Posters

This study addresses the persistent challenges of metadata interoperability and cultural inclusivity within Galleries, Libraries, Archives, and Museums (GLAM) institutions in the ASEAN region. It proposes a hybrid metadata framework that integrates international standards—such as Dublin Core, CIDOC-CRM, and EAD—with culturally responsive elements including indigenous protocols, multilingual support, and post-custodial metadata practices. Employing a mixed-methods approach, the research combined thematic analysis of existing metadata practices with case studies on Indonesian and Thai heritage collections. The resulting framework, implemented in the ASEAN GLAM Repositories prototype system, features modular metadata categories and technologies such as OAI-PMH, JSON API, and blockchain-based provenance tracking. Evaluation results indicate the framework preserves 98% metadata integrity, supports 47 minority languages across six scripts, and significantly enhances cross-institutional interoperability and user engagement. The findings demonstrate that ethical, context-aware metadata design is both feasible and impactful for digital heritage management. This study contributes a scalable model for inclusive and sustainable metadata practices, with broad applicability for global GLAM environments seeking to balance technical rigor with cultural sensitivity.

The study investigates the hypothesis that the adoption of metadata standards such as DCAT in German municipal Open Data portals improves the assignability of datasets to specific geographical regions. It focuses on municipal Open Data portals and compares those that utilise DCAT-compliant metadata structures to portals with non-standard formats, such as ArcGIS JSON. The harvesting and analysis of metadata from each portal is conducted via public endpoints. The classification routine is based on metadata fields such as geocoding URI, dct:spatial and keywords . Each dataset is evaluated for its regional geographical capability. Preliminary results suggest that DCAT-based portals significantly outperform non-standard implementations in terms of regional assignability of datasets, error rate, and metadata completeness.

As interest in applying artificial intelligence (AI) to cataloging and metadata creation grows, there remains a lack of comparative analysis on how current generative AI performs in real-world workflows. This project evaluates the practical capabilities of four freely available generative AI models in creating descriptive metadata, examining which aspects of bibliographic description they handle effectively and where they fall short. By analyzing each model’s output and identifying strengths and limitations, the study offers guidance for catalogers seeking to integrate generative AI into their work. The findings aim to support informed decision-making, set realistic expectations, and contribute to ongoing discussions around automation, labor, and quality in metadata creation.

This ongoing project aims to evaluate the quality and completeness of publisher-generated metadata in Spanish law journals by comparing records from Crossref and OpenAlex with those curated by Dialnet, a major Spanish bibliographic platform. Using a mixed-methods approach, we analyze metadata elements such as authorship, abstracts, references and ORCID identifiers across a corpus of journals. The expected findings may help identify inconsistencies and gaps, particularly in metadata standardization and completeness, which hinder the discoverability and interoperability of legal scholarship.

This poster highlights the importance of integrating open metadata management in open access book publishing. It showcases publishers from a variety of regions across the globe using Thoth Open Metadata to manage and distribute FAIR and open metadata in multiple formats. Doing so, Thoth Open Metadata enables publishers to establish good metadata practice, while also fostering discoverability, sustainability, and accessibility of publishers' valuable contributions to the scholarlay record. The implementation of open practices also promotes collaboration with open infrastructures supporting open scholarship.

This research examines ethical metadata practices within LGBTQIA+ community archives, documenting how marginalized communities develop alternative descriptive systems that center lived experiences rather than institutional standards. Through autoethnographic methodology, the study reveals critical tensions between standardized vocabularies and community terms in representing queer histories. Initial findings inform a framework for "metadata dignity" emphasizing community agency, temporal flexibility for evolving terminology, ethical interoperability, and reflexive practice. Future research involves comparative analysis across archives, interviews with stakeholders, and controlled vocabulary analysis. This work contributes practical guidelines for improving marginalized community representation while advancing conversations about ethical metadata creation and balancing standardization with contextual specificity.

