OpenRefine is a desktop application for exploring, cleaning and transforming datasets. It is particularly useful when information contains inconsistent spelling, duplicated values, mixed formats or other problems that make further analysis difficult.
The application presents tabular data in a spreadsheet-like interface, but its workflow is built around operations that can be applied to many records at once. Users can filter and facet datasets, examine distributions and apply transformations to selected groups of rows.
OpenRefine is also useful for reconciling local records against external reference sources. This allows data to be connected to established identifiers and helps resolve inconsistent names or descriptions.
Projects retain a history of transformations, making it possible to inspect, undo and replay operations. The application runs locally, with its interface accessed through a web browser. This arrangement allows users to work interactively with datasets without uploading them to a hosted service.
This is free and open source software.
Key Features
- Import tabular and structured data from CSV, TSV, JSON, XML and other formats.
- Explore datasets through text, numeric, date and custom facets.
- Filter records to focus transformations on selected subsets.
- Detect similar text values using clustering algorithms.
- Merge inconsistent categories, names and other values.
- Transform fields using General Refine Expression Language (GREL).
- Split, join, normalize and reorganize columns and records.
- Reconcile local data against external reference services.
- Extend records using information from external data sources.
- Maintain an undo and redo history of changes.
- Extract and reuse operation histories for repeatable cleaning tasks.
- Export cleaned data into supported tabular and structured formats.
- Cross-platform support – runs on Linux, macOS, and Windows.
Website: github.com/OpenRefine/OpenRefine
Support:
Developer: OpenRefine community
License: BSD 3-Clause ‘New’ or ‘Revised’ License

OpenRefine is written in Java. Learn Java with our recommended free books and free tutorials.
Related Software
| Python Data Validation | |
|---|---|
| Pydantic | Data validation using Python type hints |
| pandera | Framework for precision data testing |
| jsonschema | Implementation of JSON Schema for Python |
| Cerberus | Lightweight and extensible data validation library |
| schema | Library for validating Python data structures |
| GX | Validating, documenting, and profiling data |
| marshmallow | ORM/ODM/framework-agnostic library |
| Voluptuous | Python data validation library |
| Schematics | Combine types into structures, validate , and transform the shapes of data |
| Colander | Serialization / deserialization / validation library |
| Valideer | Lightweight data validation and adaptation Python library |
| OpenRefine | Desktop program for data cleanup and transformation |
| Soda Core | Data quality and data contract verification engine |
| OpenMetadata | Unified metadata platform |
| Elementary OSS | dbt-native data observability command-line tool |
Read our verdict in the software roundup.
LinuxLinks helps you discover the best free and open source software for Linux. Explore our extensive collection of recommended applications, including alternatives to popular proprietary software.We also publish software reviews, Linux tutorials, hardware reviews, free programming books and articles covering the wider open source community. Browse our Linux resources to discover more. Know a useful free and open source Linux application we haven't covered? Suggest a program for inclusion. Has your software been featured on LinuxLinks? Display one of our Featured on LinuxLinks badges on your website or GitHub README. |


Please read our Comment Policy before commenting.