KB/LIBRIS Definitions

This repository is a collection of vocabulary and scheme definitions and mappings to external resources. These define the foundation of linked library data used by the National Library of Sweden.

Dependencies

Install the Python-based dependencies (preferably within a virtualenv):

$ pip install -r requirements.txt

Usage

Run the following script to build the full set of definition resources:

$ python datasets.py -l

You can also pass dataset names to generate the different parts in isolation. Pass -h or --help to the script for details.

Contents

The source/ directory contains the main vocabulary mappings for linked data at KB.

Here can also be found a bunch of common definitions and mappings, as well as language labels more or less manually synced with various external origins. See datasets.py for the details.

It also contains a hand-curated set of RDF types extracted from MARC fixed field definitions (006, 007 and 008 for bib, auth and hold).

Vocab & MARC

The vocabulary is split into the formally deciced "vocab" terms, and the legacy "marc" (often unstable) terms stemming from MARC21 constructs not yet interpreted according to the new modelling principles (based on RDF and linked data (see source/doc/model.en.mkd)).

In these files are special:

• source/vocab/bf-to-kbv-base.rq and source/vocab/bf-map.ttl are used to automatically wire up the base BF2 mappings and term hierarchies.

• source/vocab/display.jsonld defines lenses used to display data (as "cards" or "chips").

• source/vocab/platform.ttl and source/vocab/services.ttl map various technical terms to public vocabularies.

• source/vocab/enums.ttl, source/vocab/construct-enum-restrictions.rq, and source/marc/enums.ttl define the terms (properties and classes) for controlled, "enumerable" values. A lot of these stem from controlled values for columns in fixed fields in MARC21. Some come from RDA, and some from cleaned up defintions in BibFrame 2, or our own vocabulary. (See links in the data for references.)

  These files also contain certain instances of these classes. Specifically, these correspond to the domain of the properties defined as @type: @vocab in source/vocab-overlay.jsonld. These are special values defined within the vocabulary (often because they are very "type-like"). A prime example is IssuanceType, whose values are kept together with the vocabulary itself.

• source/marc/construct-enums.rq combine to create all other "enumerable" values, which may or may not become merged with other controlled lists in the future. (When that is done, the definition here must be removed and its URI be places in a sameAs relation in whatever term that is replacing it.

Note: the file source/vocab/check-bases.rq is used to check some sanity in the generated structures. It is advised to heed any warnings by correcting the relevant sources.

Maintenance

Tip: During vocab development. Regularly run just:

    $ python datasets.py vocab

to generate a vocab build file. Look at it as Turtle by running:

    $ rdfpipe -ijson-ld:context=build/vocab/context.jsonld build/vocab.jsonld

, and/or make a nice, digested tree view by running:

    $ python scripts/misc/vocab-summary.py build/vocab.jsonld -c build/vocab/context.jsonld -v

marcframe & legacy mappings

By using utilities in the whelk-core repository; you can generate a SPARQL construct file from the marcframe.json mappings, from which you can i turn generate a basic vocab file:

$ cd ../whelk-core/ && gradle -q vocabFromMarcFrame #.rq

To generate RDF descriptions from legacy MARC definitions, use:

$ python scripts/marcframe-skeleton-from-marcmap.py scripts/marc/marcmap.json --enums

See that script for other options.

Pipe the output to rdfpipe -ijson-ld:base=source/ -oturtle - to get it as Turtle.