Background and Motivation The Korea Institute of Science and Technology Information (KISTI) has been at the forefront of Korea’s scientific advancement for over six decades, leading innovation in science and technology information services and supercomputing infrastructure. In the current era of artificial intelligence and high-performance computing convergence, KISTI operates the National Research Data Platform (DataON) to systematically manage and provide long-term access to research data as strategic knowledge assets for national R&D innovation. DataON represents Korea's commitment to transforming research data from isolated institutional resources into a unified national asset that drives innovation-based economic growth and enhances the efficiency and competitiveness of government-funded research activities. Korea is pioneering the world's first comprehensive “Research Data Act,” which fundamentally restructures the national approach to research data management. This landmark legislation shifts responsibility from individual researchers to research institutions, creating a systematic framework for accumulating, sharing, and utilizing research data to generate new scientific, technological, and socio-economic value. The act mandates that all government-funded research institutes deposit their data into DataON, establishing unprecedented requirements for national-scale data sharing and accessibility. Problem Statement The implementation of mandatory data deposition presents significant technical and organizational challenges for DataON. Currently, the platform manages heterogeneous research data from diverse scientific disciplines, including the Korea Institute of Geoscience and Mineral Resources, the Korea Polar Research Institute, the Korea Research Institute of Bioscience and Biotechnology, the Korea Institute of Oriental Medicine, and the Korea Research Institute of Chemical Technology. Each contributing institute operates within distinct disciplinary paradigms, employing specialized data collection methodologies, analytical frameworks, and documentation practices that result in fundamentally different metadata structures and vocabularies. This metadata heterogeneity creates substantial barriers to effective data discovery, integration, and cross-disciplinary utilization. Users attempting to locate relevant datasets across multiple domains encounter inconsistent descriptive frameworks, incompatible terminology systems, and varying levels of documentation completeness. The lack of standardized metadata schemas undermines the platform’s core mission of facilitating knowledge-based innovation and limits the potential for serendipitous discoveries that often emerge from interdisciplinary data exploration. Methodology KISTI’s Data Platform Center has initiated a comprehensive metadata standardization program employing systematic analysis and stakeholder engagement methodologies. The approach encompasses four critical phases: First, conducting exhaustive evaluation of existing metadata schemas currently implemented within DataON, documenting their structural characteristics, semantic coverage, and operational effectiveness. Second, performing detailed comparative analysis of metadata schemas submitted by participating research institutes, identifying common elements, unique requirements, and potential integration pathways. Third, investigating contemporary international metadata standards and emerging best practices in scientific data management, including examination of successful implementations in similar national research infrastructures globally. Fourth, synthesizing findings to develop a unified, extensible metadata schema framework that accommodates disciplinary specificity while ensuring cross-domain interoperability and semantic consistency. The methodology emphasizes evidence-based decision-making through quantitative analysis of metadata usage patterns, qualitative assessment of user experience requirements, and iterative refinement through stakeholder feedback mechanisms. Particular attention is devoted to maintaining backward compatibility with existing data deposits while establishing forward-looking frameworks that can accommodate emerging research paradigms and technological developments. Expected Outcomes and Impact The standardized metadata schema framework will fundamentally transform Korea's national research data ecosystem by enabling seamless data discovery, enhanced interoperability, and systematic reusability across disciplinary boundaries. Implementation across participating institutes will catalyze cross-disciplinary research collaboration, accelerate scientific discovery processes, and maximize return on investment for government-funded research activities. The framework seeks Telecommunications Technology Association (TTA) certification to ensure alignment with national technical standards and facilitate broader adoption across Korea’s research infrastructure. Beyond immediate operational improvements, this standardization initiative will establish Korea as an international leader in national research data management, providing a replicable model for countries developing similar legislative frameworks and technical infrastructures. Significance This research addresses fundamental challenges in large-scale, multidisciplinary research data management while contributing to the broader scientific understanding of metadata standardization in heterogeneous research environments. The work provides critical insights for policymakers, research administrators, and technical professionals engaged in developing national research data infrastructures, offering practical solutions that balance standardization benefits with disciplinary autonomy requirements. The standardized approach will position Korea’s research ecosystem for enhanced productivity and innovation in an increasingly data-driven scientific landscape.