Knowledge Organization Systems Research Articles

Assessing knowledge organization systems from a gender perspective: Wikipedia taxonomy and Wikidata ontologies

PurposeDevelop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.Design/methodology/approachThis study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.FindingsThis study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.Originality/valueThe assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.

Improving the interoperability of drugs terminologies: Infusing local standardization with an international perspective

Objectives:The objective of this study is to describe how OCRx (Canadian Drug Ontology) has been built to address the dual need for local drug information integration in Canada and alignment with international standards requirements. Methods:This paper delves into (i) the implementation efforts to meet the Identification of Medicinal Product (IDMP) requirements in OCRx, alongside the ontology update strategy, (ii) the structure of the ontology itself, (iii) the alignment approach with several reference Knowledge Organization Systems, including SNOMED CT, RxNorm, and the list of “Code Identifiant de Spécialité” (CIS-Code), and (iv) the look-up services developed to facilitate its access and utilization. Results:Each OCRx release contains two distinct versions: the full and the up-to-date version. The full version encompasses all drugs with a DIN code sanctioned by Health Canada, while the up-to-date version is limited to drugs currently marketed in Canada. In the last release of OCRx, the full version comprises 162,400 classes; meanwhile, the up-to-date version consists of 36,909 classes. In terms of mappings with OCRx, substances in RxNorm and SNOMED CT fall below 40%, registering at 37% and 22% respectively. Meanwhile, mappings for CIS-Code achieve coverage of 61%. The strength mappings are notably low for RxNorm at 40% and for CIS-code at 28%. This affects the mapping of clinical drugs, which are predominantly alignable through post-coordinated expressions: 56% for RxNorm, 80% for SNOMED CT, and 35% for CIS-Code. The main support service of OCRx is a look-up service known as PaperRx that displays OCRx’s entities based on description logic queries (DL-queries) performed through the classified structure of OCRx. The look-up services also contain a SPARQL endpoint, an OCRx OWL file downloader, and a RESTful API. Discussion:The OCRx ontology demonstrates a significant effort towards integrating Canadian drug information with international standards. However, there are areas for improvement. In the future, our focus will be on refining the structure of OCRx for better classification capability and improvement of dosage conversion. Additionally, we aim to harness OCRx in constructing an ontology-based annotator, setting our sights on its deployment in real-world data integration scenarios.

Prejudice but no pride: The Portuguese Universal Decimal Classification’s labelling of sexual orientation

Critical cataloguing aims to study cases of social injustice, misrepresentation, negative biases, offensive terminologies, and hegemonic and oppressive hierarchical structures in the representation of communities and identities in knowledge organization systems. The aim of this study is to provide a critical analysis of the representation of sexual orientation in the Portuguese Universal Decimal Classification, grounded in a qualitative content analysis method. The results show that the principle of exhaustiveness does not manifest itself in the representation of sexual orientation. The absence of the term ‘heterosexuality’ mirrors the heteronormative hegemony, while the minoritization of ‘lesbianism’, but not of ‘male homosexuality’, reflects the patriarchal hegemony. The representation of sexual orientation carries the historical pathologization of sexual orientations other than heterosexuality. The Portuguese Universal Decimal Classification conveys negative biases and misrepresents sexual orientation in a way that is irreconcilable with present-day reality. Critical thinking must be encouraged within the library community and the Universal Decimal Classification should be promptly revised and updated.

Domain Analysis Versus Facet Analysis

This paper delves into the complexities and theoretical underpinnings of knowl­edge organization systems (KOS), focusing on domain analysis and facet analysis as methodologies, such as improving the Library of Congress Subject Headings (LCSH). The study repeats a former critique of the LCSH and argues for the incorporation of facet and domain analysis to enhance its utility and academic rigor. Facet analysis, although well-established, is critiqued for its rationalist philosophy and lack of empirical grounding. Domain analysis is presented as a complementary approach that addresses these gaps by considering empirical, historical, philosophical, and pragmatic issues. To any given system, the paper emphasizes that KO systems are not neutral; they reflect underlying theoretical paradigms that must be understood for effective classification. The study concludes by advocating for interdisciplinary research and broader cooperation among knowl­edge organization professionals, philosophers, and subject specialists to develop more robust and academically rigorous KOS.

