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NextPyter: Open-Source Collaborative Platform for Interdisciplinary Research

Project
The research project is based on the proposal of an open-source collaborative platform for interdisciplinary research, called NextPyter, aimed at simplifying complex research workflows and promoting seamless collaboration among members of multidisciplinary research teams. The NextPyter platform represents a significant advancement at the intersection of technology and the humanities, offering numerous advantages for scholarly and interdisciplinary research projects. The platform integrates the Jupyter Notebook framework into a wider research workflow designed to facilitate researchers from multidisciplinary contexts, enabling the use of instruments like Jupyter Notebooks in conjunction with online file storage and collaboration platforms, while supporting real- time collaboration directly within the Notebook in a user-friendly interface. The chosen software stack includes Jupyter Notebook as the notebook engine, NextCloud as open-source solution for online file storage and collaboration, and Kubernets technology to distribute and balance the load over multiple nodes. The chosen technology stack also allows remote execution of Notebooks, which, combined with the usage of cloud-based platforms, offers several advantages for data scientists: storage scalability, parallel computing, resource-intensive tasks on remote machines with specialized hardware (e.g. GPUs), collaboration, privacy, and security thanks to self-hosted solutions. To show the potential of NextPyter in facilitating interdisciplinary research collaboration and providing a flexible easy-to-use and high-performance environment accessible to non-technical researchers, the platform will be tested over a case study coming from literature and cultural studies. Through the collaborative platform, researchers in humanities will have the opportunity to create images from natural language descriptions exploiting generative AI algorithms. Specifically, through an analysis of Boiardo’s “Inamoramento de Orlando” and the lost gardens of Renaissance Ferrara, the use of the platform will allow researchers to: a) unveil new interpretative possibilities of Boiardo’s literary text through the creation of images that originate directly from the text; b) to combine philological information extracted from the text with data from archaeobotanical studies to generate images that assist in faithfully reconstructing a lost element of the past, such as the gardens of the House of Este. To summarize the most innovative contributions of the project, NextPyter may facilitate complex research workflow and promote seamless collaboration among researchers from different disciplinary fields, offering an easy-to-use platform for real-time collaboration capabilities on Notebooks, enhanced by a file storage system and accessible through an easy-to-use Web-based interface. The possibility to execute Notebooks on premise or on remote cloud systems will also guarantee privacy-enhanced management of research data.
  • Overview
  • Skills

Overview

Contributor (4)

CANALI Claudia   Scientific Manager  
LANCELLOTTI Riccardo   Participant  
MARCHETTI Cecilia   Participant  
MENETTI Elisabetta   Participant  

Leading department

"Enzo Ferrari" Department of Engineering   Principale  

Term type

FAR 2024 Progetti interdisciplinari - Linea UNIMORE

Financier

Università degli Studi di MODENA e REGGIO EMILIA
Funding Organization

Partner

Università degli Studi di MODENA e REGGIO EMILIA

Total Contribution (assigned) University (EUR)

79,344€

Date/time interval

December 2, 2024 - December 1, 2026

Project duration

24 months

Skills

Concepts (4)


PE6_1 - Computer architecture, embedded systems, operating systems - (2024)

PE6_2 - Distributed systems, parallel computing, sensor networks, cyber-physical systems - (2024)

SH5_2 - Theory and history of literature, comparative literature - (2024)

Settore IINF-05/A - Sistemi di elaborazione delle informazioni
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