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dimensions-api-lab

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Research data analytics tutorials using the Dimensions Analytics API

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# Getting Started

This GitHub repository contains code samples and reusable **Jupyter notebooks** for scholarly data analytics using the [Dimensions API](https://www.dimensions.ai/dimensions-apis/).

A companion website including [browsable HTML versions of these tutorials](https://digital-science.github.io/dimensions-api-lab/) is also available.

Note: please use the notebooks in the `cookbook` folder for up-to-date examples and templates (see below for more details).

[![License: CC BY-NC-SA 4.0](https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg)](https://creativecommons.org/licenses/by-nc-sa/4.0/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/digital-science/dimensions-api-lab/master) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/digital-science/dimensions-api-lab/)

## Background

If you've never heard of Dimensions.ai or Jupyter notebooks, then this section if for you.

### 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 https://www.dimensions.ai/

For a detailed breakdown of the Dimensions API language, see the [API documentation](https://docs.dimensions.ai/dsl)

### 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 https://jupyter.org/

## 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.

There are two main folders:

* The [cookbooks](https://github.com/digital-science/dimensions-api-lab/tree/master/cookbooks) folder contains the **latest version** of notebooks providing reusable, simple solutions to common scholarly analytics problems. The notebooks in this folder are regularly tested and kept up to date. If any of these do not work, please [open an issue](https://github.com/digital-science/dimensions-api-lab/issues/new) to let us know. 
* The [archive](https://github.com/digital-science/dimensions-api-lab/tree/master/archive) folder contains **historical copies** of notebooks used for workshops and tutorials. Most often, these are customized versions of the generic notebook templates (in the `cookbooks` folder), adapted for a specific institution or audience. Please note that the notebooks in this folder are simply *archived* for future reference and **not maintained** afterwards. So use the materials in the `cookbooks` folder for up to date examples and reusable templates.

### Using Binder

[mybinder.org](https://ovh.mybinder.org/) 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.

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/digital-science/dimensions-api-lab/master)

### Using Google Colab

[Google Colaboratory](https://colab.research.google.com) 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](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/digital-science/dimensions-api-lab/)

## Comments, bug reports

This project lives on [Github](https://github.com/digital-science/dimensions-api-lab). You can file [issues]([issues](https://github.com/digital-science/dimensions-api-lab/issues/new)) or ask questions there. Suggestions, pull requests and improvements welcome!

## See also

https://docs.dimensions.ai/dsl/resources.html

dimensions-api-lab

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