Library Catalog’s Search Interface: Making the Most of Subject Metadata

This article addresses the underutilization of knowl­edge organization systems (KOS) elements in online library catalogs, hindering effective subject-based search and discovery. It highlights the International Society for Knowl­edge Organization's initiative to develop metadata guidelines for library catalog procurement, focusing on maximizing the value of subject metadata from classification systems and controlled vocabularies. The paper discusses the rationale for quality subject access, proposes desirable search functionalities based on research, explores implementation challenges, and outlines future developments. The conclusion emphasizes the importance of providing quality subject access in digital services and calls for further research on interface design, guideline adoption, KOS evolution, and the impact of language models on subject metadata use. The work underscores the need for applying controlled vocabularies in search interfaces across libraries, archives, and museums while acknowledging the complementary role of alternative approaches like social tagging and automatic indexing. Extensive future research is suggested to implement search functionalities, promote guidelines adoption, enhance KOS evolution, and assess the influence of language models on subject metadata utilization.

The fault in our TARs: A critical review of research paradigms for intermediate‐scale bedforms on Mars

AbstractWe provide a critical review of research paradigms for classifying intermediate‐scale aeolian bedforms on Mars and the new terminology that has emerged. The systematic classification of bedforms has always been challenging and debated, and no paradigmatic knowledge organization system exists beyond general agreement on the importance of a distinction between ripples and dunes. The diverse aeolian landscapes of Mars have introduced further topics and challenges to these debates. We argue that Martian aeolian geomorphology's knowledge organization system for intermediate‐scale bedforms is preparadigmatic and that consensus over terminology and their definitions has not been established in the literature. A preparadigmatic science can be functional only if scientists operating in the discipline provide precise, falsifiable definitions or use abductive logic. Drawing on evidence and examples from the literature, we argue that the replacement of the conventional abductive paradigm used in bedform classification with inductive logic has created an emerging disciplinary paradigm based on scientific hesitancy and a dependence on complex inductive research structures, epitomized by the concepts of ‘transverse aeolian ridges’ (TARs) and ‘large Martian ripples’ (LMRs). We show that TAR and, increasingly, LMR are inductive constructs that have been popularized despite them causing significant confusion. Notably, we highlight how the terms are irreconcilably used as both a class of bedform and as a non‐genetic placeholder term for bedforms. Suggestions for moving beyond the need for TAR and LMR are provided, focusing on a return to more direct and local hypothesis‐driven research inspired by W.M. Davis's notion of outrageous geological hypotheses. Recent debate surrounding bedforms in Gale crater is presented as an example of the productivity of such an approach, and it is recommended that TAR and LMR no longer be used.

Research on prediction model of scaling in ASP flooding based on data mining

As a result of alkali ASP flooding in oil and gas fields, strata and pipelines become seriously scaled, which poses a threat to the normal operation of crude oil production. We propose an intelligent knowledge reasoning model for dynamic scaling prediction in order to address the problems of high directivity, poor generalization ability, and poor application effect of existing scaling prediction methods. The model framework includes the knowledge acquisition layer which mainly relates to the manual acquisition of scaling prediction knowledge and the intelligent training of the knowledge base, and it includes the knowledge modeling layer that provides a set of standard domain common ontology and knowledge organization system using the ontology modeling technology, it also includes the knowledge inference layer which is the application layer of the model. The three layers collaborate and finally complete the scaling prediction through inference and expression. A total of 238 wells were selected for experimentation in the northern development area of the Xingshugang Oilfield. Experimental results indicate that the model has the highest accuracy of 91.87%. Additionally, the time series prediction trend for the six ions matches the trend of change in ion concentration in the scaling state, verifying the accuracy of the model’s predictions.

Guest editorial: Knowledge organization systems are an enduring method for information access and control

Guest editorial: Knowledge organization systems are an enduring method for information access and control

Arabian Gulf Academic Libraries’ Knowledge Representation Practices, Perspectives and Barriers

Knowledge representation through metadata is crucial to successful knowledge management and ensuring access. Libraries, especially those associated with universities and colleges, have been long engaged in important activities of developing, adapting, implementing, and managing descriptive and administrative metadata, bibliographic authority control, etc. A substantial amount of research exists in knowledge representation practices of libraries that operate in North America and Western Europe. However, some other regions of the world, in particular the Arabian Gulf region which includes Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates, are currently underrepresented in this research. The exploratory project presented in this paper aimed to address this gap with the goal of developing an understanding of the current state of knowledge representation (including descriptive metadata practices, identity management, use of knowledge organisation systems, and more) in academic libraries of Kuwait, Oman, and Qatar, as well as plans and preparedness of these institutions and their staff for future developments in this area to facilitate discovery of resources, specifically in the aggregated digital environment. The qualitative study used semi-structured interviews of metadata managers at a representative sample of regional university libraries. The findings provide insights into this previously under-researched area and contribute to understanding of related knowledge management barriers and perspectives on a global scale. Implications for practice and research are discussed.

