Datasets:

dsfsi
/

za-mafoko-statssa

license: other
license_name: noodl
license_link: https://licensingafricandatasets.com/nwulite-obodo-license
language:
  - en
  - af
  - ts
  - tn
  - ve
  - nr
  - nso
  - ss
  - st
  - zu
  - xh
pretty_name: za-mavito-statssa
size_categories:
  - 1K<n<10K
tags:
  - terminology

# Statistics South Africa Multilingual Statistical Terminology Dataset

Dataset Description

The Multilingual Statistical Terminology 2013 dataset is the result of an initiative by Statistics South Africa (Stats SA) to promote linguistic diversity and increase access to statistical information across all South African official languages. The dataset includes multilingual equivalents for statistical terms developed in collaboration with language specialists, academic institutions, and government bodies.

This dataset aims to bridge linguistic barriers, ensuring that all South Africans, regardless of their first language, can understand key issues such as the economy, education, and living conditions. Supported by the Use of Official Languages Act, 2012, and the National Language Policy Framework, this project reflects Stats SA's commitment to inclusivity and accessibility. By making statistical information available in all 11 official languages, the dataset fosters educational engagement and pride in native languages, particularly through dissemination channels such as the Mbalo Brief for high school learners.

This initiative underscores Stats SA's dedication to ensuring every South African can access and understand statistical data, enhancing democratic participation and informed decision-making.

The machine-readable version of this dataset was processed as part of the Mafoko: South African Terminology, Lexicon, and Glossary Project by the Data Science for Social Impact (DSFSI) group at the University of Pretoria. This work supports the development of multilingual language technologies, including machine translation and term extraction.

Dataset Structure

The dataset consists of a single JSONL file containing comprehensive statistical terminology:

File Overview

File	Domain	Description
`statssa_multilingual_statistical_terminology.jsonl`	Statistics	Statistical terms and concepts across all official SA languages

Data Format

Each entry in the JSONL file contains statistical terms translated across all South African official languages:

{
  "id": "unique_identifier",
  "eng": "English statistical term",
  "afr": "Afrikaans translation",
  "xho": "isiXhosa translation",
  "ssw": "siSwati translation",
  "nbl": "isiNdebele translation",
  "tsn": "Setswana translation",
  "nso": "Sepedi translation",
  "sot": "Sesotho translation",
  "ven": "Tshivenda translation",
  "tso": "Xitsonga translation",
  "zul": "isiZulu translation",
  "eng_pos_or_descriptor": "Part of speech or descriptor in English",
  "eng_pos_or_descriptor_info": "Additional grammatical information",
  "[lang]_pos_or_descriptor": "Part of speech for each language",
  "[lang]_pos_or_descriptor_info": "Additional grammatical information for each language"
}

Languages Covered

The dataset includes statistical terminology in all 11 official South African languages:

English (eng)
Afrikaans (afr)
isiXhosa (xho)
isiZulu (zul)
siSwati (ssw)
isiNdebele (nbl)
Setswana (tsn)
Sepedi/Northern Sotho (nso)
Sesotho (sot)
Tshivenda (ven)
Xitsonga (tso)

Statistical Domains Covered

The terminology encompasses key statistical concepts across various domains:

Economic Statistics: GDP, inflation, employment, trade
Demographic Statistics: Population, migration, vital statistics
Social Statistics: Education, health, living conditions
Survey Methodology: Sampling, data collection, statistical methods
Data Analysis: Statistical measures, indicators, indices
Census Terminology: Enumeration, household concepts, geographic units

Usage

Loading the Dataset

import json

def load_statssa_terminology(file_path='statssa_multilingual_statistical_terminology.jsonl'):
    """Load Stats SA statistical terminology from JSONL file"""
    terms = []
    with open(file_path, 'r', encoding='utf-8') as f:
        for line in f:
            terms.append(json.loads(line))
    return terms

# Example usage
statistical_terms = load_statssa_terminology()
print(f"Loaded {len(statistical_terms)} statistical terms")

Example Applications

Statistical Education: Create multilingual educational materials for statistics courses
Government Communication: Develop accessible statistical reports in local languages
Translation Services: Build statistical translation tools and glossaries
Research Tools: Support multilingual statistical research and analysis
Public Understanding: Enhance citizen understanding of statistical concepts
Language Technology: Train multilingual NLP models for statistical domains
Data Literacy: Develop multilingual data literacy programs

Data Quality and Provenance

The terminology was developed by Statistics South Africa in 2013 through:

Collaboration with language specialists
Partnership with academic institutions
Consultation with government bodies
Adherence to official language policies

The machine-readable version was processed and curated by the Data Science for Social Impact (DSFSI) group, ensuring technical accuracy and accessibility for computational applications.

Legal and Policy Framework

This dataset is supported by:

Use of Official Languages Act, 2012: Promoting multilingual access to government information
National Language Policy Framework: Advancing linguistic diversity and inclusion
Stats SA Mandate: Ensuring statistical information accessibility for all South Africans

Citation

Paper Citation

[Placeholder for associated research paper - To be updated]

@article{marivate2025mafokostructuringbuildingopen,
      title={Mafoko: Structuring and Building Open Multilingual Terminologies for South African NLP}, 
      author={Vukosi Marivate and Isheanesu Dzingirai and Fiskani Banda and Richard Lastrucci and Thapelo Sindane and Keabetswe Madumo and Kayode Olaleye and Abiodun Modupe and Unarine Netshifhefhe and Herkulaas Combrink and Mohlatlego Nakeng and Matome Ledwaba},
      year={2025},
      eprint={2508.03529},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2508.03529}, 
}

Authors and Contributors

Original Development

Statistics South Africa (Stats SA) - Primary author and terminology developer
Language Specialists - Linguistic expertise and translation quality
Academic Institutions - Research support and validation
Government Bodies - Policy alignment and stakeholder input

Dataset Processing and Curation

Data Science for Social Impact (DSFSI) - University of Pretoria
Mafoko Project Team - Machine-readable format processing
[Additional contributors to be listed]

[Placeholder for comprehensive list of individual contributors - To be updated]

Project Information

Original Publisher: Statistics South Africa
Processing Institution: Data Science for Social Impact (DSFSI), University of Pretoria
Project Website: http://www.dsfsi.co.za/za-mafoko/
Parent Project: Mafoko: South African Terminology, Lexicon, and Glossary Project
Publication Year: 2013 (Original), 2024 (Machine-readable version)

Impact and Applications

Educational Impact

Mbalo Brief: Supporting high school learners with multilingual statistical content
Data Literacy: Enhancing statistical understanding across language communities
Academic Research: Enabling multilingual statistical research

Social Impact

Democratic Participation: Improving citizen access to statistical information
Informed Decision-Making: Supporting evidence-based discussions in all languages
Language Preservation: Maintaining and developing statistical vocabulary in indigenous languages

Technical Impact

Machine Translation: Training data for statistical domain translation
Term Extraction: Supporting automated terminology extraction systems
Language Technologies: Enabling multilingual statistical NLP applications

License

This dataset is licensed under Nwulite Obodo Open Data License - Version 1.0

Contact

For questions regarding this dataset:

Original Content: Statistics South Africa
Technical Processing: Data Science for Social Impact (DSFSI), University of Pretoria
Project Information: Visit http://www.dsfsi.co.za/za-mafoko/

Acknowledgments

We acknowledge Statistics South Africa for their pioneering work in making statistical information accessible across all South African languages. Special recognition goes to the language specialists, academic institutions, and government bodies who contributed to the original terminology development. We also thank the Data Science for Social Impact (DSFSI) group at the University of Pretoria for processing this valuable resource into a machine-readable format as part of the Mafoko project.

This dataset represents a significant milestone in multilingual statistical communication, supporting South Africa's linguistic diversity while enhancing access to crucial statistical information for all citizens.

This dataset exemplifies the intersection of statistical literacy, language policy, and technological innovation in service of inclusive access to information in multilingual South Africa.