Giacomo NannipersName, Linda FreybergpersName, Sabine de GüntherpersName, Marian DörkpersName (2023date). ““The research is happening in the text fields” – Are Linked Open Data and Art History a good match?.” Digital Humanities 2023 (DH2023), Graztitle·a, GrazplaceName.
Object of study — Where the boundary falls between what an art-historical research project can express as Linked Open Dataterm·dom and what it must leave as prose.
Research question — Structured vocabulariesterm·key buy accuracy and queryability - so what is lost when the reflexive, contextual part of humanities research is forced into them?
Contribution — Argues that only the quantitative, queryable part of art-historical research is worth modelling as triples, and bridges the rest to it through visual interfaces rather than forcing it into ontologiesterm·mth.
phenomenon · claim-type · cross-domain-transfer · mechanism · claim-relation · replication-status · limitation — grounded in the full text| phenomenon | linked open data modelling in art history — “A recurring question is: What should be modeled as linked open data (LOD) and what should be entered as free-form text?” | |
| claim-type | critique — “In terms of representing the research process it is not worth making this part machine -readable as a basis for formal queries.” | |
| method — evidence | — “We use Art History research, in particular, the project “Restaging Fashion - Digital contextualization of vestimentary sources” (Refa), as one example to show how emerging discourses within the research process can be mapped in a knowledge organization system and which aspects may not be formally represented.” | |
| object of study — evidence | — “A recurring question is: What should be modeled as linked open data (LOD) and what should be entered as free-form text?” | |
| research question — evidence | — “Despite the proven utility of data standards, vocabularies, and authority files providing for accuracy, context, and unambiguity, there is also a need for an open space to formulate and present tentative observations.” | |
| contribution — evidence | — “With this contribution we present how we bridge LOD and full text descriptions through information visualization.” | |
| transfer | from semantic web and information science: Linked Data, reference ontologies and authority files, applied to art-historical research and found to fit only part of it — “In Digital Humanities (DH) research this process and its specific structure has to be represented on a data level.” | transfers[0] |
| mechanism | an ontology can never close: no cultural artefact is finally contextualisable, and the vocabularies are uneven across subtopics — “Complex ontologies will never be completely exhaustive since no cultural artifact or experience could be fully and finally contextualized and vocabularies are not equally accurate and detailed for every subtopic.” | mechanisms[0] |
| mechanism | the target moves: meanings shift over the life of the project doing the modelling — “In addition, contexts and meanings shift over time, even during the timeframe of a research project.” | mechanisms[1] |
| mechanism | the cost of manual tagging is what forces institutions to publish shallow metadata, which then constrains what anyone can ask of the data — “This leads institutions to publish only a subset of the available information, exposing minimal metadata (Doerr et al. 2010), which might prevent researchers from using the data and constrains them to conventional research methods.” | mechanisms[2] |
| mechanism | deep modelling is not durable either - the British Museum modelled its whole collection in CIDOC CRM and then could not keep it accessible — “The British Museum, on the other hand, structured its entire collection using CIDOC CRM, but was unable to preserve its database in a consistent and accessible manner (Lincoln, 2015).” | mechanisms[3] |
| builds-on | Galloway (2011: 91) on the unrepresentable — “According to Galloway "there are some things that are unrepresentable. And the computer is our guide into that realm" (2011: 91).” | claim_relations[0] |
| builds-on | Daquino et al. (2022) on institutional uptake of LOD-native systems — “Since 2006, when the term Linked Data was coined (see Berners-Lee 2006), according to Daquinoet al."only a few pioneers have abandoned legacy cataloguing and archiving systems to fully embrace the Semantic Web paradigm and manage their catalogues through LOD-native management systems" (2022).” | claim_relations[1] |
| builds-on | Berners-Lee (2006) on Linked Data — “The potential of these applications is obvious: LOD allows data to be reused and redistributed, revealing relationships with other data on the Web (Berners-Lee 2006).” | claim_relations[2] |
| contradicts | the programme of modelling cultural heritage research exhaustively in formal ontologies — “In terms of representing the research process it is not worth making this part machine -readable as a basis for formal queries.” | claim_relations[3] |
| sense | representation - as machine-readable structure, whose point is that a formal query can be run over it — “In terms of representing the research process it is not worth making this part machine -readable as a basis for formal queries.” | senses[0] |
| sense | representation - as something another researcher can read and understand, which the paper argues needs no formalisation at all — “It is more important to present it in a way that is accessible and understandable to other researchers, which does not require this high level of formalization, because it would end up in overcomplicated queries.” | senses[1] |
| sense | the unrepresentable - material the paper holds cannot be captured by either, quoting Galloway — “According to Galloway "there are some things that are unrepresentable. And the computer is our guide into that realm" (2011: 91).” | senses[2] |
