Evaluating the SharedCanvas Manuscript Data Model in CATCHPlus

TL;DR

This paper evaluates the SharedCanvas data model for describing medieval manuscripts, demonstrating its suitability for complex collections and its support for linked data, annotation, and crowd-sourcing.

Contribution

It assesses the SharedCanvas model's effectiveness on new collections, confirming its core robustness and highlighting areas for UI and discovery improvements.

Findings

SharedCanvas effectively models complex manuscript layouts.

The linked data approach enables seamless multi-repository interaction.

The model supports scholarly commentary and crowd-sourcing activities.

Abstract

In this paper, we present the SharedCanvas model for describing the layout of culturally important, hand-written objects such as medieval manuscripts, which is intended to be used as a common input format to presentation interfaces. The model is evaluated using two collections from CATCHPlus not consulted during the design phase, each with their own complex requirements, in order to determine if further development is required or if the model is ready for general usage. The model is applied to the new collections, revealing several new areas of concern for user interface production and discovery of the constituent resources. However, the fundamental information modelling aspects of SharedCanvas and the underlying Open Annotation Collaboration ontology are demonstrated to be sufficient to cover the challenging new requirements. The distributed, Linked Open Data approach is validated as an important methodology to seamlessly allow simultaneous interaction with multiple repositories, and at the same time to facilitate both scholarly commentary and crowd-sourcing of the production of transcriptions.