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            <title><![CDATA[Interoperable CSV for Environmental Data Archival and Exchange: iCSV]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-039</link>
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            <pubDate>Thu, 22 Oct 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Environmental research relies on seamless data exchange between institutions globally, but inadequate documentation and complex formats hinder collaboration. We introduce interoperable CSV (iCSV), a self-describing, human-readable format that combines the simplicity of Comma-Separated Values (CSV) with the metadata richness of NetCDF(Network Common Data Format)/CF (Climate and Forecast). iCSV ensures long-term interpretability, interoperability, and user accessibility, addressing key challenges in environmental data stewardship. By embedding structured metadata directly in a human-readable text file, iCSV enables automated validation, supports FAIR principles, and lowers the barrier to data sharing and reuse while ensuring data remains interpretable for future users and maintaining broad compatibility with existing software. This work motivates the need for a simple, self-describing tabular format for environmental time series, presents the iCSV specification, positions it within existing binary and human-readable format ecosystems through comparative analysis, and discusses current limitations with directions for future improvements.]]></description>
            <category>ARTICLE</category>
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        <item>
            <title><![CDATA[Dataset Publication Standards: Community Lessons from a Multi-Stakeholder Workshop on FAIR Implementation]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-038</link>
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            <pubDate>Mon, 19 Oct 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Ninety-seven percent of biological research identifiers (accession numbers) are published in supplementary files rather than in manuscripts. These files are usually in proprietary formats, such as Excel. This makes them invisible to standard search engines and difficult for machines to process. This ‘long tail of data’ is a critical resource for reproducibility and discovery, yet it remains hidden from researchers and curators alike. Although Findable, Accessible, Interoperable and Reusable (FAIR) standards exist, they have not yet been adopted and/or coordinated.
To address this issue, we organised a multi-stakeholder workshop with international experts from data repositories, publishing houses, text mining, and standards organisations, at SciDataCon 2025 in Brisbane. The solutions presented at the workshop, along with subsequent community dialogue, revealed that, while stakeholders agree on the necessary standards, key questions remain about how to implement them. Three barriers emerged: timing (should FAIRification occur during or after peer review?), governance (who enforces standards?), and incentives (who funds what?).
Our recommendations are as follows: authors should deposit datasets early; publishers should embed FAIR standards in the peer review process; repositories should harmonise metadata to enable cross-platform discovery; funders should require and support FAIR compliance.
This paper argues that implementing FAIR standards requires coordinated action across the research ecosystem with regard to technical standards, governance, incentives, and workflows.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[What Do We Mean by ‘Version’? Actionable Guidelines for the Versioning of Data]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-037</link>
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            <pubDate>Tue, 22 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[The data lifecycle, from acquisition to release, is increasingly complex, involving multiple processing stages, research groups, and funding sources. There are also growing concerns about data sovereignty and data governance. This complexity demands a robust conceptual framework to ensure reproducible versioning and linking of any original datasets to their many derivatives.
To address this, we initially developed six data versioning principles for digital data artefacts by analysing use cases and adapting the Functional Requirements for Bibliographic Records framework for analogue Information Resources. Our six principles established a common language for key concepts and terms: Revision, Release, Granularity, Manifestation, Provenance, and Citation.
