---
pretty_name: Tesis UChile
license: unknown
---

# Tesis UChile

`erickfmm/Tesis_UChile` is a collection of thesis metadata from the University of Chile repository (`repositorio.uchile.cl`). The data was obtained by scraping public pages around August 2024 (approximately), and then normalized into a row-based CSV plus grouped JSON exports.

## What is in this dataset?

The main file is `train.csv`. Each row represents one metadata value associated with a source record. Rows are linked by the `origen` field, which acts as the record identifier or source URL.

The repository also includes JSON and JSONL exports generated from `train.csv`, where all rows that share the same `origen` are grouped into a single document.

This dataset mainly contains bibliographic and repository metadata, for example:

- thesis title
- author
- advisor
- publisher / faculty / school
- issue or accession dates
- language
- subjects
- rights / access fields
- repository links and file links

Most keys follow Dublin Core naming conventions such as `dc.title`, `dc.subject`, `dc.identifier.uri`, and `dcterms.accessRights`.

## Files

| File | Description | Link |
| --- | --- | --- |
| `train.csv` | Row-level metadata table used as the base dataset. On Hugging Face, this is exposed as the `train` split. | [Download](https://huggingface.co/datasets/erickfmm/Tesis_UChile/resolve/main/train.csv) |
| `tesis_uchile_pretty.json` | Grouped JSON array, pretty-printed for easier inspection. | [Download](https://huggingface.co/datasets/erickfmm/Tesis_UChile/resolve/main/tesis_uchile_pretty.json) |
| `tesis_uchile_min.json` | Grouped JSON array, compact version of the same data. | [Download](https://huggingface.co/datasets/erickfmm/Tesis_UChile/resolve/main/tesis_uchile_min.json) |
| `tesis.uchile.jsonl` | Grouped JSON Lines export, one record per line, convenient for streaming and incremental processing. | [Download](https://huggingface.co/datasets/erickfmm/Tesis_UChile/resolve/main/tesis.uchile.jsonl) |

## CSV schema

The processing script expects at least the following columns in `train.csv`:

| Column | Meaning |
| --- | --- |
| `origen` | Source identifier for a thesis record, typically the repository URL used to group rows. |
| `DC` | Metadata field name, usually a Dublin Core-style key such as `dc.title` or `dc.subject`. |
| `nombre` | Original scraped field name. A special case maps `filelink` to `extra.file.link` when `DC` is missing. |
| `value` | Metadata value. Empty values are skipped when building the JSON exports. |
| `lang` | Optional language tag for the value, for example `es_CL`. |

## JSON / JSONL structure

The JSON exports are built by grouping all rows with the same `origen`.

Rules used in the export:

- each grouped record gets `_id = origen`
- scalar values are stored as `{"value": "..."}`
- when a language is available, values become `{"value": "...", "lang": "..."}`
- repeated metadata fields become lists
- if `DC` is missing and `nombre == "filelink"`, the field is stored as `extra.file.link`

Example grouped record:

```json
{
  "_id": "https://repositorio.uchile.cl/handle/2250/100054",
  "dc.contributor.advisor": {
    "value": "Cárdenas, Juan",
    "lang": "es_CL"
  },
  "dc.contributor.author": {
    "value": "Gallego, Francisco",
    "lang": "es_CL"
  },
  "dc.contributor.editor": [
    {
      "value": "Facultad de Arquitectura y Urbanismo",
      "lang": "es_CL"
    },
    {
      "value": "Escuela de Arquitectura",
      "lang": "es_CL"
    }
  ],
  "dc.identifier.uri": {
    "value": "https://repositorio.uchile.cl/handle/2250/100054"
  },
  "extra.file.link": {
    "value": "..."
  }
}
```

## Example code

### Load the CSV with pandas

```python
import pandas as pd

df = pd.read_csv(
    "hf://datasets/erickfmm/Tesis_UChile/train.csv",
    encoding="utf-8",
)

print(df.head())
print(df.columns.tolist())
```

### Load the dataset with `datasets`

```python
from datasets import load_dataset

dataset = load_dataset("erickfmm/Tesis_UChile")
print(dataset)
print(dataset["train"][0])
```

### Stream the JSONL export

```python
import json
import urllib.request

url = "https://huggingface.co/datasets/erickfmm/Tesis_UChile/resolve/main/tesis.uchile.jsonl"

with urllib.request.urlopen(url) as response:
    for i, line in enumerate(response):
        record = json.loads(line)
        title = record.get("dc.title", {})
        print(record["_id"], title)
        if i == 2:
            break
```

### Read the compact JSON export locally

```python
import json

with open("tesis_uchile_min.json", "r", encoding="utf-8") as fh:
    data = json.load(fh)

print(len(data))
print(data[0]["_id"])
```

## Source and collection notes

- Source website: public pages from the University of Chile repository (`repositorio.uchile.cl`)
- Collection method: scraping
- Collection period: around August 2024 (approximate)
- Contents: public metadata records and derived grouped exports

## License

No license is provided for this dataset in this repository, or the license is unknown.

If you plan to reuse the data, especially beyond research or indexing purposes, please verify the terms of use of the original source and the rights associated with individual records.

## Limitations

- scraped metadata can contain inconsistencies, missing fields, duplicates, or formatting issues
- language tags are not guaranteed to exist for every value
- the JSON exports are derived from `train.csv`, so updates to the CSV should be regenerated in the exported formats