| differs in | the programme of modelling cultural heritage research exhaustively in formal ontologies — THE AXIS IS WHICH PART OF THE WORK IS BEING MODELLED. 'IN TERMS OF REPRESENTING THE RESEARCH PROCESS IT IS NOT WORTH MAKING THIS PART MACHINE-READABLE as a basis for formal queries.' The exhaustive-formalisation programme is contradicted for ONE COMPONENT and left standing for the rest - which is exactly the qualification a bare 'contradicts' deletes. — “In terms of representing the research process it is not worth making this part machine -readable as a basis for formal queries.” — “In terms of representing the research process it is not worth making this part machine” | claim_relations[3] |
| audit | Linked Open Data —contrasted-with→ free-form text — Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but the span poses the choice between LOD and free-form text as a question; contrasted-with is loose. — “A recurring question is: What should be modeled as linked open data (LOD) and what should be entered as free-form text?” | concept_edges[0] |
| edge | CIDOC CRM —is-a→ ontologies — “Sophisticated ontologies like CIDOC CRM encourage the detailed description of an object through an event-driven structure, which makes it a very powerful tool for the cultural heritage sector by providing for the possibility of adding meaning to the original data.” | concept_edges[1] |
| for which use | limitation — the generality of the argument: it is illustrated by the Restaging Fashion project rather than tested across cases — “As part of the Restaging Fashion project, we devised different experimental prototypes, linked specific parts of the textual description to artworks, to classification entries, to archival sources as well as to other cultural heritage objects” | limitations[0] |
| for which use | limitation — the proposed boundary itself: QUANTITATIVE INFORMATION ... WHICH CAN BE QUERIED AND EXPRESSED STATISTICALLY, ARE WORTH TO BE MODELED IN TRIPLE STRUCTURES - asserted, not operationalised — “In particular quantitative information, for instance, on objects and their relations, which can be queried and expressed statistically, are worth to be modeled in triple structures.” | limitations[1] |
| replication | untested | |
| limitation | One project, one discipline: the argument is illustrated by Restaging Fashion rather than tested across cases. — “As part of the Restaging Fashion project, we devised different experimental prototypes, linked specific parts of the textual description to artworks, to classification entries, to archival sources as well as to other cultural heritage objects” | limitations[0] |
| limitation | The boundary it proposes - quantitative to triples, reflexive to interfaces - is asserted rather than operationalised; nothing says where a given sentence falls. — “In particular quantitative information, for instance, on objects and their relations, which can be queried and expressed statistically, are worth to be modeled in triple structures.” | limitations[1] |
finding · quantity · variable · definition · key-term — grounded in the full text| finding | The central question of the paper is a boundary question: what becomes structured data and what stays prose. — “A recurring question is: What should be modeled as linked open data (LOD) and what should be entered as free-form text?” | content_tags.findings[0] |
| finding | Standards buy accuracy and unambiguity, but research also needs room for observations that are not yet settled. — “Despite the proven utility of data standards, vocabularies, and authority files providing for accuracy, context, and unambiguity, there is also a need for an open space to formulate and present tentative observations.” | content_tags.findings[1] |
| finding | Modelling a collection early forces a trade-off between standardisation and semantic accuracy. — “Semantic data modeling of a collection during an early stage of the research prompts a trade-off to be made between data standardization and semantic accuracy.” | content_tags.findings[2] |
| finding | Even major museums publishing LOD share only shallow models of their objects. — “it appears that these museums only share relatively shallow data models for their artworks on the web” | content_tags.findings[3] |
| finding | The British Museum structured its whole collection in CIDOC CRM but could not keep the database consistent and accessible. — “The British Museum, on the other hand, structured its entire collection using CIDOC CRM, but was unable to preserve its database in a consistent and accessible manner (Lincoln, 2015).” | content_tags.findings[4] |
| finding | Manual tagging is precise but does not scale, and automatic tagging fails on inconsistent data - so neither route reaches existing collections. — “Manual tagging can be performed by domain experts in a very precise manner, but it cannot be performed manually to large volumes of already existing content due to the lack of resources (Simou et al. 2017) or may not be conducted automatically due to inconsistencies and/or the lack of standardization in the datasets.” | content_tags.findings[5] |
| finding | More elaborated, reflexive or contextualized information may need other forms of representation, such as visual interfaces. — “Other, more elaborated, reflexive, or contextualized information may require different forms of representations like visual interfaces.” | content_tags.findings[6] |
| finding | Free text is treated as the starting point for semantic contextualisation rather than as a residue to be tidied away. — “Instead of hiding the full text in unstructured note fields, we approach this as a starting point for the semantic contextualization of the research process.” | content_tags.findings[7] |
| definition | reference models — “reference models like CIDOC CRM (2022) offer a precise structural vocabulary to describe cultural heritage objects and their relations” | content_tags.definitions[0] |
| definition | CIDOC CRM — “Sophisticated ontologies like CIDOC CRM encourage the detailed description of an object through an event-driven structure, which makes it a very powerful tool for the cultural heritage sector by providing for the possibility of adding meaning to the original data.” | content_tags.definitions[2] |
