Enriching and Futureproofing the Databases of the Hungarian Heritage House

Enriching and Futureproofing the Databases of the Hungarian Heritage House A short feasibility study and early manuscript for publication (version 0.2.0) Antal, Dániel Zagyva, Natália Mester, Anna Márta Introduction ĺImportant This document serves as a living document for documenting the Reprex-HH documentation to serve as a basis of the forthcoming joint publication. This is the version 0.2.0 and it has not been reviewed by Hagyomanyok Háza institutionally, it may contain mispresentation of some HH databases. DOI: 10.5281/zenodo.17759777; please check for potential later versions before re-using or citing. Folklore Databases in Hungary Folklore databases in Hungary play a crucial role in preserving, systematising, and rendering accessible the country’s intangible cultural heritage. The most significant collections and datasets are maintained by leading scientific and cultural institutions that have long served as custodians of ethnographic and musicological knowledge. The Ethnological Archives of the Museum of Ethnography function as the central archival repository of Hungarian ethnography. They hold an extensive corpus of manuscripts, photographs, films, and sound recordings, much of it originating from a nationwide network of community collectors who contributed materials through organised collecting schemes. Through sustained digitisation efforts, the Museum has made a substantial portion of these holdings available as online collections and thematic digital resources. These resources constitute an irreplaceable foundation for contemporary folkloristic research. The archives of the Institute of Ethnology and the Institute for Musicology primarily preserve materials accumulated through fieldwork conducted by researchers, along with records arising from archival investigations. They also safeguard the personal papers, manuscripts, and legacies of scholars, folklorists, and composers. Over the past decades, these institutes have developed a number of highly valuable thematic folklore databases, covering the domains of folk music, folk dance, and narrative folklore. 1 A fourth institution of major importance is the Heritage House (Hungarian Heritage House) in Budapest, founded in 2001. Its folklore collections and ongoing development projects are discussed in detail in the following chapter. For piloting, we chose to work with two data sources. 500 Folk Music Examples from Székelyföld: One of the processed collections derives from ethnomusicologist István Pávai’s representative selection of folk music from Székelyföld (Szeklerland in Romania.) The examples are organised according to a regional classification system developed by Pávai, based on his field research and tailored to the stylistic and geographical distribution of traditional dance music. The metadata accompanying the sound recordings include: place of use (macro-region, region, micro-region, settlement); genre; informant (name, age or year of birth); performance mode (instrumentation); date of collection; collector. The recordings originate from 101 settlements across Székelyföld. Folk Tale Inventory: The second collection is currently unpublished. In 2003–2004, Sára Dala and her colleagues compiled a dataset containing more than 11,000 Hungarian folk tales, intended to serve as the foundation for an online catalogue arranged by geographical area and chronology, supporting the work of researchers, educators, cultural mediators, and storytellers. Under the working title Folk Tale Inventory, the compilers processed the contents of 467 printed volumes. In addition to bibliographic data, the dataset includes the place of use (settlement, county), the informant, the collector, the date of collection, and the tale type. The editors intend to expand the dataset with materials published after 2000, as well as tales available in audio and video formats. Within the present project, we restrict our work to the material published in 1957 as Háromszék Hungarian Folk Poetry (Háromszéki magyar népköltészet), documenting the collections of Samu Konsza and his students in the Háromszék region. This subset comprises 121 folk tales from 39 Székelyföld settlements. We chose this collection to show that gradually we can extend our immaterial work model optimised for music to other related immaterial heritage. The transition from musical works to folk tales is natural, because the tales are often preserved as sound recordings, and they have similar textual manifestations as the lyrics of vocal music. Our aim is to follow the European Interoperability Framework1, and to utilise our work developed in the OpenMusE project, particularly with the creation of the architecture of the Open Music Observatory, and the experience gained with its Finno-Ugric federated module. we aim to create not only technically and semantically correct new representations of the databases of Hagyományok Háza (in short: HH) but also workflows (organisational aspect) and data governance (legal aspect) of our work. 1The European Interoperability Framework (EIF) not only as a semantic guide but also as a legal and organizational model (Commission and Digital Services 2017; European Commission 2017) to connect various library, museum, archival, geographic information and other services. 2 In our work, we aim to transfer some of the databases, or their data tables as datasets into a graph format. Particularly suitable data for this task is the person, corporate and geographical name spaces, which need to be permanently updated, and often enriched for further historical or other language variants. Another trivial choice is the representation of a thesaurus in this format, as thesauri per se follow a graph format. Last, but not least, the graph format can help to connect relational databases that are now standing alone, or to re-document and improve the metadata schemas of existing relational databases or their tables. Linking datasets across domains, institutions, and languages proved more difficult and less successful than the 5-star FAIR model suggests. In practice, findability, interoperability, and reuse are not easily achieved across national metadata practices, multilingual vocabularies, or heritage-specific contexts. For this reason, we adopted the extended 8-star model of linked cultural data proposed by Hyvönen and Tuominen (Hyvönen and Tuominen 2024), which adds essential dimensions such as provenance, multilingualism, contextualization, participation, and sustainability. This higher standard better reflects the realities of cross-border, community-anchored heritage work and connected unconnected, often less documented databases, Excel sheets, and different information sources. Architectural choices The architectural choices for connecting Hungarian music and folklore datasets to a futureproof, interoperable infrastructure must address three simultaneous challenges: (1) historically layered and multilingual heritage; (2) highly heterogeneous and partly undocumented legacy databases; and (3) limited institutional capacity for large-scale ontology engineering. For these reasons, we have focused on Wikibase as the core bridging technology. Its suitability is demonstrated most clearly by the National Library of Wales’ SNARC (Shared National Archival Record Catalogue) architecture, which has already been adopted as a model by cultural-heritage institutions across Europe. SNARC is a directly relevant precedent for HH, because it supports exactly the combination of requirements present in Hungary: distributed collections, multilingual metadata, legacy databases, and active community contributors. Wikibase has proven effective for multilingual authority control (Bianchini, Bargioni, and Pellizzari di San Girolamo 2021; Fagerving 2023). The Finnish Wikibase pilot of the National Library of Finland demonstrated how it can connect museum, linguistic, and archival records while also supporting community participation (National Library of Finland 2021). Similar experiences in minority-language contexts—such as the Võro User Group (Wikimedians of Võro language User Group 2025) and Wikimedia Norge’s Sámi knowledge project (Wikimedia Norge 2020)—show that Wikibase can combine semantic interoperability with respect for knowledge sovereignty and multilingual representation. These experiences are particularly suitable for connecting to less formal civic or community, municipal diaspora 3 Hungarian collections. These precedents confirm that Wikibase can act as a shared, multilingual curatorial platform for minority and diasporic heritage without imposing a single institutional metadata regime. The relevance of the Welsh precedent is explicitly confirmed in the documents the National Library has made public and is also reflected in the wider scholarly literature, and given the institutional strength of the Welsh National Library, it is probably the highest scaled subnational example. As summarised in our internal materials: “A notable example is the SNARC Wikibase… developed by the National Library of Wales. SNARC allows Welsh libraries, archives, and museums to describe cultural heritage using persistent identifiers and structured metadata in Welsh and English. It supports shared authority work and multilingual reconciliation while respecting institutional diversity and community input.” This architecture provides not only a technical blueprint but also a governance model that suits a heritage ecosystem with many semi-independent contributors, including fieldworkers, regional archives, civic initiatives, and diasporic communities. Wikibase offers an effective bridge between human-centred curatorial workflows and the formal structures of the semantic web. As an open, collaborative platform, it enables curators, researchers, and community partners to describe heritage materials in a readable, intuitive format, while simultaneously maintaining machine-actionable semantics through RDF export. This duality makes Wikibase particularly suitable for projects that must combine community participation, multilingual metadata, and interoperability with formal ontologies such as HDTO (ECCCH), CIDOC-CRM (museums), Records in Contexts (archives), and DCTERMS)2. In contexts characterised by limited archival depth, legacy databases of uneven quality, or undocumented local schema variations, strict ontology-based systems can easily become too rigid for practical curation. Wikibase, by contrast, supports incremental enrichment. Incomplete, contradictory, or uncertain statements can coexist with qualified assertions, references, and provenance notes. Curators can therefore record uncertainty—an intrinsic part of folkloristic and ethnographic data—without compromising the coherence of the underlying semantic structures. Its flexible data model also allows domain ontologies to be introduced progressively: digitaltwin classes, heritage-entity relations, component hierarchies, and temporal layers can be added over time without disrupting existing documentation practices. This progressive modelling principle is essential for a project like HH, where archival quality, provenance depth, and historical metadata formats vary significantly across collections. 