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A desktop application to analyze, anonymize and audit learning analytics data sets.

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Graasp Insights

A Cross-Platform Desktop Client for Dataset Anonymization

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graasp-insights

About Graasp Insights

Graasp Insights is an open-source desktop client for dataset anonymization built with Electron.js. After loading a dataset into the application, a user can run anonymization scripts on the dataset, selecting from scripts built into the application, or writing their own scripts (in Python) via an in-app editor. The application runs completely on a user's local device, and its code is open-source and freely available (GitHub repository). It has initially been optimized to work on datasets generated by the Graasp educational platform.

See the Graasp Insights user guide for guidance on how to use the application.

For more information on the application, please visit the Graasp Insights landing page.

Distributions

You can get the latest official distribution from our GitHub release channel or the Graasp Insights landing page.

Legal Disclaimer

Graasp Insights (the 'software') and its source code are freely distributed under the GNU Affero General Public License (AGPLv3). The software and source code are provided to you “as is”, without warranty of any kind, express or implied. Without limiting the generality of the foregoing, the Graasp Association and École Polytechnique Fédérale de Lausanne (EPFL) make no representation or warranty regarding the functionality, reliability, or performance of the software, or the results to be obtained through the use of the software, or that the operation of the software shall be error-free. In no event shall the Graasp Association or EPFL be liable to you or any third party for any damages arising from the use of Graasp Insights, including but not limited to the distribution, misuse, leakage, or theft of any original files or datasets or duplicates thereof handled, processed, or generated by the software.

Developers

Getting Started

To run Graasp Insights on your device, make sure you have Node installed on your operating system. We strongly recommend that you use the Yarn package manager, so that the commands in package.json are executed seamlessly. However, these commands have npm equivalents, and you can use the default Node Package Manager (NPM) instead.

Once you have Node and Yarn/NPM installed, copy or clone the repository to your local machine, preferably using Git.

Installation

Inside the project directory, run yarn to install the application's dependencies. In the project's root directory, you will need to create a file called .env.local with the following contents:

GH_TOKEN=
BROWSER=none
REACT_APP_GOOGLE_KEY=

The GH_TOKEN is an environment variable used for releasing new versions of the application. If you want to create your own distribution of Graasp Insights, you can add your GH_TOKEN here and use electron-builder to manage releases on GitHub.

The BROWSER=none assignment instructs Electron not to use a web browser to load the application, but instead to use the native operating system's windows.

When you first run or build the application, a file called env.json will be created under the /public folder. If you update your .env.local and .env files with values for the variables in env.json, the contents of this file will also update the next time you run or build. This process is handled by scripts/setup.js.

Launch the application!

You are now ready to launch Graasp Insights! Simply run yarn start in your terminal, and the application will be launched.

Please submit any contributions, ideas, or issues you identify to the application's GitHub repository.

Build the application

Run yarn dist. MacOS systems can build the application for all other systems. Windows can only create a distribution for Windows.

Licenses

Licenses are displayed to the user during the application installation. The configuration follows the instructions for electron-builder. When building the application on macOS, the license saved in public/license_en.txt is used for all distributions, including for windows' .exe executable. However, a build on Windows requires a windows-encoded license public/windows_license.txt to deal with special characters.

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A desktop application to analyze, anonymize and audit learning analytics data sets.

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