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.
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.
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:
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.
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
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
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
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
Upload the amended CSV file
Create Import Templates for each section of the
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 /
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
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: