Metadata Enrichment Research Articles

Identifying genomic data use with the Data Citation Explorer

Increases in sequencing capacity, combined with rapid accumulation of publications and associated data resources, have increased the complexity of maintaining associations between literature and genomic data. As the volume of literature and data have exceeded the capacity of manual curation, automated approaches to maintaining and confirming associations among these resources have become necessary. Here we present the Data Citation Explorer (DCE), which discovers literature incorporating genomic data that was not formally cited. This service provides advantages over manual curation methods including consistent resource coverage, metadata enrichment, documentation of new use cases, and identification of conflicting metadata. The service reduces labor costs associated with manual review, improves the quality of genome metadata maintained by the U.S. Department of Energy Joint Genome Institute (JGI), and increases the number of known publications that incorporate its data products. The DCE facilitates an understanding of JGI impact, improves credit attribution for data generators, and can encourage data sharing by allowing scientists to see how reuse amplifies the impact of their original studies.

OpenCitations Meta

Abstract OpenCitations Meta is a new database for open bibliographic metadata of scholarly publications involved in the citations indexed by the OpenCitations infrastructure, adhering to Open Science principles and published under a CC0 license to promote maximum reuse. It presently incorporates bibliographic metadata for publications recorded in Crossref, DataCite, and PubMed, making it the largest bibliographic metadata source using Semantic Web technologies. It assigns new globally persistent identifiers (PIDs), known as OpenCitations Meta Identifiers (OMIDs) to all bibliographic resources, enabling it both to disambiguate publications described using different external PIDS (e.g., a DOI in Crossref and a PMID in PubMed) and to handle citations involving publications lacking external PIDs. By hosting bibliographic metadata internally, OpenCitations Meta eliminates its former reliance on API calls to external resources and thus enhances performance in response to user queries. Its automated data curation, following the OpenCitations Data Model, includes deduplication, error correction, metadata enrichment, and full provenance tracking, ensuring transparency and traceability of data and bolstering confidence in data integrity, a feature unparalleled in other bibliographic databases. Its commitment to Semantic Web standards ensures superior interoperability compared to other machine-readable formats, with availability via a SPARQL endpoint, REST APIs, and data dumps.

Cultural heritage on the Semantic Web: The Europeana Data Model

The Semantic Web allows data to be linked on the Web and structures information for use by humans and machines. Furthermore, it makes relationships between data explicit, enabling the creation of Linked Data. Based on a literature review, the principles and technologies underlying Linked Data are presented – namely, the Resource Description Framework and models developed for libraries, archives and museums. Europeana aggregates European institutions’ digital cultural heritage, having developed a model that follows linked-data principles. For a deeper understanding of this model, the Europeana Data Model is presented with examples of two representation approaches and the advantages of metadata enrichment in information discovery. The experience of the University of Coimbra with Europeana is briefly explained. Finally, the authors discuss the challenges that cultural heritage institutions face in adopting these models and freeing their information from the silos it is in, taking advantage of the potential that Linked Data provides.

OAVA: the open audio-visual archives aggregator

The purpose of the current article is to provide an overview of an open-access audiovisual aggregation and search service platform developed for Greek audiovisual content during the OAVA (Open Access AudioVisual Archive) project. The platform allows the search of audiovisual resources utilizing metadata descriptions, as well as full-text search utilizing content generated from automatic speech recognition (ASR) processes through deep learning models. A dataset containing reliable Greek audiovisual content providers and their resources (1710 in total) is created. Both providers and resources are reviewed according to specific criteria already established and used for content aggregation purposes, to ensure the quality of the content and to avoid copyright infringements. Well-known aggregation services and well-established schemas for audiovisual resources have been studied and considered regarding both aggregated content and metadata. Most Greek audiovisual content providers do not use established metadata schemas when publishing their content, nor technical cooperation with them is guaranteed. Thus, a model is developed for reconciliation and aggregation. To utilize audiovisual resources the OAVA platform makes use of the latest state-of-the-art ASR approaches. OAVA platform supports Greek and English speech-to-text models. Specifically for Greek, to mitigate the scarcity of available datasets, a large-scale ASR dataset is annotated to train and evaluate deep learning architectures. The result of the above-mentioned efforts, namely selection of content, metadata, development of appropriate ASR techniques, and aggregation and enrichment of content and metadata, is the OAVA platform. This unified search mechanism for Greek audiovisual content will serve teaching, research, and cultural activities. OAVA platform is available at: https://openvideoarchives.gr/.

