---
annotations_creators:
- no-annotation
language_creators:
- expert-generated
languages:
- ca
- es
licenses:
- cc0-1-0
multilinguality:
- translation
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- conditional-text-generation
task_ids:
- machine-translation
paperswithcode_id: null
---

# Dataset Card for OPUS DOGC

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** http://opus.nlpl.eu/DOGC.php
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**

### Dataset Summary

OPUS DOGC is a collection of documents from the Official Journal of the Government of Catalonia, in Catalan and Spanish languages, provided by Antoni Oliver Gonzalez from the Universitat Oberta de Catalunya.

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

Dataset is multilingual with parallel text in:
- Catalan
- Spanish

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

A data instance contains the following fields:
- `ca`: the Catalan text
- `es`: the aligned Spanish text

### Data Splits

[More Information Needed]

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

Dataset is in the Public Domain under [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/).

### Citation Information

```
@inproceedings{tiedemann-2012-parallel,
    title = "Parallel Data, Tools and Interfaces in {OPUS}",
    author = {Tiedemann, J{\"o}rg},
    booktitle = "Proceedings of the Eighth International Conference on Language Resources and Evaluation ({LREC}'12)",
    month = may,
    year = "2012",
    address = "Istanbul, Turkey",
    publisher = "European Language Resources Association (ELRA)",
    url = "http://www.lrec-conf.org/proceedings/lrec2012/pdf/463_Paper.pdf",
    pages = "2214--2218",
    abstract = "This paper presents the current status of OPUS, a growing language resource of parallel corpora and related tools. The focus in OPUS is to provide freely available data sets in various formats together with basic annotation to be useful for applications in computational linguistics, translation studies and cross-linguistic corpus studies. In this paper, we report about new data sets and their features, additional annotation tools and models provided from the website and essential interfaces and on-line services included in the project.",
}
```

### Contributions

Thanks to [@albertvillanova](https://github.com/albertvillanova) for adding this dataset.