In this paper, we present recommendations for implementing the data versioning principles after consulting data communities. The recommendations cover: adopting a consistent versioning strategy; considering standardisation initiatives; using persistent identifiers and unambiguous identification of versions; implementing clear and descriptive version labels; ensuring user-friendly version control systems; documenting changes and metadata; and communicating versioning practices clearly to stakeholders.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Toward a Standardized Framework for Benthic Mapping Data and Metadata Integration in Florida]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-036</link>
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            <pubDate>Thu, 17 Sep 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Spatially-integrated marine benthic data provide the foundation for effective spatial decision-support tools that address critical issues in marine and coastal systems. However, the diversity of benthic data types and forms often presents challenges for proper data integration. Without common standards, these data cannot be easily integrated and reused. Here, we proposed standards for data collection, processing, archiving, and publication, as well as metadata standards, for various types of commonly integrated marine data (i.e., bathymetric, backscatter, biological, chemical, geological, and physical oceanographic data). The standards are aimed at Florida data producers and users and, as a result, leverage existing state, regional, and national infrastructure. The standards recommendations were shared with the Florida-based stakeholder community to quantify the overall level of agreement, the likelihood of their widespread adoption, and the types of tools needed to increase that likelihood. Overall, the Florida community reported varying but positive agreement with the recommended standards and expressed willingness to adopt them, on the condition that easy-to-use tools and comprehensive documentation are provided to facilitate the implementation. We also found that while relatively few individuals or organizations establish standards themselves, most researchers and users are willing to adopt recommended practices when they are easy and efficient to implement. In an era where scientific data are digitally processed and archived, scientists must foster a culture that consistently shares data, workflows, and use cases. However, this requires tools and accessible resources to facilitate the broader adoption of standards within the scientific community.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[VESA: A Visualization-Enabled Search Application for Exploratory Dataset Discovery]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-034</link>
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            <pubDate>Wed, 26 Aug 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[The increasing complexity and scale of scientific datasets demand advanced tools for efficient discovery and exploration. Traditional search systems often fall short in addressing the multidimensional nature of data and their inherent relationships, limiting their effectiveness for exploratory search. This paper presents the visualization-enabled search application (VESA), a backend-agnostic visual analytics framework that supports interactive and multidimensional exploration of heterogeneous scientific metadata. VESA enables cross-repository data discovery through configurable adapter interfaces that map repository-specific metadata onto a minimal set of common discovery dimensions, enabling seamless ingestion and consistent processing. At the frontend, coordinated visualizations, including spatial, temporal, and relational views, support exploratory search and sensemaking.
To demonstrate the functionality and usefulness of the system, a software prototype is developed and applied to Earth System Science repositories, showing how heterogeneous sources can be integrated and explored through a unified interface. The framework is evaluated against established design guidelines and further validated through an online user study. In addition, adapters for two data repositories are implemented, illustrating how different backends can be connected to the system. Results indicate positive user reception, highlighting VESA’s usability, low learning curve, and its potential to enhance data discovery workflows through interactive visual exploration.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Data Management Challenges for Translational Agricultural Research in West Africa: The Case of the Crops Research Institute, Ghana]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-035</link>
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            <pubDate>Wed, 26 Aug 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[The establishment of robust, long-term data management strategies remains especially challenging in low-resourced and applied research contexts. Drawing on qualitative methods including ethnographic fieldwork and survey data collected from August to December 2023, this paper discusses ongoing concerns around data practices within Ghana’s Crops Research Institute (CRI), a premier West African facility for translational agricultural research. This case exemplifies the concerns emerging from a lively and productive research environment, effectively contributing to basic and applied research for a variety of publics, where, however, the infrastructure is fragile and institutional memory resides mainly in people rather than in computational systems. CRI researchers recognise the key components of effective data stewardship but encounter significant material and administrative obstacles that prevent these ideals from being fully realised. Using social scientific understandings of institutional memory and epistemic cultures, the paper highlights three key reasons for such difficulties: (1) frustrated epistemic cultures, which entrench the community’s difficulties in implementing known necessary practices; (2) data sedimentation, with successive layers of processed and summarised knowledge accumulating on top of earlier research records; and (3) epistemic precarity, that is, a widely perceived gap between understanding what is needed and having the capacity to meet those needs. The picture that emerges is not about insufficient commitment to data sharing and effective long-term management, but rather about structural conditions that make continuity in data practices precarious. If open science aims to effectively engage resource-constrained settings, it must address the lack of relevant infrastructure and administration rather than presuming inadequacies and lack of commitment in research cultures.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Designing Repository-Level Evaluation Criteria: A Data Stewardship Framework for Research Data Repositories]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-033</link>
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            <pubDate>Fri, 21 Aug 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Purpose: This study aims to design comprehensive repository-level evaluation criteria that assess data stewardship capacity, governance structures, and institutional quality control mechanisms in the context of open science and data-intensive research.
Design/methodology/approach: We employed a systematic approach consisting of four stages: formulation of research questions, case study analysis, empirical investigation with expert validation, and framework development through pilot evaluation. We analyzed representative repository-related frameworks and platform-based evaluation guidelines, including the Research Data Alliance (RDA), Confederation of Open Access Repositories (COAR), Science Europe, FAIRsharing, and DSpace, to derive a set of 110 evaluation criteria elements evenly divided between mandatory and optional elements.