RADio* – An Introduction to Measuring Normative Diversity in News Recommendations

In traditional recommender system literature, diversity is often seen as the opposite of similarity, and typically defined as the distance between identified topics, categories or word models. However, this is not expressive of the social science’s interpretation of diversity, which accounts for a news organization’s norms and values and which we here refer to as normative diversity. We introduce RADio, a versatile metrics framework to evaluate recommendations according to these normative goals. RADio introduces a rank-aware Jensen Shannon (JS) divergence. This combination accounts for (i) a user’s decreasing propensity to observe items further down a list and (ii) full distributional shifts as opposed to point estimates. We evaluate RADio’s ability to reflect five normative concepts in news recommendations on the Microsoft News Dataset and six (neural) recommendation algorithms, with the help of our metadata enrichment pipeline. We find that RADio provides insightful estimates that can potentially be used to inform news recommender system design.

Automating subject indexing at ZBW

Subject indexing, i.e., the enrichment of metadata records for textual resources with descriptors from a controlled vocabulary, is one of the core activities of libraries. Due to the proliferation of digital documents, it is no longer possible to annotate every single document intellectually, which is why we need to explore the potentials of automation on every level. At ZBW the efforts to partially or completely automate the subject indexing process started as early as 2000 with experiments involving external partners and commercial software. The conclusion of that first exploratory period was that commercial, supposedly shelf-ready solutions would not suffice to cover the requirements of the library. In 2014 the decision was made to start doing the necessary applied research in-house which was successfully implemented by establishing a PhD position. However, the prototypical machine learning solutions that they developed over the following years were yet to be integrated into productive operations at the library. Therefore in 2020 an additional position for a software engineer was established and a pilot phase was initiated (planned to last until 2024) with the goal to complete the transfer of our solutions into practice by building a suitable software architecture that allows for real-time subject indexing with our trained models and the integration thereof into the other metadata workflows at ZBW. In this paper we address the question of how to transfer results from applied research into a productive service, and we report on the milestones we have reached so far and on those that are yet to be reached on an operational level. We also discuss the challenges we were facing on a strategic level, the measures and resources (computing power, software, personnel) that were needed in order to be able to affect the transfer, and those that will be necessary in order to subsequently ensure the continued availability of the architecture and to enable a continuous development during running operations. We conclude that there are still no shelf-ready open source systems for the automation of subject indexing – existing software has to be adapted and maintained continuously which requires various forms of expertise. However, the task of automation is here to stay, and librarians are witnessing the dawn of a new era where subject indexing is done at least in part by machines, and the respective roles of machines and human experts may shift even further and more rapidly in a not-so-distant future. We argue that in general, the format of “project” and the mindset that goes with it may not suffice to secure the commitment that an institution and its decision-makers and the library community as a whole will have to bring to the table in order to face the monumental task of the digital transformation and automation in the long run. We also highlight the importance of all parties – applied researchers, software engineers, stakeholders – staying involved and continuously communicating requirements and issues back and forth in order to successfully create and establish a productive service that is suitable and equipped for operation.

Improving FAIRness of eDNA and Metabarcoding Data: Standards and tools for European Nucleotide Archive data deposition

The advancements in sequencing technologies have promoted the generation of molecular data for cataloguing and describing biodiversity. The analysis of environmental DNA (eDNA) through the application of metabarcoding techniques enables comprehensive descriptions of communities and their function, being fundamental for understanding and preserving biodiversity. Metabarcoding is becoming widely used and standard methods are being generated for a growing range of applications with high scalability. The generated data can be made available in its unprocessed form, as raw data (the sequenced reads) or as interpreted data, including sets of sequences derived after bioinformatics processing (Amplicon Sequence Variants (ASVs) or Operational Taxonomic Units (OTUs)) and occurrence tables (tables that describe the occurrences and abundances of species or OTUs/ASVs). However, for this data to be Findable, Accessible, Interoperable and Reusable (FAIR), and therefore fully available for meaningful interpretation, it needs to be deposited in public repositories together with enriched sample metadata, protocols and analysis workflows (ten Hoopen et al. 2017). Metabarcoding raw data and associated sample metadata is often stored and made available through the International Nucleotide Sequence Database Collaboration (INSDC) archives (Arita et al. 2020), of which the European Nucleotide Archive (ENA, Burgin et al. 2022) is its European database, but it is often deposited with minimal information, which hinders data reusability. Within the scope of the Horizon 2020 project, Biodiversity Community Integrated Knowledge Library (BiCIKL), which is building a community of interconnected data for biodiversity research (Penev et al. 2022), we are working towards improving the standards for molecular ecology data sharing, developing tools to facilitate data deposition and retrieval, and linking between data types. Here we will present the ENA data model, showcasing how metabarcoding data can be shared, while providing enriched metadata, and how this data is linked with existing data in other research infrastructures in the biodiversity domain, such as the Global Biodiversity Information Facility (GBIF), where data is deposited following the guidelines published in Abarenkov et al. (2023). We will also present the results of our recent discussions on standards for this data type and discuss future plans towards continuing to improve data sharing and interoperability for molecular ecology.

