@dmvis/dmvis v1.0.0

Documentation • Demo website • Gallery repository • Contributing

A Framework for Interactive Multi-Criteria Decision Making with Data Visualisations

Introduction

DMVis is an innovative platform designed to revolutionize multi-criteria decision making through the power of data visualisation. In the existing landscape, decision making tools frequently restrict users from independently exploring their information space. Users are generally confined to navigating through cumbersome lists or relying on opaque recommendations, as seen in platforms like Funda and Netflix. This project aspires to transcend these limitations by leveraging data visualisations, an impactful but underemployed tool in public domains for multi-criteria decision making.

The need for DMVis stems from two core challenges in the current utilization of data visualisations. Firstly, the transition of sophisticated visualisation concepts from academic research to functional, user-accessible tools remains a significant hurdle. Secondly, the prevalent visualisation library, D3.js, is seldom integrated into scalable interactive frameworks such as Angular, React, or Svelte.

DMVis aims to empower users to navigate through their decision making processes with greater clarity and insight, leveraging the untapped potential of data visualisations in everyday decision making tools. Additionally, it will serve as a model, enabling future visualisation researchers to augment the gallery with their innovative decision making visualisations by employing the DMVis components. The project will be a step forward in making advanced data visualisation techniques more accessible ultimately empowering people to make data informed decisions in various application domains.

Project context

The framework is designed to be flexible and extensible, allowing developers to create a wide range of visualisations to suit their needs. DMVis is built using Svelte and D3.js, making it easy to integrate with existing web applications.

This application was written for the Softwareproject course at Utrecht University. The goal of the course is to develop a software application for a real-world client. The client for this project is Evanthia Dimara, an Assistant Professor and a researcher in Information Visualisation at the Visualisation and Graphics Group (VIG) at Utrecht University.

Demo

You can view a live demo of the project here. It displays the Gallery project which was created to showcase the visualisations that can be created using the DMVis framework.

Setting up

You will need to install the following dependencies:

• Node.js (preferably version 20.x or higher)
• npm

We have pinned our node version in .nvmrc so you can use nvm to install the correct version of node. If you have nvm installed (instructions for Linux and Windows), you can use the following command to install the correct version of node:

nvm install

Once you have installed the above dependencies, you can install the packages using the following commands:

npm install --save-dev husky
npm install

To maintain code quality, husky is used to run tests, linting, and formatting checks before commits. To enable this, you need to install the git hooks:

npx husky install

Developing

Start a development server:

npm run dev

# or start the server and open the app in a new browser tab
npm run dev -- --open

Building

To build your library:

npm run package

To create a production version of your showcase app:

npm run build

You can preview the production build with npm run preview.

Documentation

The documentation is written in markdown and rendered using docsify. You can check it out over here. To serve the documentation locally, run the following command:

npm run docs

License

This project is licensed under the AGPL-3.0 License - see the LICENSE file for details.