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Digital Scriptorium Data Reconciliation Process through OpenRefine

Digital Scriptorium OpenRefine documentation and JSON recipes for data reconciliation and management

General instructions

When utilizing the JSON instructions (also known as recipes) found in this repository for DS data in OpenRefine, find the left column, select the Undo/Redo tab, select Apply, paste the JSON code, and then select Perform operations. This will execute the prewritten commands which perform various actions on the data for the reconciliation process and when merging new datasets with previous ones.

Facets and filters can also be used on the data by using drop-down menus available on each column header and displayed in the left column when selecting the Facet/Filter tab.

The following notes apply to file naming conventions for editing file name variables found in the instructions in this repository (use all lowercase letters where applicable):

  • DATE = the date the file/dataset was generated/created/extracted in YYYYMMDD format
  • VALUE = the type of metadata values or metadata element extracted and enriched, such as genres or languages or names
  • INSTITUTION = the code for the name of the institutional source for the data, such as penn or kansas or csl
  • DATATYPE = the type of encoding standard or technical format of the metadata source, such as marcxml or mets or csv
  • One or more DIFFERENTIATORS may also be added on the file name to disambiguate files, using sources names of collections or databases, such as bibliophilly or muslimworld, or batch numbers, such as batch-1, batch-2, etc.

Examples of correctly formatted file names:

  • 20230518-materials-rome-mets-legacy-enriched.csv
  • 20230630-genres-penn-marcxml-bibliophilly-enriched.csv
  • 20230715-names-kansas-marc-enriched.csv
  • 20230816-languages-princeton-marcxml-batch-3-enriched.csv
  • 20230901-places-hrc-csv-fragments-batch-1-enriched.csv

Reconciliation instructions by metadata element / authority type

Genres

Genre reconciliation instructions

Languages

Language reconciliation instructions

Materials

Material reconciliation instructions

Names

Name reconciliation instructions

Places

Place reconciliation instructions

Subjects

Subject reconciliation instructions

Titles

Title reconciliation instructions

Instructions for integrating new reconciliations with previously reconciled data

Merging newly enriched data with data dictionaries