Findings: The developed framework emphasizes repository-level stewardship, including governance, preservation, provenance tracking, integrity safeguards, and access infrastructure. Rather than directly assessing the scientific validity of individual datasets, the framework evaluates structural conditions that enable trustworthy and sustainable data management at scale.
Originality: This research validates and provides comprehensive evaluation criteria for data repositories, filling the gap in previous studies. It creates a balanced framework, distinguishing between essential and additional features.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Indigenous Governance of Data Held by Organisations: How to Operationalise Indigenous Data Sovereignty Principles in Australia]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-032</link>
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            <pubDate>Thu, 20 Aug 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Indigenous Data Sovereignty has emerged in response to poor data practices concerning Indigenous Peoples worldwide and offers a way of returning control of data ecosystems to Indigenous Peoples. In Australia, the Maiam nayri Wingara Indigenous Data Sovereignty principles were developed and published in 2018 and as a result, there is a growing body of academic and policy relevant literature on Indigenous Data Sovereignty. There are increasing calls from Aboriginal and Torres Strait Islander communities and their organisations, governments, statistical agencies and universities for practical guidance on how to operationalise Indigenous Data Sovereignty principles through Indigenous Data Governance within data systems controlled outside Aboriginal and Torres Strait Islander communities and organisations. The aim of this paper is to guide how the Maiam nayri Wingara Indigenous Data Sovereignty principles can be applied within organisations creating or holding Indigenous data. This guide can additionally be used to review organisations’ and institutions’ progress on their Indigenous Data Sovereignty journeys.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Navigating Gaps in Governance and Capacity for Equitable and Responsible Data Sharing in Health Research in Sub-Saharan Africa: A Literature Review]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-031</link>
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            <pubDate>Fri, 14 Aug 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Sharing data from diverse sources is essential for addressing grand challenges in global health. The COVID-19 pandemic, which affected populations on a global scale, demonstrated the benefits of data sharing but also exposed some challenges that stakeholders face, such as lack of data interoperability, accessibility and guiding principles for ensuring equitable and responsible sharing when data are distributed across multiple organisations, institutions and ecosystems in multisite studies. In sub-Saharan Africa (SSA), these challenges are compounded by fragmented regulatory frameworks. By examining the legal and regulatory frameworks for equitable health data sharing in selected SSA countries, namely Kenya, Nigeria, Rwanda and South Africa, this review aims to identify good practices and challenges in the health data ecosystem. It then proposes recommendations that can be used to improve the legal and regulatory frameworks for health research in the region. The review also highlights lessons that may be learned from the selected country case studies by countries seeking to reform their data policy and privacy governance frameworks.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[The JARDIN Hackathon to Seek Solutions to Overcome Technical Barriers in Health Data Exchange: From the Point of Care to European Registry Networks]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-029</link>
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            <pubDate>Wed, 12 Aug 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Effective exchange of health data between healthcare providers, national registries, and European Reference Networks (ERNs) is crucial for advancing research and clinical care of rare diseases. Technical, organisational, and legal barriers persist in many situations that disrupt this process. The Joint Action on Integration of ERNs into National Healthcare Systems (JARDIN) tackles these barriers by identifying such existing solutions. At the technical level, there are existing standards, software, and infrastructures that could be adapted and reused if there were evidence of a method and value in doing so. These need to be identified, matched against known problems, and tested before subsequent work can begin to evaluate and deploy solutions. This paper describes the methodologies and outcomes of a hackathon conducted as a software-oriented workshop to collaboratively identify and implement solutions to technical barriers identified as relevant to rare diseases. The event brought together 47 experts from 10 European countries to combine their knowledge and experience to tackle challenges of data harmonisation, secure data access, and the Findable, Accessible, Interoperable and Reusable (FAIR) description of data services. Motivated by a simple use case, the participants proposed adapting existing infrastructures to create a realistic, secure data-sharing architecture based on existing standards. Solutions included federated querying of rare disease data integrated with a standard for data access conditions, the use of semantic models for rare disease data harmonisation across organisations, and extending a standard metadata model to better describe rare disease data being held by organisations. The process of expert-driven selection of the components yielded approaches relevant for the rare disease community and has provided important momentum. As an output of the JARDIN initiative, this will lead to further real-world evaluation and pilot testing together with rare disease data stakeholders and ultimately EU-wide recommendations that will benefit coordination and focus on improving data exchange.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[A Semantic Web Model for Standardizing FAIR Metrics and Assessment Results]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-030</link>
