open-math-dataset / README.md
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---
language:
- en
- si
license: cc-by-4.0
task_categories:
- text-generation
- question-answering
pretty_name: Open Math Dataset
tags:
- mathematics
- math
- education
- reasoning
- problem-solving
- multilingual
- sinhala
- sri-lanka
- algebra
- geometry
- calculus
- arithmetic
- word-problems
- step-by-step
- llm-training
- synthetic
size_categories:
- 1K<n<10K
---
## Dataset Description
**Open Math Dataset** is an open mathematics corpus designed for **mathematical AI, reasoning, education, and research**.
The project is being developed from **Sri Lanka** with the goal of creating an internationally useful mathematics dataset for developers, researchers, educators, and AI systems.
### Mathematics Corpus
The dataset is designed to contain structured mathematical problems and solutions across different mathematical domains and education levels.
**Planned content includes:**
- Arithmetic
- Algebra
- Geometry
- Trigonometry
- Calculus
- Statistics
- Probability
- Number theory
- Linear algebra
- Discrete mathematics
- Mathematical reasoning
- Word problems
- Step-by-step solutions
- Mathematical explanations
- Error correction
- Multiple solution methods
- Mathematical proofs
The dataset supports both **general mathematics** and **curriculum-specific mathematics**.
### Languages
Current languages:
- **English** (`en`)
- **Sinhala** (`si`)
Sinhala mathematics is an important initial focus because high-quality Sinhala mathematical training data is limited.
However, the project is **not limited to Sri Lankan mathematics**. The dataset is designed for international expansion and may include additional languages, countries, and curricula in future releases.
### Sri Lankan Mathematics
Sri Lankan mathematical content is one of the initial areas of development. This may include:
- Sri Lankan school mathematics
- Sinhala mathematical terminology
- O/L mathematics
- A/L mathematics
- Sri Lankan curriculum-related problems
- Localized mathematical explanations
Sri Lankan content is treated as part of the wider Open Math Dataset rather than the entire scope of the project.
## Dataset Structure
### Data Fields
The dataset is intended to use structured records containing information such as:
| Field | Description |
|--------------------|--------------------------------------------------|
| `id` | Unique identifier |
| `problem` | The mathematical problem statement |
| `solution` | Step-by-step solution |
| `answer` | Final answer |
| `language` | Language code (`en`, `si`, etc.) |
| `topic` | Mathematical topic (e.g. `algebra.linear_equations`) |
| `difficulty` | Difficulty score (e.g. 0.0–1.0) |
| `education_level` | Education level (e.g. `middle_school`) |
| `curriculum` | Curriculum identifier (optional) |
| `country` | Country code (optional) |
| `source_type` | Provenance type |
### Example
```json
{
"id": "omd_000001",
"language": "en",
"problem": "Solve 2x + 5 = 15.",
"solution": "2x + 5 = 15\n2x = 10\nx = 5",
"answer": "5",
"topic": "algebra.linear_equations",
"difficulty": 0.2,
"education_level": "middle_school"
}
```
## Data Quality
Mathematical correctness is a major priority.
The project aims to prioritize:
- Correct answers
- Correct mathematical reasoning
- Clear explanations
- Consistent formatting
- Deduplication
- Accurate metadata
- Diverse difficulty levels
- Diverse mathematical domains
- Transparent data provenance
Automatically generated mathematical content should be treated as candidate data and verified before being considered high-quality training data.
## Data Pipeline
The planned data preparation process is:
```
Collection
↓
Cleaning
↓
Normalization
↓
Generation
↓
Mathematical Verification
↓
Deduplication
↓
Quality Filtering
↓
Metadata
↓
Dataset Release
```
## Intended Uses
The dataset may be useful for:
- Mathematical AI
- LLM training
- LLM fine-tuning
- Mathematical reasoning research
- Educational AI
- AI tutoring systems
- Question generation
- Mathematical evaluation
- Multilingual AI
- Curriculum-aware AI
- Mathematical search systems
## Data Provenance
The dataset may contain data from multiple sources and generation methods.
Possible source types include:
- `human_verified`
- `official_source`
- `public_domain`
- `synthetic_verified`
- `community_contributed`
- `translated_verified`
Source and licensing information should be preserved whenever possible.
Only data that can legally be redistributed should be included in public releases.
## Dataset Versions
The dataset will use versioned releases.
| Version | Description |
|---------|---------------------------------|
| `v0.1` | Initial release |
| `v0.2` | Expanded mathematical domains |
| `v0.5` | Multilingual expansion |
| `v1.0` | Stable major release |
Dataset statistics and coverage information will be updated with future releases.
## Project Status
**Active Development**
Open Math Dataset is an ongoing project.
The initial focus is building a strong foundation of high-quality mathematical data before expanding into larger international and multilingual coverage.
## Long-term Goal
The goal is to create an open mathematics dataset that developers and researchers around the world can use.
- From basic arithmetic to advanced mathematics.
- From simple question-and-answer pairs to structured mathematical reasoning.
- From Sinhala and English to additional languages in the future.
**Mathematics is universal. The data should be too.**
## Maintainer
Created and maintained by **Tharustack**.
Built from Sri Lanka 🇱🇰 for the world 🌍.