Check out suspended projects

Objectives of this prototype: (1) Enhanced Understanding: Reveals patterns, themes, and sentiments, offering insights into context. (2) Efficient Analysis: NLP automates analysis of historical texts, saving time. (3) Interactive Exploration: SDE offers engaging visualizations like word clouds and frequency plots. (4) Facilitating Research: NLP-based SDE aids scholars with a rich, accessible dataset.

The project aims at reconstructing the provenance of the Italian paintings collection at the MET Museum in New York on the basis of MET OpenAccess CSV and Zeri&LODE. The datasets have been analysed and compared with archival and bibliographical resources to reconstruct the history of the masterpieces, artists and art dealers involved in this process. The website can be enjoyed by a variety of users who want to explore the secrets of one of the most important Italian art collections in the world.

The project aims at developing a software solution that integrates a relational database and a graph database, enabling the simultaneous population and querying of both systems. It processes structured data from CSV and JSON files using Python's pandas library for efficient and intuitive data handling. The software demonstrates how relational and graph database models can be utilized together for versatile data management and querying tasks.