Project Context:
ECHOLOT operates within the European Collaborative Cloud for Cultural Heritage (ECCCH) framework to address fragmentation and heterogeneity of cultural heritage (CH) datasets across Europe. By combining institutional authority data (e.g., Europeana) with collaborative, crowd-sourced data (e.g., Wikimedia), ECHOLOT enables cultural heritage professionals and researchers (CHPRs) to create, enrich, and publish semantically rich, FAIR datasets while supporting data reuse, interoperability, and attribution.
TAKIN’s Contribution:
TAKIN leads Task T2.3 – Semantic Interoperability of Data (M3–M18), focusing on addressing heterogeneity across CH datasets. Key activities include:
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Mapping relevant formats, ontologies, and data models (Europeana Data Model, DS4CH, Semantic MediaWiki, Wikibase).
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Developing consistent, reusable data pattern documentation and model-to-model mappings for many-to-many data integration.
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Supporting practical deployment and validation through multiple case studies:
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Basque CH datasets (entity disambiguation and linking)
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European Literary Bibliography (data enrichment and harmonization)
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Media art collections (ontology development and interoperability)
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Flemish fine arts and performing arts collections (data transformation for Europeana/Wikimedia publishing)
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Swedish GLAM data (publishing, enrichment, and round-tripping across Wikimedia platforms)
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Objectives & Outcomes:
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Enable seamless integration and enrichment of heterogeneous CH datasets.
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Deliver AI- and knowledge-driven workflows for annotation, entity linking, and metadata enhancement.
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Establish best practices, guidelines, and training materials for CH data interoperability.
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Provide demonstrators of enriched, FAIR data accessible across multiple platforms while preserving attribution and rights management.
Impact:
ECHOLOT strengthens the European CH data ecosystem by bridging institutional and community-driven resources, creating interoperable, enriched datasets, and empowering CHPRs to efficiently manage, share, and reuse cultural data.