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            <pubDate>Wed, 12 Aug 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[This study proposes a web standards-based semantic model for representing FAIR (Findable, Accessible, Interoperable, Reusable) metrics and FAIR assessment results. Building on existing recommendations for the publication of data quality information on the Web, in particular the W3C Data Quality Vocabulary (DQV) and related ontologies, we examine to what extent these standards are applicable to FAIR assessments. Based on a comparative analysis of the output formats of existing FAIR assessment tools, we identify core requirements for a harmonized representation of FAIR metrics and results. On this basis, we propose a semantic model that integrates established vocabularies to describe both FAIR metrics and their corresponding assessment outcomes. The model is presented together with an exemplary implementation for the F-UJI assessment tool and demonstrates how web standards can support holistic, machine-actionable analyses of FAIR assessments across different tools.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Persistent Identifiers in Germany: Key Findings of a Nationwide Survey]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-028</link>
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            <pubDate>Mon, 10 Aug 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Persistent identifiers (PIDs) are global, unique, resolvable, and persistent references that have become core components of open science and FAIR research as well as their infrastructures. This article reports key findings from the first nationwide Survey on the Need for and Use of Persistent Identifiers at Research and Infrastructure Organizations in Germany.
This survey is based on a cross-sectional, cross-disciplinary online survey covering more than 20 PID types and established entity categories, targeting all relevant public-sector academic and non-academic research organizations in Germany as well as European and international research infrastructure nodes headquartered in Germany.
Responses from a diverse set of academic and non-academic research and infrastructure organizations provide an empirical basis for analyzing PID familiarity and use, training needs, infrastructural embedding, and strategic framework conditions. The findings indicate that PID adoption is currently concentrated on a limited set of widely established identifiers (DOI, ISBN, ORCID iD, GND, URN), whereas newer or specialized identifiers remain less recognized and are infrequently implemented. PID usage predominantly occurs within publication and research data workflows, with anticipated expansion to additional entity types such as research software and instruments. Across organizations, respondents strongly point out high-quality, interoperable metadata as a precondition for sustainable PID integration, yet many report capacity and governance constraints, including limited institutional training and guidance, insufficient expertise and personnel, and uncertainty about benefits. This survey delivers a comprehensive, empirical dataset for systematic analysis, a first in this field.
A key opportunity is to enhance the efficiency and potency of managing, ensuring the traceability of, and monitoring of research activities across academic and non-academic organizations in Germany. The findings provide an evidence-based foundation for developing a national PID roadmap by highlighting the current level of usage, existing practices, and gaps. They also highlight objectives for strengthening Germany’s PID ecosystem, including better alignment of advisory and training resources with the needs of scholarly communities and the systematic integration of PIDs into digital strategies to advance Germany’s digital transition toward more interoperable national and European research infrastructures.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Automated Retrieval and Analysis of Finnish Cultural Metadata with finna]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-027</link>
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            <pubDate>Fri, 24 Jul 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Cultural metadata is essential in making cultural heritage resources discoverable, accessible, and understandable. However, such metadata is often difficult to access and reuse due to its heterogeneous structure and scattered sources. Cultural heritage metadata usually contains structured information on art, literature, music, and scientific collections. It serves as a powerful research object for understanding trends, representations, and societal impacts over time. Despite the growing availability of such datasets, there remains a lack of targeted computational tools and workflows to integrate them into analytical environments. Finna is a national search platform developed by the Finnish Ministry of Culture and Education that provides unified access to millions of metadata records from Finnish libraries, museums, and archives. We introduce the finna R package, which provides a seamless interface to these services and bridges the gap between accessible cultural metadata and its computational analysis. The package allows researchers to query, retrieve, and clean Finnish cultural heritage metadata programmatically, automate workflows, and integrate the results into R for visualization and further analysis.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Insects in the Mail, a Quantitative Analysis of Charles Robertson’s Scientific Correspondence]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-026</link>
