MuViAS 3.0

MuViAS born as a tool to visualize multidimensional datasets implementing a doxel model.
The application is working on top of the NASA Web WorldWind framework.
The development of this project took inspiration from the EST-WA developed by Politecnico di Milano.
However, MuViAS implements many new functionalities and works on the Web with great performances, thanks to many HTML5 and WebGL techniques that permit to handle big amount of data over the web.

What's new? UN World Challenge 2018

Thanks to the collaboration with Alma Mater Studiorum (Università di Bologna), Università di Padova, and the GSoC 2017 and 2018 Students, MuVIAS now implements WFS capabilities and Marker Cluster. MuViAS 3.0 with its new look is also faster than ever and support many new formats.

Want to try a demo?

Try the hosted version or deploy your own

Application Audience

MuViAS could be the first point of reference when users need to visualize multi-dimensional datasets.

Our audience so is very wide, since a wide category of users could use it for different purposes. All the uses of the application refer to a better understanding of the data thanks to a visual perception in a 3D environment and can be adopted in many study areas, where people need to understand the data inside a dataset. Thus the category of users that can get advantages from it could vary from studies in the telecommunication, to the geological or environmental one.

How to start


To start using MuViAS, just go to the demo page and follow the tutorial to import a sample dataset.
You will be guided throughout the application to learn how to use the importing system and to use the various items of the user interface.

MuViAS is more! Many other ways to visualize data are shown from the other demos available in the MuViAS suite.
Just select a dataset and play with the importing parameter to obtain your custom data visualization environment.

What can you do?


What can you get out of MuViAS?

Upload a custom dataset

Uploading your dataset is really easy, just follow the datasets in the example and you will be able to import your data easily.

Compare two variables

Our application permits to upload a dataset with multiple variables and compare two of them in a single view, even during the time.

Retrieve statistics from data

The system permits to obtain several information from your data. You can cluster them and obtain the variance, the average or even the correlation between two variables.

Use the application


Import a point feature dataset

To import a dataset the application provides a 'select file' box that allows choosing a file in your computer and importing it inside the application.
It is also possible to choose a file available online, inserting the link to the file location.
The file should have a .CSV format and contain the following columns in any order:

  • Latitude
  • Longitude
  • Time
  • Variable optional

  • After having selected the file, click on the Load Configuration button to select the appropriate kind of file (Georeferenced CSV).
    Now the application, under the Georeferenced CSV menu, will show all the options to import the file correctly.

    To customize the environment, from the dropdown menu, click on Advanced Options and select the required parameters.

    Browse the data

    When the data is successfully imported, it will be shown over the globe. You will see some doxels representing the data, in particular the color will represent the first selected variable.
    The layers of time will be shown according to the time-step selected in the Advanced Options panel during the importing of the data.
    From the left panel you can use all the available filters, browse through the time, and customize many options.

    To obtain information about a doxel, you can select from the top bar the Point Info selector and click on a doxel.
    A panel showing some statistics will appear on the bottom

    To create some spatial cluster, you can instead click on the top bar, selecting the Big Doxels selector. Automatically the doxels will be grouped according to the group defined during the importing of the data. By default the color will represent the weighted average.

    Main Developer

    Gabriele Prestifilippo

    Developer Collaborators

    Simone Battaglia
    Tobia Peruzzi