Developing a Knowledge Organization System for Ethnic Groups in Lao PDR through Linked Open Data Techniques

ABSTRACT The objective of this study is to propose a knowledge organization system (KOS) for the ethnic groups of Laos by utilizing linked open data (LOD) to standardize the metadata. Data of 49 Laos ethnic groups and the techniques of Linked Open Data were used. Linked data of ethnic groups in Lao PDR from other external standardized data sources, including DBpedia and Wikidata, was found. The results indicate that there is limited an information on the ethnic groups of Laos in online databases. This study aims to link and improve data on Laos ethnic groups by utilizing ontology and reconciliation techniques to link incomplete or outdated data, as well as using OpenRefine and RDF extension to link the source database. Although the country has implemented policies to promote the national identity and the tourism economy, much of the related information remains inaccessible to the public as it is only available in official documents. The available information in the online database system would be compared to foreign languages like Vietnamese, Thai, etc., because these areas and ethnic groups were close to each other, and the languages were in the same family.

Aggregating distributed KOSs: enriching with meta information and linking to the multilingual KOS registry

PurposeThis study aims to collect distributed knowledge organization systems (KOSs) from various domains, enrich each with meta information and link them to the multilingual KOS registry, facilitating integrated search alongside KOSs from various languages and regions.Design/methodology/approachThis research involved collecting and organizing KOS information through three primary steps. The initial phase involved finding KOSs from Web search results, supplemented by the Korea ON-line E-Procurement System (KONEPS) and the National R&D Integrated Notification Service. After obtaining these KOSs, they were enriched by structuring contextual meta information using Basic Register of Thesauri, Ontologies and Classification (BARTOC) metadata elements and established dedicated media wiki pages for each. Finally, the KOSs were linked to the multilingual KOS registry, BARTOC, ensuring seamless integration with KOSs from various languages and regions and creating connections between each registry entry and its associated KOS wiki page.FindingsThe research findings revealed several insights, as follows: (1) importance of a stable source for collecting KOS: no national body currently oversees KOS registration, underscoring the need for a systematic approach to collect dispersed KOSs. For Korean KOSs (K-KOSs), KONEPS and National R&D Integrated Notification Service are effective data sources. (2) Importance of enhanced metadata: merely collecting KOSs were not enough. Enhanced metadata bridges access gaps and dedicated wiki pages aid user identification and understanding. (3) Observations from multilingual registry uploads: When adding KOSs to a multilingual registry, similarities were observed across languages and regions. Recognizing this, the K-KOSs were linked with their international counterparts, fostering potential global collaboration.Research limitations/implicationsDue to the absence of a dedicated KOS registry agency, the study might have missed KOSs from certain fields or potentially over-collected from others. Furthermore, this study primarily focused on K-KOSs and their integration into the BARTOC registry, which might influence the methods and perspectives on collecting and establishing links among analogous KOSs in the registry.Originality/valueThis research pursued a stable method to detect KOS development and revisions across various fields. To facilitate this, we used the integrated e-procurement and R&D notification system and added meta information to aid in the identification and understanding of KOSs, which includes media wiki pages. Furthermore, link information was provided between the BARTOC registry and the Korean KOS websites and media wiki pages.

MMLKG: Knowledge Graph for Mathematical Definitions, Statements and Proofs

Nowadays, Knowledge Graphs (KGs) are important and developing in different areas. However, there is a lack of genuinely interoperable datasets representing mathematics that allow for information exchange between datasets in the Web ecosystem. In this paper, we address this matter based on the Mizar Mathematical Library (MML), a collection of articles written in the Mizar language. MML includes definitions and theorems with proofs to which authors can easily refer from newly written Mizar articles. However, extracting information directly from Mizar scripts by external projects is not very straightforward. Therefore, we propose a new data storage and retrieval approach based on the Knowledge Organization System (KOS) model and the KG concept that provides a way to organize and access knowledge. We present Mizar Mathematical Library Knowledge Graph (MMLKG), a thesaurus for describing mathematical objects. MMLKG supports semantic interoperability and allows linking data from different sources, e.g., Wikidata. Moreover, it satisfies the FAIR data principles. The data is publicly available via a Cypher endpoint.