2ECCCH: (Commission et al. 2022; ECHOES Ontology Task Force 2025); CIDOC: (Bekiari et al. 2024), RiC (Archives Expert Group on Archival Description 2023), Dublin Core (DCTERMS): (Core 2020). 4 The Welsh Model: Why SNARC Is the Most Relevant Precedent SNARC demonstrates how Wikibase can operate as a national-level authority and reconciliation layer for distributed archives. Its architecture exhibits several properties that map directly onto the needs of Hungarian folklore collections: 1. Multilingual authority control with community participation: SNARC maintains bilingual (Welsh/English) labels, descriptions, and authority records, enabling minority and regional languages to coexist with national cataloguing standards. This aligns with HH’s need to support Hungarian, regional dialects, and minority languages across the Carpathian Basin. 2. A federated approach rather than centralisation: Institutions retain autonomy over their internal databases, while contributing shared authority data into the Wikibase layer. This mirrors the governance model recommended we followed with the prototyping in the Finno-Ugric Data Sharing Space, and fits in with the situation in Hungary: HH must integrate data from diverse field researchers, local cultural centres, and legacy scholarly collections without imposing a single catalogue. 3. Support for weakly standardised, legacy, and community-derived data: SNARC deals with inconsistent archival metadata, variant place names, historical spellings, and ambiguous provenance—challenges identical to those found in Hungarian folklore collections. 4. A sustainable governance model: Wikibase enables contributors, stewards, validators, and reviewers to participate according to their role. This matches HH’s needs: ethnomusicologists, dance researchers, ethnographers, and community collectors can contribute in different capacities. 5. Compatibility with semantic-web export: SNARC relies on Wikibase’s RDF layer to integrate with external linked-data infrastructures—analogous to our plan to export to HDTO/ECCCH and other European data spaces. Wikibase as a Bridging Layer in Heritage Architectures Architecturally, Wikibase functions as a bridging layer between descriptive archives (AtoM, legacy field-record tables, digitised notebooks, manuscript metadata) and semantic infrastructures capable of supporting cross-institutional reasoning. It links curatorial work with graph-based analytics through: • Federated SPARQL queries • Multilingual labels and aliases • Reconciliation services • Versioned, provenance-rich authority records • Incremental modelling of heritage ontologies 5 This architecture has been tested extensively in the Finno-Ugric Data Sharing Space, where it supports the representation of complex, multilingual, and historically layered heritage in a transparent, sustainable form. Human curators maintain an accessible knowledge base; automated pipelines generate HDTO-compliant linked-data exports for long-term interoperability. For the HH pilot, we will therefore: 1. Use the existing, well-curated Finno-Ugric Wikibase instance to test small sample datasets. 2. Evaluate feasibility and governance requirements for establishing one or two dedicated Wikibase instances: – a public-facing authority and catalogue layer, – and, if necessary, a more detailed internal-facing instance for sensitive or partially processed data. 3. This staged approach mirrors the Welsh model, where the public Wikibase instance aggregates reconciled data, while institutions retain internal systems tailored to their operational needs. Subsidiarity in Data Governance: Proven Suitability for Minority, Regional, and Diasporic Heritage The suitability of Wikibase for complex cultural ecosystems is supported by comparative examples: – the National Library of Finland’s Wikibase pilot, – the Võro User Group’s regional-language knowledge base, – Wikimedia Norge’s Sámi metadata projects, – and other community-based knowledge initiatives. These projects demonstrate that Wikibase can combine semantic interoperability with knowledge sovereignty, a crucial requirement for representing the diverse, often community-generated folklore and folk-music heritage that HH oversees. 