Wikibase Model for Premodern Manuscript Metadata Harmonization, Linked Data Integration, and Discovery

To facilitate discovery of premodern manuscripts in U.S. memory institutions, Digital Scriptorium, a growing consortium of over 35 institutional members representing American libraries, museums, and other cultural heritage institutions, has developed a digital platform for an online national union catalog. The platform will allow low-barrier and efficient collection, aggregation, and enrichment of member metadata and sustainably publish it as Linked Open Data. This article describes the methods and principles behind the data model development and the decision to use Wikibase. The results of the prototype implementation and testing phase demonstrate the practicality and sustainability of Digital Scriptorium’s approach to building an online national union catalog based on Linked Open Data technologies and practices.

THE CORPORA-ORIENTED PROJECTS AND COURSES – INNOVATION OF THE UNIVERSITY LIFE

The advancement of computer technologies opened up a bunch of opportunities in different spheres of life. Computer science has revolutionized the modes of studying and researching. The educators and policy makers started modernization of educational programs in accordance to the latest achievements in the field. The present paper deals with the presentation of the progressive university courses as well as the projects (winter schools, Akaki Shanidze’s Digital Library and Text Corpus, etc.) facilitating the integration of corpora in teaching and researching. The major accept is put on the successful modes of the enhancement of the learners’ digital skills (operation, application, problem solving, critical thinking, etc.), corpus-building abilities (annotation, orientation towards the scientific metalanguage, enrichment of metadata, etc.), corpora-based analysis (proper coinage, finding equivalency, plying with concepts and terms, etc.) as well as the corpus-oriented research. Determination of the major challenges and outcomes of the projects and courses, discussion of some gaps, introduction of the convenient opportunities of their “filling” – these are the major issues of the paper. The methodology of research includes observation, analysis and evaluation of the ongoing processes.

ENHANCED FINDABILITY AND REUSABILITY OF ENGINEERING DATA BY CONTEXTUAL METADATA

AbstractComplex research problems are increasingly addressed by interdisciplinary, collaborate research projects generating large amounts of heterogeneous amounts of data. The overarching processing, analysis and availability of data are critical success factors for these research efforts. Data repositories enable long term availability of such data for the scientific community. The findability and therefore reusability strongly builds on comprehensive annotations of datasets stored in repositories. Often generic metadata schema are used to annotate data. In this publication we describe the implementation of discipline specific metadata into a data repository to provide more contextual information about data. To avoid extra workload for researchers to provide such metadata a workflow with standardised data templates for automated metadata extraction during the ingest process has been developed. The enriched metadata are in the following used in the development of two repository plugins for data comparison and data visualisation. The added values of discipline-specific annotations and derived search features to support matching and reusable data is then demonstrated by use cases of two Collaborative Research Centres (CRC 1368 and CRC 1153).

DETEXA: declarative extensible text exploration and analysis through SQL

Metadata enrichment through text mining techniques is becoming one of the most significant tasks in digital libraries. Due to the exponential increase of open access publications, several new challenges have emerged. Raw data are usually big, unstructured, and come from heterogeneous data sources. In this paper, we introduce a text analysis framework implemented in extended SQL that exploits the scalability characteristics of modern database management systems. The purpose of this framework is to provide the opportunity to build performant end-to-end text mining pipelines which include data harvesting, cleaning, processing, and text analysis at once. SQL is selected due to its declarative nature which offers fast experimentation and the ability to build APIs so that domain experts can edit text mining workflows via easy-to-use graphical interfaces. Our experimental analysis demonstrates that the proposed framework is very effective and achieves significant speedup, up to three times faster, in common use cases compared to other popular approaches.