| definition | LOD — “The potential of these applications is obvious: LOD allows data to be reused and redistributed, revealing relationships with other data on the Web (Berners-Lee 2006).” | content_tags.definitions[3] |
| definition | unrepresentable — “According to Galloway "there are some things that are unrepresentable. And the computer is our guide into that realm" (2011: 91).” | content_tags.definitions[4] |
| key-terms | Linked Open Data, CIDOC CRM, authority files, controlled vocabulary, semantic accuracy, free text, free-form text, information visualization, ontologies, vocabularies, semantic data modeling, metadata, cultural heritage, triple structures |
| concept | linked open data — “The potential of these applications is obvious: LOD allows data to be reused and redistributed, revealing relationships with other data on the Web (Berners-Lee 2006).” | concepts[0] |
| concept | CIDOC CRM — “Sophisticated ontologies like CIDOC CRM encourage the detailed description of an object through an event-driven structure, which makes it a very powerful tool for the cultural heritage sector by providing for the possibility of adding meaning to the original data.” | concepts[1] |
| concept | free-form text — not defined in this paper's own words; the unformalised prose in which tentative observations and contextual argument are written - the other half of the trade-off — “A recurring question is: What should be modeled as linked open data (LOD) and what should be entered as free-form text?” | concepts[5] |
| concept | information visualization — not defined in this paper's own words; the proposed bridge: an interface that links parts of the prose to the objects, classifications and sources they discuss — “With this contribution we present how we bridge LOD and full text descriptions through information visualization.” | concepts[6] |
| concept | ontologies — not defined in this paper's own words; formal structures of classes and relations, held here to be necessarily incomplete for cultural material — “Complex ontologies will never be completely exhaustive since no cultural artifact or experience could be fully and finally contextualized and vocabularies are not equally accurate and detailed for every subtopic.” | concepts[7] |
| concept | metadata — not defined in this paper's own words; what institutions actually publish - a shallow subset, because deeper description costs more than they have — “This leads institutions to publish only a subset of the available information, exposing minimal metadata (Doerr et al. 2010), which might prevent researchers from using the data and constrains them to conventional research methods.” | concepts[8] |
| concept | triple structures — not defined in this paper's own words; the representation the paper reserves for quantitative, queryable relations between objects — “In particular quantitative information, for instance, on objects and their relations, which can be queried and expressed statistically, are worth to be modeled in triple structures.” | concepts[9] |
| claim type | critique — a second reading reaching the same value; recorded: critique — “In terms of representing the research process it is not worth making this part machine -readable as a basis for formal queries.” | alternatives.claim_type |
| method | conceptual-analysis — a second reading DIFFERING from the recorded value; recorded: practice-report — “We use Art History research, in particular, the project “Restaging Fashion - Digital contextualization of vestimentary sources” (Refa), as one example to show how emerging discourses within the research process can be mapped in a knowledge organization system and which aspects may not be formally represented.” | alternatives.method |
| phenomenon | the trade-off between semantic formalisation and the expressiveness of humanities research writing — a second reading DIFFERING from the recorded value; recorded: linked open data modelling in art history — “Semantic data modeling of a collection during an early stage of the research prompts a trade-off to be made between data standardization and semantic accuracy.” | alternatives.phenomenon |
Full text — tagged
The reference list is not part of the text we hold for this paper. Our copy was extracted from the publisher's page and the bibliography did not survive that extraction, so the article below ends before its references. Nothing has been removed by us.
Introduction The scientific discourse in object-focused and historical disciplines follows certain methods and builds a narration with objects, events, evidence and conclusions.
In Digital Humanities (DH) research this process and its specific structure has to be represented on a data level. Linked Open Dataterm·dom, Semantic Web ontologiesterm·mth and, in particular, reference modelsterm·def like CIDOC CRMterm·dom (2022) offer a precise structural vocabulary to describe cultural heritageterm·key objects and their relations. These frameworks can support GLAM institutions to make the data on their objects findable, accessible and interoperable.
However, in research projects the course of developing arguments and describing findings is crucial. We use Art History research, in particular, the project “Restaging Fashion - Digital contextualization of vestimentary sources” (Refa), as one example to show how emerging discourses within the research process can be mapped in a knowledge organization systemterm·dom and which aspects may not be formally represented. A recurring question is: What should be modeled as linked open dataterm·dom (LODterm·def) and what should be entered as free-form textterm·mth? Despite the proven utility of data standards, vocabulariesterm·key, and authority filesterm·key providing for accuracy, context, and unambiguity, there is also a need for an open space to formulate and present tentative observations. With this contribution we present how we bridge LODterm·def and full text descriptions through information visualizationterm·mth.
