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How to Package your Data

Reducing frictions one simple table at a time

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The Data Package is a format for frictionless, standards-based exchange of metadata. It enables everyone to publish open data in a reliable way: like the TTN-Twist Data Package that you can see published on DataHub above. From here, it can be easily read into various tools and programming languages - for example, in JavaScript with frictionlessdata-js) for visualization & analysis.

📖 For more guidance visit the Standards Library, which covers Field Descriptors (string, integer, date...) and all other topics. You may also find the Field Guide useful for an overview.

Creating Data Packages

A good starting point is the Data Package Template - click Use this template to make a fresh data package in your GitHub account.

You can also use the Data Package Creator to easily edit your datapackage.json file (using the Upload button on the top left) or to generate one from a CSV file that you upload (click the "Load" button on the upper right part of the page):

When a Data Package is linked anywhere on this site (dribdat), it looks like this:

Connecting to visualization

You can use your Data Package to create a web page or online report with the Livemark project, or add Vega views if you are uploading to DataHub. See Livemark for Data Journalism for instructions.

Data Packages are a great starting point to work with your project in Python, Julia, JavaScript, or any of the other supported languages. Here are, for example, some instructions for loading into an Observable notebook:

Observable
Analyse

Data science notebooks "light" using JavaScript

Validation

Once you have a Data Package, you can create an automated report card using the Frictionless Repository which updates every time there is a change in the data. The easiest way to do this is through the GitHub Marketplace, as shown here or when you create a blank workflow in your Actions tab:

Here is an example Action with the validation step: loleg/rain-of-drums


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