6 Figure 1: Figure 1: The opening page at https://reprexbase.eu/fu/index.php for the FinnoUgric Data Sharing Space Within the Finno-Ugric Data Sharing Space, this approach allows complex, multilingual, and historically layered heritage to be represented transparently and sustainably: human curators maintain an accessible knowledge base, while automated exports produce HDTOcompliant datasets for long-term interoperability. We will test this well-developed and curated Wikibase instance for the first phase of testing small data samples from HH, then we review the feasibility of building one or two dedciated (for example, public facing and separate internal facing) instances for HH. Alignment with European Research Infrastructures Reprex aligns the Wikibase data model with the Heritage Digital Twin Ontology(HDTO), the semantic backbone of the European Collaborative Cloud for Cultural Heritage (ECCCH). This alignment ensures that HH’s data will be future-proof, interoperable with European heritage clouds, and ready for integration into AI-assisted digital humanities tools. In this respect, Wikibase functions not merely as a curatorial interface, but as an enabling architecture for open, interoperable cultural-heritage data within the emerging European research and data-space ecosystem. Viability and competences Because Reprex works with very similar data from the Latvian Folk Archive, and various smaller Nordic and Baltic collections, and Hungarian and Slovak repertoire data, we are importing into the current datasets a small subset of Folk Tales Inventory [Népmeseleltár], in 7 short: FTI Example Dataset, and the A Székelyföld népi tánczene szempontú táji tagolódása – 500 hangzó példa, in short, Szekler dance music dataset created by Pávai, István to demonstrate on a small scale the value, usability and problems of the broader collections of HH. These datasets, as much as it is possible, will be converted and added to the Finno-Ugric Data Sharing Space (FUDSS), a non-profit, research data sharing space that connects various Finno-Ugric immaterial and material culture in formats that are interoperable with libraries, archives, museums, Europeana, Daria-H, and the European Culture Heritage Cloud. FUDSS only stores metadata and does not take away any published HH material; it will link back to the Szekler dance music dataset. It will expose a small subset, probably ~50 tales with connected bibliographical entries from FTI Example Dataset, which is less than 0.5% of the contents of the original data source. The aim of this direction is: • to evaluate to what extent the current data models developed by Reprex with the Latvian Folk Archive and other similar organisations can be directly applicable to HH; • to gain hands-on graph building, reviewing, editing experience to the HH team; • to expose various professional questions in the entire data curation workflow (technical, semantic, scalability or legal) At the same time, HH colleagues will write competency questions to the expected graph, which we hope to be able to answer by querying the FUDSS in SPARQL. The competency questions should be organised like this. A Székelyföld népi tánczene szempontú táji tagolódása – 500 hangzó példa Competences expected from importing to the FUDSS graph: • Which example items were in use in Gyergyóremete? • Which example items were collected by Pávai, István? • What musical instruments appear in Pávai’s examples? • Which instrumental ensembles appear among Pávai’s examples? • In which example does a clarinet appear? • In which folk region is the dance called korcsos found? • What cultural micro-regions belong to the Marosszék cultural (meso)region? • From which Bartók collections (location and date of collection) did István Pávai select his examples? After enriching the graph with Linked Open Data: 8 • Which collector worked in Remetea [with the addition of multi-language gazetteer], for methodology see Remapping the Livonian Coast: A Multilingual Gazetteer of the Settlements of Northern Kurzeme (Antal, Pigozne, and Mester 2025). • Which example items were collected within 25 kms from 46°15'8.96"N, 25°26'5.86"E. We enriched Abásfalva-Aldea with geographical coordianates and Geonames PID (686517); a simple distance function can be built in a query that answers this question and lists other collection locations that fall into the radius. • Which publications of the collector Agócs, Gergely are available in OSZK and other libraries? • Which settlements in the collection have a proportion of Hungarian population below 50% according to the 2021 Romanian census? After feasibility accomplished: • Which publications of the collector Bartók, Béla are available in library of HH • Which original audio tapes on inventory are connected to the collector Pávai, István • Which collection can be listened to in its entirety in the Folklore Database (Folklóradatbázis)? • Which original media can be listened to in its entirety in the ZTI Sound Archive? Folk Tales Inventory [Népmeseleltár] We placed about 120 folk tales from Transylvania into our database. These entries are not the abstract tales, but their textual manifestations as they were described in Konsza, Samu: Háromszéki magyar népköltészet [Folk Poetry of Háromszék] and made available originally by the State Publishing House for Literature and Arts / Állami Irodalmi és Művészeti Kiadó, and currently by Adatbank (fudss:Q5823)]. We used the following modelling solutions: 1. We placed Competences expected from importing to the FUDSS graph: • Which tales were published in Magyar Nyelvőr in the year 1888? • Which tales were collected in Mohács? • Which tales were collected by Ortutay, Gyula? After enriching the graph with Linked Open Data: • Which collector worked in ����������� [requires addition of multi-language