Cross-portal metadata alignment – Connecting open data portals through means of formal concept analysis

Due to openness and transparency initiatives, a vast amount of data is being made publicly available. This data has great significance for business and society. However, it also led to challenges that need to be overcome for this data to reach its full potential. In this paper, we are focusing on the problem of connecting open data portals (ODPs) through metadata alignment. We investigate the available metadata accompanying datasets, especially the part related to categories datasets belong to and tags that closely describe datasets. The methodology we propose is relying on Formal Concept Analysis for the creation of the hierarchical structure used for determining the similarity of tags' usage in different ODPs. We propose such a structure to be used for open data portal metadata alignment. Further, we apply semantic similarity measures to reduce the complexity of the cross-portal data structure while preserving all its characteristics. We demonstrate how our approach can be used for determining dataset category across multiple ODPs aligned using the data structure our approach generates. We envision our approach to improve cross-portal search and metadata enrichment through open data categorization. Lastly, the quality of our approach was tested using datasets obtained from Canada’s and New Zealand’s ODPs.

Exploring microbial functional biodiversity at the protein family level-From metagenomic sequence reads to annotated protein clusters.

Metagenomics has enabled accessing the genetic repertoire of natural microbial communities. Metagenome shotgun sequencing has become the method of choice for studying and classifying microorganisms from various environments. To this end, several methods have been developed to process and analyze the sequence data from raw reads to end-products such as predicted protein sequences or families. In this article, we provide a thorough review to simplify such processes and discuss the alternative methodologies that can be followed in order to explore biodiversity at the protein family level. We provide details for analysis tools and we comment on their scalability as well as their advantages and disadvantages. Finally, we report the available data repositories and recommend various approaches for protein family annotation related to phylogenetic distribution, structure prediction and metadata enrichment.

Computer vision and machine learning approaches for metadata enrichment to improve searchability of historical newspaper collections

PurposeHistorical newspaper collections provide a wealth of information about the past. Although the digitization of these collections significantly improves their accessibility, a large portion of digitized historical newspaper collections, such as those of KBR, the Royal Library of Belgium, are not yet searchable at article-level. However, recent developments in AI-based research methods, such as document layout analysis, have the potential for further enriching the metadata to improve the searchability of these historical newspaper collections. This paper aims to discuss the aforementioned issue.Design/methodology/approachIn this paper, the authors explore how existing computer vision and machine learning approaches can be used to improve access to digitized historical newspapers. To do this, the authors propose a workflow, using computer vision and machine learning approaches to (1) provide article-level access to digitized historical newspaper collections using document layout analysis, (2) extract specific types of articles (e.g. feuilletons – literary supplements from Le Peuple from 1938), (3) conduct image similarity analysis using (un)supervised classification methods and (4) perform named entity recognition (NER) to link the extracted information to open data.FindingsThe results show that the proposed workflow improves the accessibility and searchability of digitized historical newspapers, and also contributes to the building of corpora for digital humanities research. The AI-based methods enable automatic extraction of feuilletons, clustering of similar images and dynamic linking of related articles.Originality/valueThe proposed workflow enables automatic extraction of articles, including detection of a specific type of article, such as a feuilleton or literary supplement. This is particularly valuable for humanities researchers as it improves the searchability of these collections and enables corpora to be built around specific themes. Article-level access to, and improved searchability of, KBR's digitized newspapers are demonstrated through the online tool (https://tw06v072.ugent.be/kbr/).

Entification of Metadata for Knowledge‐Graph‐Guided Discovery

AbstractThis paper reports on the application of entification to collections of archival metadata. Entification refers to the identification of the entities described in information objects and associated metadata records. The process presents issues about whether existing records‐style metadata records are suitable and how entification will affect user access and interaction with metadata and information objects. In this study, we developed an entification workflow that includes the following steps: data cleaning, entity reconciliation to create linked data through metadata enrichment, accuracy selection, and developing knowledge graphs to communicate the semantic relationships among entities. Additionally, we discuss the implications of entification for practitioners in the field of information science, especially current limitations in the process.

