# Develop data-centric web apps in Jupyter with Voilà and VOIS

- Institution: CERN
- Department: HEP Computing
- Speaker: Davide De Marchi
- Year: 2024
- Language: English
- Subjects: Computer science
- Source: [CERN](https://videos.cern.ch/record/3004445)
- Licence: [CERN](http://copyright.web.cern.ch)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

After more than four years of experience in developing dashboards with Jupyter and Voilà \[1\] and the development of a library that simplifies the creation of user interfaces for compelling interactive visualization, we can say that yes: it is possible to use Jupyter as an advanced development environment for the creation of complex web applications, centred on data and equipped with a simple but modern user interface and perfectly capable of supporting interactive and integrated exploration on multiple datasets. What we have done in this period at the Joint Research Centre of the European Commission, within the on-premise cloud infrastructure called **BDAP** \[2\] \[3\] (Big Data Analytics Platform), was to support our fellow scientists and researchers with advanced storage services for big data, parallel and GPU processing, data analysis and Machine Learning/Deep Learning. In the final phase of many of the collaborations we have established with the scientific units of the JRC, the communication of research results has gradually taken a more important role. Whether it is to inform colleagues and collaborators, as well as to communicate results to the political DGs of the Commission, to publish in scientific journals or to present research work to an audience of non-experts, over time the creation of interactive tools that allow autonomous exploration of the data and results generated by research have met with growing success. We started from simple dashboards where basic graphs allowed us to summarize the concepts being researched, and then gradually added geo-spatial visualizations with the aim of geographically framing the phenomena studied, to finally arrive at complex applications that can be used via the web for interactive communication and the exploration of multiple and interconnected datasets. Geographical, textual and numerical data integrate with customized charts and visualizations created ad-hoc to best describe the object of study and the results…

## Lectures

1. [Develop data-centric web apps in Jupyter with Voilà and VOIS](https://invisiblenetwork.ai/learn/cern/3004445/dcdbd43cbb7e), 20 min (CERN's player)