Datasets:

tharustack
/

open-math-dataset

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

{
  "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 🌍.