Guide · Open source
How to use awesome-public-datasets to find open data
Updated · written with AI from the project's own documentation and checked against our catalogue data
awesome-public-datasets is a topic-centric list of high-quality open datasets maintained as a markdown file on GitHub. It is useful if you need data for analysis, learning or a prototype and want a starting point grouped by subject. By the end of this guide you will know how to browse the list, find a dataset in a topic you care about, clone the repository if you want a local copy, and check whether a linked source still works.
awesome-public-datasetsawesomedata/awesome-public-datasets · ★ 79.9k · MIT Install options & downloads Quick start
- 1Open the repository. Go to the awesomedata/awesome-public-datasets repository on GitHub in your browser. No install is needed.
- 2Pick a topic. Scan the subject groupings, such as government, science or finance, and choose the section closest to your question.
- 3Follow a link to the source. Open an entry and go to the publisher's page, because the data is hosted there and not in the list.
- 4Verify before use. Check that the link still works, read the source's terms, and download a small sample to confirm the format.
What awesome-public-datasets is and is not
The list is a set of links to public datasets, grouped by subject such as government, science and finance. It does not host the data itself. Each entry points to the place where the dataset is published, so the actual files come from the original publisher.
Because it is a static list, it is a starting point rather than a database. It has no search API and no cleaned, ready-to-use downloads.
- Good for: finding which public sources exist in a field
- Not good for: getting one dataset already downloaded and cleaned
- Not good for: data that is guaranteed to be current, since linked sources may change or disappear
Open the list and browse it by topic
No installation is required. The project is read online, and the README lists no prerequisites. Open the repository page in your browser and read the list.
Entries are organised by subject. Scan the section headings for the topic you need, then open the entries that look relevant and follow their links to the publisher.
- Start with the subject closest to your question, such as government, science or finance
- Open each candidate link and read the publisher's own description before downloading
- Note the publisher and the date you checked, since links can change
Clone the repository locally (optional)
If you want a copy of the list on your own machine, clone the repository with git. This step is optional; reading the list online works just as well.
A local copy lets you search the markdown file with your own tools, but the links it contains still point to external sources that you need an internet connection to reach.
git clone https://github.com/awesomedata/awesome-public-datasetsCheck that a linked source still works
Linked sources may move, change format or disappear. Before you build anything on a dataset, open its link and confirm that the data is still published there and matches what the list describes.
The list's MIT licence covers the list itself. The datasets it links to are published by their owners, so read the terms on each source page before you reuse the data.
- Confirm the link opens and the publisher is the expected one
- Read the licence or terms on the source page
- Download a small sample first to check the format
Compare with other dataset directories
Other places people look for public data include Kaggle Datasets, Data.gov and Our World in Data. These are different kinds of resources from a static link list, so the right choice depends on what you need.
Use awesome-public-datasets when you want a broad, topic-grouped map of sources. Consider the others when you need a searchable catalogue or a specific publisher's data.
What people use it for
- A data analyst looking for a starting point on a topic they have not worked with before
- A student who needs sample datasets for a class or personal project
- A developer who wants test data to prototype an application
- A researcher scanning which public sources exist in a field
Frequently asked questions
Do I need to install awesome-public-datasets?
No. The list is read online and the README lists no prerequisites. Cloning the repository with git is optional if you want a local copy of the markdown file.
Does awesome-public-datasets host the data files?
No. It is a list of links, and each entry points to where the dataset is published. You download the data from the original publisher's site.
What licence is awesome-public-datasets under?
The repository is released under the MIT licence. The datasets it links to are published by their owners, so check the terms on each source before reuse.
Is the data on awesome-public-datasets always up to date?
Not guaranteed. Linked sources may change or disappear, so confirm that a link still works and that the data is current before you rely on it.
What are the alternatives to awesome-public-datasets?
Comparable projects named in the analysis are Kaggle Datasets, Data.gov and Our World in Data. Pick one based on whether you need a searchable catalogue, official government data or a curated set of charts and datasets.
Can I use awesome-public-datasets as an API or searchable database?
No. It is a static markdown list with no searchable API, so you browse it by topic or search the file yourself.
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Our verdict
Use awesome-public-datasets if you want a topic-grouped starting point for finding public data for analysis, learning or prototyping. Pick something else if you need a ready-to-use cleaned dataset, guaranteed current data, or a searchable API.
Install options & downloads