Designing metadata schema for a human library: a prototype

Purpose In the absence of a working model for describing, managing and archiving the human library resources, this study aims to attempt a practical approach that will provide all the necessary information to the library users, library professionals and researchers. Design/methodology/approach Initially, different metadata standards, archival projects and attributes of the human books were reviewed to identify appropriate metadata standards that accurately describe the resources of the human library. A free and open-source software; DSpace was considered for implementing newly defined metadata schema in this study. Thereafter, a set of new subject entries was incorporated to standardize the contents of the human library. Findings This study finds that the widely used metadata schema – Dublin Core (DC) is not appropriate to describe the contents of the human book. It shows that selected metadata elements from the types – person and event of schema.org can be used for describing, organizing and archiving the resources of the human library. It further highlights that existing subject entries are not sufficient to standardize the contents of these types of resources. Research limitations/implications Two metadata fields in DSpace are strongly recommended by the DSpace community to consider in the input-forms.xml file, that is why the study could not completely omit DC metadata elements in describing human books. Originality/value The study provides a roadmap to the library professionals on the inclusion of new metadata schemas in describing the uniquely featured resources of the library.

Metadata Schema for Folktales in the Mekong River Basin

The aim of this study was to analyze the content, context, and structure of folktales from the Mekong River Basin, and to develop a metadata schema for data description and folktale storage. The research was conducted using the MAAT metadata lifecycle model, which comprises the following four steps: (1) conducting an information content analysis; (2) creating metadata requirements, (3) developing a metadata schema; and (4) carrying out a metadata service and evaluation. The folktale analysis, based on Anne Gilliland’s information object analysis, revealed the following: (1) the folktale content consists of types of tales, and the morals, beliefs, and parts they incorporate; (2) the folktale context consists of and names distributors, characters, scenes, magical objects, ethnic groups, languages, countries, relationships between tales, and their sources; (3) the folktale structure includes verbal, non-verbal, and mixed forms. The metadata schema development adopted the functional requirements for bibliographic records concepts and existing metadata standards, resulting in metadata with the following 18 elements: identifier, title, creator, contributor, description, relation, language, medium, sources, date, rights, keyword, character, moral, ethnic group, motif, place, and country. The metadata elements were described using the categories: name, definition, format, example, and note.

Fast Healthcare Interoperability Resources (FHIR) in a FAIR Metadata Registry for COVID-19 Research

Adopting international standards within health research communities can elevate data FAIRness and widen analysis possibilities. The purpose of this study was to evaluate the mapping feasibility against HL7® Fast Healthcare Interoperability Resources® (FHIR)® of a generic metadata schema (MDS) created for a central search hub gathering COVID-19 health research (studies, questionnaires, documents = MDS resource types). Mapping results were rated by calculating the percentage of FHIR coverage. Among 86 items to map, total mapping coverage was 94%: 50 (58%) of the items were available as standard resources in FHIR and 31 (36%) could be mapped using extensions. Five items (6%) could not be mapped to FHIR. Analyzing each MDS resource type, there was a total mapping coverage of 93% for studies and 95% for questionnaires and documents, with 61% of the MDS items available as standard resources in FHIR for studies, 57% for questionnaires and 52% for documents. Extensions in studies, questionnaires and documents were used in 32%, 38% and 43% of items, respectively. This work shows that FHIR can be used as a standardized format in registries for clinical, epidemiological and public health research. However, further adjustments to the initial MDS are recommended – and two additional items even needed when implementing FHIR. Developing a MDS based on the FHIR standard could be a future approach to reduce data ambiguity and foster interoperability.

Metadata Schema for Managing Digital Data and Images of Thai Human Skulls

This research was aimed at developing metadata that meets international standards for the purpose of managing digital data and images of Thai human skulls for medical studies. The research was conducted by applying the Metadata Lifecycle Model of the Metadata Architecture and Application Team. The model comprises four steps: requirement assessment and content analysis, identification of metadata requirements, metadata schema development, and metadata service and evaluation. The research outcome was a metadata schema composed of four modules, seven data element sets, and 29 pieces of data, each of which had six sets of property descriptions. Metadata evaluation conducted by three specialists in the field of anatomy and forensic medicine and three experts in the field of information science and metadata through free retrieval based on the Continuum of Metadata Quality in four aspects revealed that the experts were satisfied with the quality of metadata at a very high level: 100% for completeness, accuracy, and accessibility, and 94% for conformance to expectations. The developed metadata contain details that can be used to describe the characteristics of human skulls, with consideration taken in the development of the language used, retrieval, access, data exchange, and sharing. Thus, this novel metadata schema can be of use in management of digital data and images of human skulls for the purposes of medical studies, i.e., human anatomy and forensic anthropology.

DAMS: A Distributed Analytics Metadata Schema

In recent years, implementations enabling Distributed Analytics (DA) have gained considerable attention due to their ability to perform complex analysis tasks on decentralised data by bringing the analysis to the data. These concepts propose privacy-enhancing alternatives to data centralisation approaches, which have restricted applicability in case of sensitive data due to ethical, legal or social aspects. Nevertheless, the immanent problem of DA-enabling architectures is the black-box-alike behaviour of the highly distributed components originating from the lack of semantically enriched descriptions, particularly the absence of basic metadata for datasets or analysis tasks. To approach the mentioned problems, we propose a metadata schema for DA infrastructures, which provides a vocabulary to enrich the involved entities with descriptive semantics. We initially perform a requirement analysis with domain experts to reveal necessary metadata items, which represents the foundation of our schema. Afterwards, we transform the obtained domain expert knowledge into user stories and derive the most significant semantic content. In the final step, we enable machine-readability via RDF(S) and SHACL serialisations. We deploy our schema in a proof-of-concept monitoring dashboard to validate its contribution to the transparency of DA architectures. Additionally, we evaluate the schema’s compliance with the FAIR principles. The evaluation shows that the schema succeeds in increasing transparency while being compliant with most of the FAIR principles. Because a common metadata model is critical for enhancing the compatibility between multiple DA infrastructures, our work lowers data access and analysis barriers. It represents an initial and infrastructure-independent foundation for the FAIRification of DA and the underlying scientific data management.

re3data COREF – Enhancing the re3data service as a community-driven and trustworthy resource for research data repositories and portals

<p>re3data is the global registry for research data repositories. As of January 2021, the service lists over 2620 digital repositories across all scientific disciplines and provides an extensive description of repositories based on a detailed metadata schema (https://doi.org/10.2312/re3.008). A variety of funders, publishers, and scientific organizations around the world refer to re3data within their guidelines and policies, recommending the service to researchers looking for appropriate repositories for storage and discovery of research data. With over 750 entries the field of geosciences is one of the most strongly represented subject groups in the registry.</p><p>The re3data COREF project (Community Driven Open Reference for Research Data Repositories) started in January 2020 and receives funding from the German Research Foundation (DFG) for 36 months. With its main focus on the current project the presentation will outline the further professionalization of re3data and the provision of reliable and individualizable descriptions of research data repositories. This includes updates and revisions of the metadata schema, the advancement of the technical infrastructure as well as an enhanced overall (technical) service model concept to embed and connect the service within the research data landscape as a community-driven source and reference for trustworthy repositories.</p><p>In addition, outcomes from the first re3data COREF stakeholder survey and workshop held in November 2020 will be presented, introducing diverse use cases of the re3data service and examples for the reuse of its metadata. The presentation will address how re3data currently interlinks with external parties and how more advanced options for easier and trustworthy integration of third-party information can be facilitated.</p>