gazetteer] • Which example items were collected within 25 kms from 48°16’36”N, 22°48’28”E • Which publications of the collector [Ortutay, Gyula] are available in OSZK? • What did Samu Konsza look like? 9 Even these “simple” cases are dynamic. A copyright protection term may expire, making a less accessible item fully reusable under the public domain. Rightsholders may change their minds, and give a more permissive license, for example, change from CC BY-NC-ND to CC-BY-SA, allowing commercial use and derivate works. Type of object HDTO class Typical examples Digital text hdt:HC6_DigitalDocumentmetadata exports, lyrics, PDFs Digital image hdt:HC7_DigitalVisualObjectphotographs, scans, blueprints Simple audio file hdt:HC5_DigitalRepresentationsingle, unambiguous recordings Each digital component carries: -use rights → a URI pointing to a standard licence (e.g. CC-BY, CC0); - optional provenance (dcterms:rightsHolder,dcterms:accessRights,dcterms:provenance). The composite digital twin (HC2) aggregates multiple components but does not override their licences. When reused, the most restrictive licence among components applies. Wikibase Rights Extensions To align HDTO, EDM, and Wikibase, FinFAIR defines two complementary properties and one supporting class. 16 ĺImportant All examples below will be changed this week to HH examples for discussion. Property: use rights (wd:P486) Field Description Label use rights Description Links a digital object to a URI identifying the applicable licence or rights statement (e.g. rightsstatements.org, Creative Commons). Aliases licence; rights; edm:rights; dcmi:license; datacite:rights Datatype External identifier (URI) Equivalent properties dcterms:license,edm:rights,datacite:rights Full definition https://reprexbase.eu/fu/Special: EntityData/P486.ttl Example: •Dēliņi homestead detail: combined barn-shed (detail photo) use rights:https://creativecommons.org/licenses/by-sa/4.0/deed.en •The Livonian Community House in Mazirbe (photograph) use rights:https://creativecommons.org/licenses/by/4.0/deed.en This property provides one-to-one interoperability with both Europeana and research repositories using DataCite Property: use policy (wd:P487) Field Description Label use policy Description Links a digital object to a local rights or usage policy item within the same Wikibase instance (e.g. “Listen on Spotify”). Used when the applicable terms are described internally rather than via an external URI. Aliases has policy; user rights policy Datatype Wikibase item (Near) Equivalent class odrl:Policy Full definition https://reprexbase.eu/fu/Special: EntityData/P487.ttl 17 Class: use policy (wd:Q5606) Field Description Label use policy Description A simplified representation of odrl:Policy within Wikibase. Describes how a digital object may be accessed, used, or shared under specific conditions. Instances act as human-readable policy nodes. Full definition https://reprexbase.eu/fu/Special: EntityData/Q5606.ttl Example instance of this class: Q5608 – Listen on Spotify You may listen to this recording via the Spotify web or mobile player, either for free or with a subscription, under Spotify’s End-User Licence. This simplified approach to ODRL was first introduced in our WikidataCon 2025 presentation, where we demonstrated how Wikibase can represent policy semantics (“play”, “reproduce”, “not download”) without external RDF frameworks. Complex Case: Composite Rights Multimodal cultural objects, such as sound recordings, often involve overlapping rights: composer, lyricist, performer, producer, and distributor. In such cases, each digital representation (HC5) carries its own use rights and use policy. 18 This example is taken from Wikibase as a Data Sharing Space: Connecting Rights, Communities, and GLAM through Federated Infrastructures (Antal 2025). Example: Tšitšōrlinki, tšitšōrlinki •Archival recording — accessible under CC-BY-NC, for non-commercial research. use policy: “Non-commercial analysis and reproduction permitted.” •Spotify release — available for streaming only under Spotify’s end-user licence. use policy: “Listen on Spotify.” These are linked within a single digital twin (HC2), which aggregates but does not merge or override rights. 19 Aggregators such as Europeana can display the most restrictive licence, while research or educational users can act according to the specified use policy. Summary 1. GDPR compliance — screen linked agents, pseudonymise or anonymise where required. 2. Simple case — one use rights URI per file, equivalent to edm:rights. 3. Composite case — multiple components, each with its own use rights and use policy. 4. Interoperability — full equivalence with EDM, DCTERMS, and ODRL. 5. Scalability — lightweight for images and texts, yet expressive for music and audiovisual works. This model provides a sustainable bridge between cultural heritage and research data ecosystems, ensuring that digital twins can circulate legally and ethically within the European Collaborative Cloud for Cultural Heritage. References Antal, Daniel. 2025. “Wikibase as a Data Sharing Space: Connecting Rights, Communities, and GLAM Through Federated Infrastructures. Presentation on Wikidata Conf 2025.” Open Music Observatory. https://doi.org/10.5281/zenodo.17496740. 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