Tracing the History and Provenance of Medieval and Renaissance Manuscripts through Linked Data

poster / demo / art installation
  1. 1. Toby Nicolas Burrows

    Oxford University

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The study of medieval and Renaissance manuscripts is a very active research field, covering a wide range of disciplinary perspectives, and supported by a proliferation of digital resources in the form of catalogues, databases, digital editions and digital images (Da Rold and Maniaci 2015). But there is little in the way of interoperable digital infrastructure to link these disparate sources together, and the evidence base for manuscript research is, for the most part, fragmented and scattered. As a result, large-scale research questions remain very difficult, if not impossible, to answer.
The Mapping Manuscript Migrations (MMM) project, funded by the Trans-Atlantic Platform under its Digging into Data Challenge for 2017-2019, aims to address these problems. It is led by the University of Oxford, in partnership with the University of Pennnsylvania, Aalto University in Helsinki, and the Institut de recherche et d’histoire des textes in Paris (Burrows et al. 2018). The project is building a coherent framework to link manuscript data from various disparate sources, with the aim of enabling searchable and browsable semantic access to aggregated evidence about the history and provenance of medieval and Renaissance manuscripts.
The four initial data sources include three relational databases (the Schoenberg Database of Manuscripts, Bibale, and Medium) and a manuscripts catalogue consisting of XML documents encoded with the Text Encoding Initiative’s Manuscript Description schema. They contain a total of 370,000 records. These have been transformed into RDF conforming to a unified data model based on CIDOC-CRM and FRBR
OO (Le Bouef 2012). Key entity types have been reconciled with Linked Data vocabularies for persons, organizations, places, and works. A user interface has been built which combines faceted searching and browsing with visualizations for exploring the data geographically and chronologically.

This framework is being used as the basis for a large-scale analysis of the history and movement of these manuscripts over the centuries. The broad research questions being addressed include: how many manuscripts have survived; where they are now; and which people and institutions have been involved in their history. More specific research focuses on particular collectors and types of manuscripts.
The poster will present the results of the first eighteen months of this project. The topics covered will include the new digital platform which has been developed, the sources of data which have been combined, the data modeling which has been carried out to link disparate data sources, the Linked Data principles and techniques which have been deployed, and the ways in which the aggregated evidence has been presented and visualized.
In particular, the poster will demonstrate the following aspects of the Linked Data environment developed by the project:

The unified data model based on CIDOC-CRM and FRBRoo;
The publishing process for transforming the source datasets into RDF suitable for ingest to the MMM triple store;
The reconciliation processes implemented to link the aggregated data to Linked Data vocabularies;
The user interface developed by the project, including geographical and network visualizations for exploring the aggregated data.


Burrows, T., Hyvönen, E., Ransom, L. and Wijsman, H.
(2018). Mapping Manuscript Migrations: digging into data for the history and provenance of medieval and Renaissance manuscripts.
Manuscript Studies: a Journal of the Schoenberg Institute for Manuscript Studies,
(1): 249–52.

Da Rold, O. and Maniaci, M.
(2015). Medieval manuscript studies: a European perspective. In Conti, A., Da Rold, O. and Shaw, P. (eds),
Writing Europe, 500-1450: Texts and Contexts
(Essays and Studies, 68). Cambridge: D. S. Brewer, pp. 1-24.

Le Boeuf, P.
(2012). Modeling rare and unique documents: using FRBRoo/CIDOC CRM.
Journal of Archival Organization,
(2): 96–106.

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