Paving the way for enriched metadata of linguistic linked data

The need for reusable, interoperable, and interlinked linguistic resources in Natural Language Processing downstream tasks has been proved by the increasing efforts to develop standards and metadata suitable to represent several layers of information. Nevertheless, despite these efforts, the achievement of full compatibility for metadata in linguistic resource production is still far from being reached. Access to resources observing these standards is hindered either by (i) lack of or incomplete information, (ii) inconsistent ways of coding their metadata, and (iii) lack of maintenance. In this paper, we offer a quantitative and qualitative analysis of descriptive metadata and resources availability of two main metadata repositories: LOD Cloud and Annohub. Furthermore, we introduce a metadata enrichment, which aims at improving resource information, and a metadata alignment to META-SHARE ontology, suitable for easing the accessibility and interoperability of such resources.

Enabling Community Curation of Biological Source Annotations of Molecular Data Through PlutoF and the ELIXIR Contextual Data Clearinghouse

The advancements in sequencing technologies have greatly contributed to the documentation of Earth’s biodiversity. However, for exploring the full potential of molecular resources for biodiversity, there needs to be a good linkage between sequence data and its biological source, contributing to a network of connected data in the biodiversity research cycle. This requires a foundation of well-structured and accessible annotations in the molecular sequence repositories. The International Nucleotide Sequence Database Collaboration (INSDC), of which the European Nucleotide Archive (ENA) is its European node, holds a large amount of annotations associated with sequence data, relating to its biological source (e.g., specimens in natural history collections). However, for a number of records, these annotations may be incomplete (e.g., missing voucher information), ambiguous or even inaccurate. Therefore, we have implemented a workflow that allows third-party annotations to be attached to sequence and sample records using two existing services, the PlutoF platform and the ELIXIR Contextual Data ClearingHouse. This work was developed within the scope of the BiCIKL (Biodiversity Community Integrated Knowledge Library) project, which aims to establish open science practices in the biodiversity domain. PlutoF is an online data management platform that also provides computing services for biology-related research. PlutoF features allow registered users to enter their own data and access public data at INSDC. Users can enter and manage a range of data, as taxonomic classifications, occurrences, etc. This platform also includes a module that allows the addition of third-party annotations (on material source, taxonomic identification, etc.) linked to specimens or sequence records. This module was already in use by the UNITE community for annotation of INSDC rDNA Internal Transcribed Spacer sequence datasets (Abarenkov et al. 2021). These UNITE annotations are displayed in the National Centre for Biotechnology Information (NCBI) records through links to the PlutoF platform. However, there was the need for an automated solution that allowed third-party annotations to any sequence or sample record at INSDC. This was implemented through the operation of the ELIXIR Contextual Data ClearingHouse (hereafter as Clearinghouse). The Clearinghouse holds a simple RESTful Application Programming Interface (API) to support the submission of additions and improvements to current metadata attributes, such as information on material sources, on records publicly available in the ELIXIR data resources. The Clearinghouse enables the submission of these corrected metadata from databases (such as the PlutoF platform) to the primary data repositories. The workflow developed is shown in Fig. 1 and consists of the following steps: i) users annotate sequence metadata that is regularly downloaded from INSDC using NCBI’s E-utilities; ii) an annotation proposal is created and a verification notification is sent to an assigned reviewer; iii) the reviewer evaluates the annotation proposal and accepts it or rejects it with comments; iv) if the annotation proposal is accepted, the annotated fields that may be mapped to ENA fields are then pushed to the Clearinghouse using their RESTful API. The annotations when received at ENA are then reviewed before being displayed. This workflow is implemented through a web interface in PlutoF, which allows user-friendly and effortless reporting of corrections or additions to biological source metadata in sequence records. Overall, we expect this tool to contribute to the enrichment of metadata associated with sequence records, and therefore increase the links between the molecular and biodiversity resources, and enable sequencing data to deliver their full potential for biodiversity conservation.

Towards Connecting Molecular Data and the Biodiversity Research Community: An ENA and ELIXIR biodiversity community perspective

