Lomen is a research project aimed at exploiting the richness of digital archives, stitching up the relationships between entities and providing a visual access to data. It is a web-based platform that allows users to explore contents in a non-linear way, identifying patterns and fostering insight.
Providing access to digital archival collections is becoming a primary concern for curators; cultural institutions are becoming aware that simply creating an online repository for the archive is not enough to reach a vast public, and that availability doesn’t necessarily bring access. As a result, there is a growing need for the design of engaging interfaces, capable of supporting the exploration of digital archives.
The Lomen project has been applied to the historical archive of Luciano Baldessari, a notable Italian architect. His archive belongs to three main funds, owned by different institutions. The main fund is managed by the LADA laboratory of the Politecnico di Milano, and contains Baldessari’s technical drawings and his private correspondence. The other two archives, owned respectively by the CASVA center of the Milan municipality and by the MART museum contain photographs and paintings. The archive is divided by architectural projects: each project is described by the geographic location, the actors involved, the chronological extremes of the realization, the related bibliography, the drawings and the correspondence regarding the project.
The aim of the project is to provide a public, web-based access to the archive able to explicit the relationship between entities, creating a visual interface allowing users to explore the archive. Also, the application should have been flexible enough to handle inconsistencies in metadata and possible modifications of the database. A Further objective of the project was to provide to curators a backend to modify existing records and create new ones.
Lomen is structured around entities extracted from data and identified as the main elements of the corpus. For every entity we defined a set of suitable views, each one focusing on one or more characterizing attributes. Moreover, for every entity we defined a group of custom filters allowing the user to refine the corpus and to narrow the set of entities being shown in the current view.
You can read more about this project in this paper by Michele Mauri, Azzurra Pini, Daniele Ciminieri and Paolo Ciuccarelli.