Enhancing health-care data integration via automated semantic mapping

PurposeThis paper aims to delve into the complexities of terminology mapping and annotation, particularly within the context of the COVID-19 pandemic. It underscores the criticality of harmonizing clinical knowledge organization systems (KOS) through a cohesive clinical knowledge representation approach. Central to the study is the pursuit of a novel method for integrating emerging COVID-19-specific vocabularies with existing systems, focusing on simplicity, adaptability and minimal human intervention.Design/methodology/approachA design science research (DSR) methodology is used to guide the development of a terminology mapping and annotation workflow. The KNIME data analytics platform is used to implement and test the mapping and annotation techniques, leveraging its powerful data processing and analytics capabilities. The study incorporates specific ontologies relevant to COVID-19, evaluates mapping accuracy and tests performance against a gold standard.FindingsThe study demonstrates the potential of the developed solution to map and annotate specific KOS efficiently. This method effectively addresses the limitations of previous approaches by providing a user-friendly interface and streamlined process that minimizes the need for human intervention. Additionally, the paper proposes a reusable workflow tool that can streamline the mapping process. It offers insights into semantic interoperability issues in health care as well as recommendations for work in this space.Originality/valueThe originality of this study lies in its use of the KNIME data analytics platform to address the unique challenges posed by the COVID-19 pandemic in terminology mapping and annotation. The novel workflow developed in this study addresses known challenges by combining mapping and annotation processes specifically for COVID-19-related vocabularies. The use of DSR methodology and relevant ontologies with the KNIME tool further contribute to the study’s originality, setting it apart from previous research in the terminology mapping and annotation field.

The British Geological Survey Rock Classification Scheme, its representation as linked data, and a comparison with some other lithology vocabularies

Controlled vocabularies are critical to constructing FAIR (findable, accessible, interoperable, re-useable) data. One of the most widely required, yet complex, vocabularies in earth science is for rock and sediment type, or ‘lithology’. Since 1999 the British Geological Survey has used its own Rock Classification Scheme in many of its workflows and products including the national digital geological map. This scheme pre-dates others that have been published, and is deeply embedded in BGS’ processes. By publishing this classification scheme now as a Simple Knowledge Organisation System (SKOS) machine-readable informal ontology, we make it available for ourselves and third parties to use in modern semantic applications, and we open the future possibility of using the tools SKOS provides to align our scheme with other published schemes. These include the IUGS-CGI Simple Lithology Scheme, the European Commission INSPIRE Lithology Code List, the Queensland Geological Survey Lithotype Scheme, the USGS Lithologic Classification of Geologic Map Units, and Mindat.org. The BGS lithology classification was initially based on four narrative reports that can be downloaded from the BGS website, although it has been added to subsequently. The classification is almost entirely mono-hierarchical in nature and includes 3454 currently valid concepts in a classification 11 levels deep. It includes igneous rocks and sediments, metamorphic rocks, sediments and sedimentary rocks, and superficial deposits including anthropogenic deposits. The SKOS informal ontology built on it is stored in a triplestore and the triples are updated nightly by extracting from a relational database where the ontology is maintained. Bulk downloads and version history are available on github. The RCS concepts themselves are used in other BGS linked data, namely the Lexicon of Named Rock Units and the linked data representation of the 1:625 000 scale geological map of the UK. Comparing the RCS with the other published lithology schemes, all are broadly similar but show characteristics that reveal the interests and requirements of the groups that developed them, in terms of their level of detail both overall and in constituent parts. It should be possible to align the RCS with the other classifications, and future work will focus on automated mechanisms to do this, and possibly on constructing a formal ontology for the RCS.

Extracting relations from texts using vector language models and a neural network classifier.

The article investigates the possibility of identifying the presence of SKOS (Simple Knowledge Organization System) relations between concepts represented by terms on the base of their vector representation in general natural language models. Several language models of the Word2Vec and GloVe families are considered, on the basis of which an artificial neural network (ANN) classifier of SKOS relations is formed. To train and test the efficiency of the classifier, datasets formed on the basis of the DBPedia and EuroVoc thesauri are used. The experiments performed have shown the high efficiency of the classifier trained using GloVe family models, while training it with use of Word2Vec models looks impossible in the bounds of considered ANN-based classifier architecture. Based on the results, a conclusion is made about the key role of taking into account the global context of the use of terms in the text for the possibility of identifying SKOS relations.

