Mapping Manuscript Migrations: A New Linked Data Portal for Manuscript Provenance Research

by Emma Cawlfield Thomson

The Mapping Manuscript Migrations portal publicly launched on January 30, 2020 at the Round Four Digging into Data Challenge Conference at the National Science Foundation in Washington DC: https://mappingmanuscriptmigrations.org/

Home Page

The Mapping Manuscript Migrations portal homepage.

The MMM portal enables you to track hundreds of thousands of medieval and Renaissance manuscripts by origin, owner, author, and title. You can also visualize their journeys over the centuries from their place of production to their last known location. The image below demonstrates the migration patterns of manuscripts in the collection of Sir Thomas Phillipps. Each arc indicates the movement of a single manuscript, changing color from blue to red as the manuscript moved from its place of production to its last known location.

MMM uses Linked Open Data principles and technology to combine data from three important manuscript databases:

The portal is the product of two and a half years’ work by the MMM project team, performed across four partner institutions: the University of Oxford (Oxford e-Research Centre and Bodleian Libraries), the University of Pennsylvania (Schoenberg Institute for Manuscript Studies), the Institut de recherche et d’histoire des textes (IRHT-CNRS), and Aalto University (Semantic Computing Research Group).

The MMM project has been funded by the Trans-Atlantic Platform under Round 4 of its Digging into Data Challenge (2017-2020). The national funding agencies contributing to the project are the Economic and Social Research Council (US), the Institute of Museum and Library Services (US), the Agence nationale de la recherche (France), and the Academy of Finland.

To contribute data to the MMM portal, do so via the Schoenberg Database of Manuscripts, which is free and open to all. Once you add your data to the Schoenberg Database, it will automatically flow down a linked data transformation pipeline into MMM.

Access the data and documentation of the MMM project via these pages:

The MMM dataset is available for reuse under a CC-BY-NC 4.0 license.

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