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This report, prepared by Graham Klyne and David Lewis of the Oxford e-Research Centre, relates to an investigation into the use of the ResearchSpace software to explore the MMM data.

This document describes an experiment using ResearchSpace to realise research questions devised for the Mapping Manuscript Migrations project (MMM) over project data. It also surveys the questions to assess how well this approach would work, and briefly considers using worksets: named groupings of entities. The initial findings are encouraging, but further work will be needed to validate them in a real research context.

http://blog.mappingmanuscriptmigrations.org/wp-content/uploads/2020/12/Exploring-research-questions-through-browsing_-ResearchSpace-for-MMM.pdf

The effective reuse of provenance-related information from catalogues of medieval and Renaissance manuscripts depends, ultimately, on the approach taken by the manuscript cataloguer towards recording provenance. There are two possible approaches:

• Recording the physical evidence found in the manuscript itself, usually in the form of a series of notes or narrative statements about the manuscript’s history;
• Assembling a structured list of successive stages in the ownership of the manuscript, usually in chronological order, together with information about the evidence for each stage.

This short paper is the result of the MMM Project’s work in transforming TEI-XML documents from Medieval Manuscripts in Oxford Libraries into RDF triples which could be mapped to the MMM unified data model.

It assesses the results of this process, and examines ways of structuring TEI-encoded descriptions in order to improve the effectiveness of their mapping to event-centric data models.

http://blog.mappingmanuscriptmigrations.org/wp-content/uploads/2020/12/Encoding_provenance_in_TEI_rev.pdf

You can read more about the MMM Project’s work with the Oxford TEI-XML data in this forthcoming paper: Burrows, Toby, Athanasios Velios, Matthew Holford, David Lewis, Andrew Morrison, and Kevin Page, ‘Transforming TEI Manuscript Descriptions into RDF Graphs,’ Scholarly Digital Editions, Graph Data-Models and Semantic Web Technologies (GraphSDE) 2019 proceedings, forthcoming 2020

The White Paper prepared by the Mapping Manuscript Migrations project as its final report to the Digging into Data Challenge can now be downloaded from the project’s page on the Digging into Data site:

https://diggingintodata.org/awards/2016/project/mapping-manuscript-migrations-digging-data-history-and-provenance-pre-modern

A copy is also available here:

http://blog.mappingmanuscriptmigrations.org/wp-content/uploads/2020/08/mmm.digging.project.white_.paper__0.pdf

Version 2.0.0 of the Mapping Manuscript Migrations Knowledge Graph is available on Zenodo:
https://zenodo.org/record/3935259

This includes the MMM Schema, as well as the RDF triples used for the MMM Portal.

Technical documentation from the Mapping Manuscript Migrations project is now available via GitHub. This include the Data Model and Schema, as well as a set of SPARQL tutorials based on the MMM dataset.

https://mapping-manuscript-migrations.github.io/

Author: Toby Burrows

My goal is to export data relating to manuscripts formerly owned by Sir Thomas Phillipps (1792-1872) from the MMM Portal, and then to import these data into a separate nodegoat database of Phillipps manuscripts. This has involved the following steps.

In the MMM Portal:

• Filter for Thomas Phillipps as an owner: result = 8,750 records
• Export these results as a CSV spreadsheet into the Yasgui SPARQL service, with the accompanying SPARQL query

In Yasgui:

• Edit the SPARQL query from MMM:
  • Remove unwanted elements – chiefly the IDs and some provenance events; keep the labels
  • Add two missing queries: Phillipps number, and number of miniatures
  • Remove the 10-manuscript limit in the query
• Re-run the SPARQL query (21 variables)
  • Result = 149,777 rows and 21 columns (81.9 seconds) – an average of 17 rows per manuscript
• Download the spreadsheet

In Google Sheets: (OpenRefine could also be used here)

• Upload and open the CSV file
• Fix UTF-8 character display problems
• With the Power Tools add-on, use Merge and Combine to combine the rows relating to a single manuscript:
  • Use a semicolon delimiter to merge values
  • Remove an additional semicolon at the beginning and end  of merged values – where there was empty content;
• Result = 8,750 rows / manuscripts – 6,882 of them with Phillipps numbers

In nodegoat:

• Upload the amended CSV file
• Create Import Templates for each section of the import process
• Import the objects (manuscripts) and descriptive fields to nodegoat
• Import production and transfer events as sub-objects – use the MMM URI as the field for matching with objects / manuscripts

I will document the nodegoat process in more detail on my Phillipps project blog.

Burrows, T, Emery, D, Fraas, M, Hyvönen, E, Ikkala, E, Koho, M, Lewis, D, Morrison, A, Page, K, Ransom, L, Thomson, E, Tuominen, J, Velios, A and Wijsman, H 2020 “Mapping Manuscript Migrations Knowledge Graph: Data for Tracing the History and Provenance of Medieval and Renaissance Manuscripts,” Journal of Open Humanities Data, 6: 3. DOI: https://doi.org/10.5334/johd.14

New publication by members of the @MSMigrations team:

“Linked Open Data Vocabularies and Identifiers for Medieval Studies”

in: DHN 2020: Digital Humanities in the Nordic Countries: Proceedings (CEUR Workshop Proceedings, vol. 2612), pp. 211-218

http://ceur-ws.org/Vol-2612/short5.pdf

The MMM aggregated dataset was updated on May 12th, 2020. This involved a new upload of data from the source datasets, followed by their transformation and mapping to the MMM data model. The updated data can be browsed and searched through the MMM portal and the MMM SPARQL endpoint:

http://mappingmanuscriptmigrations.org/

http://ldf.fi/mmm/sparql

http://mappingmanuscriptmigrations.org/

The entire MMM Knowledge Graph (20+ million RDF triples) can now be downloaded from Zenodo:

 https://zenodo.org/record/3667486