Wikimedia software ecosystem. Provenance is tracked with
+[SWHID](https://www.swhid.org/) identifiers resolvable on
+[Software Heritage](https://archive.softwareheritage.org/). Embeddings computed with
+[`Qwen/Qwen3-Embedding-0.6B`](https://huggingface.co/Qwen/Qwen3-Embedding-0.6B); indexing with
+[FAISS](https://github.com/facebookresearch/faiss).

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