Semantic data modelingterm·key in Museums Semantic data modelingterm·key of a collection during an early stage of the research prompts a trade-off to be made between data standardization and semantic accuracyterm·key.Sophisticated ontologiesterm·mth like CIDOC CRMterm·dom encourage the detailed description of an object through an event-driven structure, which makes it a very powerful tool for the cultural heritageterm·key sector by providing for the possibility of adding meaning to the original data.
Since 2006, when the term Linked Data was coined (see Berners-Lee 2006), according to Daquinoet al."only a few pioneers have abandoned legacy cataloguing and archiving systems to fully embrace the Semantic Web paradigm and manage their catalogues through LOD-native management systems" (2022).
When considering the LODterm·def datasets published by The British Museum and the Rijksmuseum, who also create tools such as ResearchSpace (Oldman / Tanase 2018) and dedicated platforms to engage with their collections, it appears that these museums only share relatively shallow data models for their artworks on the web. The Rijksmuseum provides basic metadataterm·mth on objects structured in DC , EDM and LIDO schemas. Only one example is modeled deeply: Linked Art van Gogh object metadataterm·mth download . But the creators clearly state that: “both the implementation of the model as well as the use of identifiers will be subject to change” (RijksData 2022). The British Museum, on the other hand, structured its entire collection using CIDOC CRMterm·dom, but was unable to preserve its database in a consistent and accessible manner (Lincoln, 2015). Data that should be linked together is no longer accessible, making the research of scholars no longer available ( see Programminghistorian 2017).
The potential of these applications is obvious: LODterm·def allows data to be reused and redistributed, revealing relationships with other data on the Web (Berners-Lee 2006). The resources involved, however, are somewhat excessive both from a technological perspective (see De Decker 2015)and regarding the cataloging of information. Manual tagging can be performed by domain experts in a very precise manner, but it cannot be performed manually to large volumes of already existing content due to the lack of resources (Simou et al. 2017) or may not be conducted automatically due to inconsistencies and/or the lack of standardization in the datasets. This leads institutions to publish only a subset of the available information, exposing minimal metadataterm·mth (Doerr et al. 2010), which might prevent researchers from using the data and constrains them to conventional research methods.
Data-driven art historical discourse Art historical research on and with collections is deeply concerned with the history of objects and their discourse such as provenance history, history of interpretation, dating or attribution based on comparable works. This can be expressed with the event structure of CIDOC CRMterm·dom including descriptive information on the objects like dimensions, inscriptions, and alternative titles also linked to relevant vocabulariesterm·key like ICONCLASS and AAT . But a crucial part of humanities research consists of annotating that basic formal information, by elaborating and contextualizing the history of the artworks and their interpretation, often concluding in the form of a paper or monograph. Undertaking this part of research in the form of LODterm·def is very intricate and laborious. Complex ontologiesterm·mth will never be completely exhaustive since no cultural artifact or experience could be fully and finally contextualized and vocabulariesterm·key are not equally accurate and detailed for every subtopic. In addition, contexts and meanings shift over time, even during the timeframe of a research project. According to Galloway "there are some things that are unrepresentableterm·def. And the computer is our guide into that realm" (2011: 91). In terms of representing the research process it is not worth making this part machine -readable as a basis for formal queries. It is more important to present it in a way that is accessible and understandable to other researchers, which does not require this high level of formalization, because it would end up in overcomplicated queries.
Visualizing context One way to equally accommodate formal LODterm·def structures as well as full text descriptions is through custom interfaces. In particular, information visualizationterm·mth can be used for the contextualization of images, sources, texts and their relations.
Fig. 1: Draft of Refa interface As part of the Restaging Fashion project, we devised different experimental prototypes, linked specific parts of the textual description to artworks, to classification entries, to archival sources as well as to other cultural heritageterm·key objects (see Fig. 1.) with the aim to establish an overview of the context.
Instead of hiding the full text in unstructured note fields, we approach this as a starting point for the semantic contextualization of the research process.
In conclusion, certain aspects of humanities research can be properly expressed by semantic web structures. In particular quantitative information, for instance, on objects and their relations, which can be queried and expressed statistically, are worth to be modeled in triple structuresterm·mth. Other, more elaborated, reflexive, or contextualized information may require different forms of representations like visual interfaces.
CIDOC Conceptual Reference Modelterm·def Galleries, Libraries, Archives and Museums Dublin Core Europeana Data Model Lightweight Information Describing Objects https://iconclass.org/ https://www.getty.edu/research/tools/vocabulariesterm·key/aat/