Knowledge Organisation Systems in the Humanities—Semantic Interoperability in Practice

ABSTRACTWe observe a growing universe of machine‐readable knowledge organisation systems (KOS) or even wider ‘semantic artifacts. We see at the same time, various attempts to bring semantic artifacts together via registries, catalogues and via cross‐walks among ontologies. This poster reflects how newest research on semantic interoperability informs current practice for research data repositories and registry service providers. We focus on the domain of humanities and cultural heritage, using different examples from Europe and the Netherlands: The European Archaeological Data Infrastructure Ariadne, services of the Dutch Cultural Heritage Network and two Data Stations (for Archaeology and for SSH) hosted at DANS‐KNAW. For those cases we report on current efforts to include ‘semantic artifacts’, together with opportunities and challenges. This poster is a practice report combined with an invitation to reflect about the context of semantic interoperability itself.

CHV.br: Exploratory study for the development of a consumer health vocabulary (CHV) supported by a network model for Brazilian Portuguese language

Successful consumer health vocabulary (CHV) models have been engineered and updated by using automatic term extraction techniques from online content. However, the relationship between terms has yet to be mapped. This study aims to describe a CHV model for the Brazilian Portuguese language that is supported by a complex network. The method was split up into three distinct stages: (1) collect and automatically extract terms from structured data sources on the web, such as Unified Medical Language System (UMLS) vocabularies and DBpedia; (2) construct a complex network; and (3) select the terms supported by clustering techniques. A model called CHV.br was developed and supported by a complex network structure which makes connections between the controlled vocabulary and consumer vocabulary and maps semantic relationships as categories, synonyms and related terms. CHV.br contains 146,956 terms, of which 31,439 are UMLS preferred terms and 83,279 are synonyms. The CHV.br is available and powered by Simple Knowledge Organization System and Resource Description Framework standards. The method used in this study showed to be valid for the selection of the candidate terms by connecting the terms from different reliable resources, in addition to expanding the number of terms and their semantic relationships. The content and structure of CHV.br could play a vital role in enhancing the development of consumer-oriented health applications.

No Pain No Gain: Standards mapping in Latimer Core development

Latimer Core (LtC) is a new proposed Biodiversity Information Standards (TDWG) data standard that supports the representation and discovery of natural science collections by structuring data about the groups of objects that those collections and their subcomponents encompass (Woodburn et al. 2022). It is designed to be applicable to a range of use cases that include high level collection registries, rich textual narratives and semantic networks of collections, as well as more granular, quantitative breakdowns of collections to aid collection discovery and digitisation planning. As a standard that is (in this first version) focused on natural science collections, LtC has significant intersections with existing data standards and models (Fig. 1) that represent individual natural science objects and occurrences and their associated data (e.g., Darwin Core (DwC), Access to Biological Collection Data (ABCD), Conceptual Reference Model of the International Committee on Documentation (CIDOC-CRM)). LtC’s scope also overlaps with standards for more generic concepts like metadata, organisations, people and activities (i.e., Dublin Core, World Wide Web Consortium (W3C) ORG Ontology and PROV Ontology, Schema.org). LtC represents just an element of this extended network of data standards for the natural sciences and related concepts. Mapping between LtC and intersecting standards is therefore crucial for avoiding duplication of effort in the standard development process, and ensuring that data stored using the different standards are as interoperable as possible in alignment with FAIR (Findable, Accessible, Interoperable, Reusable) principles. In particular, it is vital to make robust associations between records representing groups of objects in LtC and records (where available) that represent the objects within those groups. During LtC development, efforts were made to identify and align with relevant standards and vocabularies, and adopt existing terms from them where possible. During expert review, a more structured approach was proposed and implemented using the Simple Knowledge Organization System (SKOS) mappingRelation vocabulary. This exercise helped to better describe the nature of the mappings between new LtC terms and related terms in other standards, and to validate decisions around the borrowing of existing terms for LtC. A further exercise also used elements of the Simple Standard for Sharing Ontological Mappings (SSSOM) to start to develop a more comprehensive set of metadata around these mappings. At present, these mappings (Suppl. material 1 and Suppl. material 2) are provisional and not considered to be comprehensive, but should be further refined and expanded over time. Even with the support provided by the SKOS and SSSOM standards, the LtC experience has proven the mapping process to be far from straightforward. Different standards vary in how they are structured, for example, DwC is a ‘bag of terms’, with informal classes and no structural constraints, while more structured standards and ontologies like ABCD and PROV employ different approaches to how structure is defined and documented. The various standards use different metadata schemas and serialisations (e.g., Resource Description Framework (RDF), XML) for their documentation, and different approaches to providing persistent, resolvable identifiers for their terms. There are also many subtle nuances involved in assessing the alignment between the concepts that the source and target terms represent, particularly when assessing whether a match is exact enough to allow the existing term to be adopted. These factors make the mapping process quite manual and labour-intensive. Approaches and tools, such as developing decision trees (Fig. 2) to represent the logic involved and further exploration of the SSSOM standard, could help to streamline this process. In this presentation, we will discuss the LtC experience of the standard mapping process, the challenges faced and methods used, and the potential to contribute this experience to a collaborative standards mapping within the anticipated TDWG Standards Mapping Interest Group.

