- Implemented a new script `test_pico_arabic_waqf.py` to test the GLM annotator's ability to extract person observations from Arabic historical documents.
- The script includes environment variable handling for API token, structured prompts for the GLM API, and validation of extraction results.
- Added comprehensive logging for API responses, extraction results, and validation errors.
- Included a sample Arabic waqf text for testing purposes, following the PiCo ontology pattern.
- Introduced LEGAL-FORM-FILTER rule to standardize CustodianName by removing legal form designations.
- Documented rationale, examples, and implementation guidelines for the filtering process.
docs: Create README for value standardization rules
- Established a comprehensive README outlining various value standardization rules applicable to Heritage Custodian classes.
- Categorized rules into Name Standardization, Geographic Standardization, Web Observation, and Schema Evolution.
feat: Implement transliteration standards for non-Latin scripts
- Added TRANSLIT-ISO rule to ensure GHCID abbreviations are generated from emic names using ISO standards for transliteration.
- Included detailed guidelines for various scripts and languages, along with implementation examples.
feat: Define XPath provenance rules for web observations
- Created XPATH-PROVENANCE rule mandating XPath pointers for claims extracted from web sources.
- Established a workflow for archiving websites and verifying claims against archived HTML.
chore: Update records lifecycle diagram
- Generated a new Mermaid diagram illustrating the records lifecycle for heritage custodians.
- Included phases for active records, inactive archives, and processed heritage collections with key relationships and classifications.
- Add emic_name, name_language, standardized_name to CustodianName
- Add scripts for enriching custodian emic names from Wikidata
- Add YouTube and Google Maps enrichment scripts
- Update DuckLake loader for new schema fields
- Implemented `generate_mermaid_with_instances.py` to create ER diagrams that include all classes, relationships, enum values, and instance data.
- Loaded instance data from YAML files and enriched enum definitions with meaningful annotations.
- Configured output paths for generated diagrams in both frontend and schema directories.
- Added support for excluding technical classes and limiting the number of displayed enum and instance values for readability.
- Implemented a Python script to validate KB library YAML files for required fields and data quality.
- Analyzed enrichment coverage from Wikidata and Google Maps, generating statistics.
- Created a comprehensive markdown report summarizing validation results and enrichment quality.
- Included error handling for file loading and validation processes.
- Generated JSON statistics for further analysis.
- Introduced a comprehensive class diagram for the heritage custodian observation reconstruction schema.
- Defined multiple classes including AllocationAgency, ArchiveOrganizationType, AuxiliaryDigitalPlatform, and others, with relevant attributes and relationships.
- Established inheritance and associations among classes to represent complex relationships within the schema.
- Generated on 2025-11-28, version 0.9.0, excluding the Container class.
- Implemented a Python script that fetches and enriches entries from the NDE Register using data from Wikidata.
- Utilized the Wikibase REST API and SPARQL endpoints for data retrieval.
- Added logging for tracking progress and errors during the enrichment process.
- Configured rate limiting based on authentication status for API requests.
- Created a structured output in YAML format, including detailed enrichment data.
- Generated a log file summarizing the enrichment process and results.
- Created AuxiliaryDigitalPlatformTypeEnum.yaml to classify types of secondary digital platforms.
- Created AuxiliaryPlaceTypeEnum.yaml to classify types of secondary physical locations.
- Added OrganizationBranchTypeEnum.yaml for formal organizational branches at auxiliary locations.
- Introduced auxiliary_places.yaml slot to link CustodianPlace to subordinate physical locations.
- Introduced auxiliary_platforms.yaml slot to link DigitalPlatform to subordinate digital properties.
- Added located_at.yaml slot to connect OrganizationalStructure to physical locations.
- Created PlantUML diagrams for custodian types, full schema, legal status, and organizational structure.
- Implemented a script to generate GraphViz DOT diagrams from OWL/RDF ontology files.
- Developed a script to generate UML diagrams from modular LinkML schema, supporting both Mermaid and PlantUML formats.
- Enhanced class definitions and relationships in UML diagrams to reflect the latest schema updates.
- Created the Country class with ISO 3166-1 alpha-2 and alpha-3 codes, ensuring minimal design without additional metadata.
- Integrated the Country class into CustodianPlace and LegalForm schemas to support country-specific feature types and legal forms.
- Removed duplicate keys in FeatureTypeEnum.yaml, resulting in 294 unique feature types.
- Eliminated "Hypernyms:" text from FeatureTypeEnum descriptions, verifying that semantic relationships are now conveyed through ontology mappings.
- Created example instance file demonstrating integration of Country with CustodianPlace and LegalForm.
- Updated documentation to reflect the completion of the Country class implementation and hypernyms removal.
- Created SHACL shapes for validating temporal consistency and bidirectional relationships in custodial collections and staff observations.
- Implemented a Python script to validate RDF data against the defined SHACL shapes using the pyshacl library.
- Added command-line interface for validation with options for specifying data formats and output reports.
- Included detailed error handling and reporting for validation results.
- Implemented `owl_to_mermaid.py` to convert OWL/Turtle files into Mermaid class diagrams.
- Implemented `owl_to_plantuml.py` to convert OWL/Turtle files into PlantUML class diagrams.
- Added two new PlantUML files for custodian multi-aspect diagrams.
- Implemented three independent aspects for custodians: CustodianLegalStatus, CustodianName, and CustodianPlace.
- Renamed CustodianReconstruction to CustodianLegalStatus and updated all references.
- Created new components for CustodianPlace and PlaceSpecificityEnum.
- Removed direct links from CustodianObservation to Custodian, aligning with PROV-O standards.
- Generated comprehensive example instance demonstrating the new architecture.
- Updated documentation to reflect changes and provide guidance on multi-aspect modeling.
- Added React hook for managing IndexedDB operations, including storing and loading transformation results.
- Created complete YAML example for Rijksmuseum, illustrating the integration of all three aspects.
- Introduced custodian_hub_v3.mmd, custodian_hub_v4_final.mmd, and custodian_hub_v5_FINAL.mmd for Mermaid representation.
- Created custodian_hub_FINAL.puml and custodian_hub_v3.puml for PlantUML representation.
- Defined entities such as CustodianReconstruction, Identifier, TimeSpan, Agent, CustodianName, CustodianObservation, ReconstructionActivity, Appellation, ConfidenceMeasure, Custodian, LanguageCode, and SourceDocument.
- Established relationships and associations between entities, including temporal extents, observations, and reconstruction activities.
- Incorporated enumerations for various types, statuses, and classifications relevant to custodians and their activities.
- Introduced a new Mermaid diagram for Custodian Hub v2, detailing entities such as CustodianReconstruction, Identifier, TimeSpan, Agent, CustodianName, CustodianObservation, ReconstructionActivity, Appellation, ConfidenceMeasure, Custodian, LanguageCode, and SourceDocument.
- Established relationships between entities, including temporal extents, derivations, and revisions.
- Added a comprehensive PlantUML diagram reflecting the same structure and relationships, including enumerations for various types and statuses relevant to custodians and observations.
- Enhanced documentation to clarify the hub architecture pattern and its implications for data integrity and source authority.
