Although many European specialized museums are devoted to the preservation of silk, they usually lack size and resources to establish networks or connections with other collections. The H2020 SILKNOW project (Silk heritage in the Knowledge Society: from punched card to Big Data, Deep Learning and visual/tangible simulations) (http://silknow.org/) aims to produce an intelligent computational system in order to improve our understanding of European silk heritage. The SILKNOW platform will form a coherently integrated system to give access to a wide variety of data describing silk-related objects to researchers, museums curators or general public with a single interface.
SILKNOW has crawled datasets from websites or online databases of Cultural Heritage Institutions preserving silk-related artefacts - such as the Musée des Tissus de Lyon (via the Joconde database), the Victoria and Albert Museum or the Museos estatales del MEC. The SILKNOW crawler is made in Node.js and its source code is available at: https://github.com/SILKNOW/crawler/. In order to give access to these various datasets via a unique point of entry, it is necessary to harmonize them by designing and implementing a unique and complete data model, well adapted to Cultural Heritage data describing textile-related artefacts and more precisely silk-related artefacts. This data model is based on the CIDOC-CRM. There is yet no CRM extension for dealing with the production of textile artefacts; something similar to FRBRoo, for the creation, production and expression process in literature and the performing arts. The more complex modeling of the semantics included in data about the creative and productive process of silk textiles requires elaborating new classes and properties.
During this session, we would like to :
- make a short presentation on how we have mapped these data in CIDOC-CRM,
- discuss which new classes and properties could be elaborated to describe silk textiles’ data (and more generally textile's data),
- discuss the process of creation of these new classes and properties.