Global and regional efforts for generating molecular sequencing data are fundamental to characterise and monitor the Earth’s biodiversity. However, exploiting the full potential of molecular data for biodiversity monitoring and conservation is still a challenge. There is still the need to fully connect the generation and archiving of sequence data with other biodiversity infrastructures, thereby promoting Findability, Accessability, Interoperability and Reusability (FAIR) of data. Here we present the ongoing activities and future plans of the European Life-Science Infrastructure (ELIXIR) and the European Molecular Biology Laboratory European Bioinformatics Institute’s (EMBL-EBI) European Nucleotide Archive (ENA, the European node of the International Nucleotide Sequence Database Collaboration - INSDC) towards an enriched set of sequence data connected to the wider biodiversity research community. ELIXIR has an emerging Biodiversity Community that was originally created as a focus group in 2019, to better align the work in biodiversity across the ELIXIR Nodes and with global initiatives in the biodiversity domain. This group has been working on understanding the capabilities, interests and ongoing projects that exist across the Nodes, developing connections with external partners in the biodiversity area (e.g. Global Biodiversity Information Facilitiy, GBIF; LifeWatch Eric) and developing a longer term strategy for support of biodiversity by ELIXIR. A recent opinion piece by the group (Waterhouse et al. 2021) highlights opportunities for infrastructure developments in the area of biodiversity and provides recommendations for closer integration of molecular data with biodiversity research. These recommendations include the alignment of taxonomies across domains and the general adoption of standardized metadata. ELIXIR and EMBL-EBI are involved in several biodiversity genomics initiatives, including the Earth BioGenome Project (EBP), the Darwin Tree of Life Project (DToL), the European Reference Genome Atlas (ERGA), and the BIOSCAN Europe, where support is being provided to data curation, submission and visibility and in the definition of standards for the associated metadata (e.g. Lawniczak et al. 2022). Moreover, EMBL-EBI is a partner of UniEuk, an initiative that is working towards building a flexible universal taxonomic framework for eukaryotes. ELIXIR and EMBL-EBI are also part of the Biodiversity Community Integrated Knowledge Library (BiCIKL), an Horizon 2020 project that is working towards establishing FAIR practices in the biodiversity domain, and thereby developing tools and workflows for connecting data along the biodiversity research cycle (Penev et al. 2022). These projects and community efforts are contributing to improving metadata standards and pushing the development of tools and workflows to support enriched metadata and increased linkage with other biodiversity infrastructures. Overall, we need to continue to work towards a strong foundation of interlinked knowledge to be able to effectively respond to global challenges such as biodiversity loss and ecosystem change.

New Approaches Towards the Delivery of Service Information Using Semantic Correlation Rules

Knowledge about products and their applications, as well as how to use them, is often distributed in different places within companies. In the past, this has been an internally and externally accepted situation leading to time-consuming searches for required data. Nowadays, expectations of in-time delivery of information and the general view of knowledge processes as well as on associated data are changing radically. Traditional methods and approaches for storing, distributing and accessing information are therefore in many cases inappropriate and are questioned on industry-side. For example, in the domain of customer service of B2B products in machinery industry, it was common to communicate by phone with experts and help-desk-organizations, who provided the required information by experience or by informal information exchange networks. Under the pressure of digitalization and the constant increase in efficiency, as well as the demand of customers to obtain requested information more quickly, new ways of providing and connecting information are becoming increasingly relevant. It is still unrealistic to assume that all relevant information can be prepared specific to each target group and to each application within a short period of time. Rather, the challenge is to create and store information in the future in a structured way with meaningful semantic and consistent metadata and, on the other hand, to relate this new information to existing information in such a way that the user can be helped quickly and easily. Several preconditions are crucial to build up a new information infrastructure: First, management has to be convinced of the benefits of storage and intelligent search environments and to get support from relevant stakeholders. Subsequently, new information architectures require smart approaches for content authoring and metadata enrichment supporting information delivery via different media channels for relevant customer groups. Time and effort for setting up this new architectures has to be argued and justified..

Re-imagining (black) comic book cataloguing: increasing accessibility through metadata at one university library

ABSTRACT Cataloguing single-issue comic books has been a challenge that has flustered librarians for nearly half a century. At one Mid-Atlantic public university’s library, rapid growth of their trade comic book collection necessitated finding ways to make its contents more useful, usable, and accessible in the library catalogue. Familiar tags meant to increase the findability of these comics, such as pencillers, inkers, characters, and story arcs, were added to these records. The need for this project accelerated as the library began developing a collection of Black comic books, highlighted by characters such as Black Panther and Vixen and creators like Dwayne McDuffie and Ta-Nehisi Coates. This required an acknowledgement of the historically silenced contributions of members of the African diaspora and how things such as Library of Congress Subject Headings have ascribed normativity to white comic book characters and creators while tokenising the contributions of those from marginalised groups. This essay explores the technical and ethical challenges of demographic metadata using bibliographic and authority records. The aspiration of this project is increased access to the entire comic book collection, especially through socially-engaged metadata enrichment.