Mapping across Standards to Calculate the MIDS Level of Digitisation of Natural Science Collections

The Minimum Information about a Digital Specimen (MIDS) standard is being developed within Biodiversity Information Standards (TDWG) to provide a framework for organisations, communities and infrastructures to define, measure, monitor and prioritise the digitisation of specimen data to achieve increased accessibility and scientific use. MIDS levels indicate different levels of completeness in digitisation and range from Level 0: not yet meeting minimal required information needs for scientific use to Level 3: fulfilling the requirements for Digital Extended Specimens (Hardisty et al. 2022) by inclusion of persistent identifiers (PIDs) that connect the specimen with derived and related data. MIDS Levels 0–2 are generic for all specimens. From MIDS Level 2 onwards we make a distinction between biological, geological and palaeontological specimens. While MIDS represents a minimum specification, defining and publishing more extensive sets of information elements (extensions) is readily feasible and explicitly recommended. The MIDS level of a digital specimen can be calculated based on the availability of certain information elements. The MIDS standard applies to published data. The ability to map from, to and between TDWG standards is key to being able to measure the MIDS level of the digitised specimen(s). Each MIDS term is being mapped across TDWG standards involving Darwin Core (DwC), the Access to Biological Collections Data (ABCD) Schema and Latimer Core (LtC, Woodburn et al. 2022), using mapping properties provided by the Simple Knowledge Organization System (SKOS) ontology. In this presentation, we will show selected case studies that demonstrate the implementation of the MIDS standard supplemented by MIDS mappings to ABCD, to LtC, and to the Distributed System of Scientific Collections' (DISSCo) Open Digital Specimen specification. The studies show the mapping exercise in practice, with the aim of enabling fully automated and accurate calculations. To provide a reliable indicator for the level of digitisation completeness, it is important that calculations are done consistently in all implementations.

Making Schemas and Mappings Available and FAIR: A metadata and schema crosswalk registry from the FAIRCORE4EOSC project

Community standards like the Darwin Core (Darwin Core Task Group 2009) together with semantic artefacts (controlled vocabularies, ontologies, thesauri, and other knowledge organisation systems) are key building blocks for the implementation of the FAIR (Findable, Accessible, Interoperable, Reusable) principles (Wilkinson et al. 2016), specifically as emphasized in the Interoperability principle I2 “(Meta)data use vocabularies that follow FAIR principles”. However, most of these artefacts are actually not FAIR themselves (Le Franc et al. 2020). To address this, the FAIRCORE4EOSC project (2022-25) is developing a Metadata Schema and Crosswalk Registry (MSCR) that will allow registered users and communities to create, register and version schemas and crosswalks that all have persistent identifiers (PIDs). The published content can then be searched, browsed and downloaded without restrictions. The MSCR will also provide an API to facilitate the transformation of data from one schema to another via registered crosswalks. It will provide projects and individual researchers with the possibility to manage their metadata schemas and/or relevant metadata schema crosswalks. The schema and crosswalks will be shared with the community for reuse and extension supported by a proper versioning mechanism. The registry tool will facilitate better interoperability between resource catalogues and information systems using different (metadata) schemas and encourage organisations and especially researchers to share their metadata interoperability by publishing the metadata crosswalks used in their workflows, which are currently not visible (FAIRification). By providing an easy-to-use graphical user interface (GUI) for creating crosswalks, the GUI will attract users currently relying on project-specific solutions.