- Removed obsolete slots: `has_or_had_custodian_observation`, `provider`, and `specificity_annotation`.
- Updated `has_or_had_score` slot to use `SpecificityScore` class and modified its description and examples.
- Added new slots: `end_seconds`, `end_time`, `has_archive_path`, `has_or_had_custodian_name`, `protocol_name`, and `protocol_version`.
- Introduced a script `check_annotation_types.py` to validate the presence and structure of `custodian_types` in YAML files.
- Added a script `update_specificity.py` to automate updates related to `SpecificityAnnotation` to `SpecificityScore`.
- Introduced GeospatialLocation class for specific geospatial locations.
- Added HandsOnFacility class representing facilities for hands-on experiences.
- Created Hyponym class for narrower terms or instances.
- Added ImagingEquipment class for imaging-related equipment.
- Introduced LoadingDock class for loading dock facilities.
- Created LocalCollection class for locally held collections.
- Added Locker class for storage lockers available to visitors/staff.
- Introduced MichelinStarRating class for Michelin star ratings.
- Created MicrofilmReader class for equipment used to read microfilms.
- Added OperationalArchive class for archives containing operational records.
- Introduced OperationalUnit class for operational units within organizations.
- Added has_or_had_archive slot for associating archives with entities.
- Created has_or_had_rating slot for ratings assigned to entities.
- Introduced has_or_had_section slot for sections or units within organizations.
- Added has_geospatial_location slot linking nominal places to precise geospatial coordinates.
- Introduced VerificationStatus, Verifier, VersionNumber, ViabilityStatus, VideoCategoryIdentifier, VideoIdentifier, WhatsAppProfile, WordCount, WorkRevision, and WorldCatIdentifier classes to capture various aspects of data verification, categorization, and identification.
- Created corresponding slots such as analyzes_or_analyzed, unit_type, years_restricted, benefits_provided, consumes_or_consumed, has_or_had_contact_details, has_or_had_investment, has_or_had_liability, has_or_had_likelihood_score, has_or_had_location, has_or_had_net_asset, is_or_was_affiliated_with, is_or_was_allocated_to, is_or_was_alternative_form_of, is_or_was_categorized_as, is_or_was_used_by, and was_last_updated_at to facilitate detailed tracking and categorization of entities and their attributes.
- Each class and slot includes detailed descriptions, usage examples, and mappings to relevant ontologies to ensure interoperability and clarity in data representation.
