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Learn about the Dimensions Analytics API via code examples and Jupyter notebooks
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Getting Started

This GitHub repository contains code samples and reusable Jupyter notebooks for scholarly data analytics using the Dimensions API.

Binder Open In Colab

A companion website including HTML versions of these tutorials is also available:

License: CC BY-NC-SA 4.0

What is Dimensions?

Digital Science's Dimensions is a dynamic, easy to use, linked-research data platform that re-imagines the way research can be discovered, accessed and analyzed. Within Dimensions, users can explore the connections between grants, publications, clinical trials, patents and policy documents.

For more information, see

For a detailed breakdown of the Dimensions API language, see the API documentation

What are Jupyter Notebooks?

The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.

For more information, see

Running the examples

If you are already familiar with Python and Jupyter, then you probably know what to do already. Download this repository and run it locally. Feel free to modify and adapt these examples so to match your project needs.

You can also run these examples online in your browser, thanks to Binder.

Using Binder is a free service that transforms a github repository into a Jupyter server hosting the repository's contents.

With Binder, you can run most of the Jupyter notebooks directly from your web browser without installing anything. Just click on the launch binder button below. A temporary Jupyter Notebook server with all dependencies will be automatically launched in the cloud. It is not persistent: all your changes will be lost after some time.


Using Google Colab

Google Colaboratory is a free Jupyter notebook environment that requires no setup and runs entirely in the cloud.

With Colaboratory you can write and execute code, save and share your analyses, and access powerful computing resources, all for free from your browser.

Open In Colab

Comments, bug reports

This project lives on Github. You can file issues or ask questions there. Suggestions, pull requests and improvements welcome!

See also

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