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            <pubDate>Fri, 17 Jul 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Charles Robertson (1858–1935), a biology professor based in Carlinville, Illinois, conducted a decades-long study recording interactions between species of insects and flowering plants within a 10-mile radius of his home. His records have enduring value as legacy data and provide invaluable insights into an ecosystem that can never be observed firsthand again. However, consistent with the typical scientific practices of his time, Robertson’s publications leave gaps in the information required by scientists reusing his work today. One key source of context for his published findings is his archived correspondence, part of the Charles Robertson Papers at the University of Illinois Archives. His correspondence documents when, where, how, and with whom he exchanged thousands of insect specimens. This paper presents the results of a quantitative analysis of data extracted from Robertson’s correspondence, which provides some of the contextual and methodological information missing from his published works. This analysis demonstrates the essentially collaborative nature of Robertson’s research, the contributions of his collaborators, the challenges of species determination, and the value of considering specimen exchange in analyses of scientific correspondence. The connections documented in this correspondence made his landmark study possible by pooling expertise that was distributed across four decades and throughout the U.S. and Canada. The associated dataset makes that correspondence analyzable and indexes items, correspondents, and specimens to the digitized records, making the original materials more accessible and navigable.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Work Plans: A Tool for Suggesting Implementation Strategies to Improve the FAIRness of Data Repositories]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-025</link>
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            <pubDate>Thu, 16 Jul 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Improving the findability, accessibility, interoperability, and reusability (or ‘FAIRness’) of digital resources has become increasingly important since the publication of the ‘FAIR Principles’ in 2016. As an advocate of the FAIR Principles, GO FAIR US has developed a methodology for assessing the FAIRness of repositories. Through involvement in a myriad of data landscaping projects across health research and the geosciences, GO FAIR US’s analytical approach has been tested, improved, and demonstrated to be a valuable practice. Crucially, GO FAIR US’s approach focuses on the need to gather feedback from repositories and from the stakeholders involved in said repositories. In this paper, we describe a way to organize and present the rich data collected into Work Plans that clearly convey changes recommended through the FAIRness assessment process.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[A Structured Examination of Reproducibility: A Case Study for HTS Using the PRIMAD Model and BioCompute Object]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-024</link>
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            <pubDate>Tue, 14 Jul 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Reproducibility is a core expectation of computational pipelines in biomedical research, particularly in health-critical applications. To support the standardised reporting of high-throughput sequencing (HTS) analyses, the IEEE 2791-2020 standard, known as the BioCompute Object (BCO), was developed with support from the U.S. Food and Drug Administration. While the BCO serves as a pragmatic framework for documenting pipelines and is intended to improve transparency and reproducibility, its claims of reproducibility have not been systematically evaluated.
This study employs the PRIMAD (Platform, Research objectives, Implementation, Methods, Actor, Data) model, a conceptual framework for describing computational experiments for reproducibility purposes, to systematically review the BCO in terms of depth and coverage. A systematic mapping of BCO and PRIMAD elements onto a published BCO use case, accompanied by a quantitative scoring rubric to evaluate the completeness of the mapping, highlights potential omissions and necessary enhancements in both frameworks. This emphasises the significance of systematically validating claims of reproducibility for published digital objects, thereby enhancing the reliability of scientific research in bioscience and related fields.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[MatSci-YAMZ: Integrating Human and Artificial Intelligence Vocabulary]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-023</link>
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            <pubDate>Mon, 13 Jul 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[This paper presents MatSci-YAMZ, a novel implementation of Yet Another Metadata Zoo (YAMZ), a crowdsourced vocabulary application. MatSci-YAMZ is designed to assist vocabulary development for materials science by configuring a large language model (LLM) and provenance tracking into the YAMZ workflow. Implementation of MatSci-YAMZ occurred in three phases: requirements and model selection, development, and fine-tuning. The application utilizes the Gemma3:27b LLM to formulate definitions based upon examples provided with human definitions. Provenance tracking captures the evolution of LLM-generated definition evolution, which occurs in response to user comments. MatSci-YAMZ can improve shared semantics among communities of materials researchers whose terminology may contain nuances or idiosyncratic usages. Improved semantic alignment supports more concise data descriptions and use of metadata, which is foundational to supporting the FAIR principles of findability, accessibility, interoperability, and reusability. Improved provenance tracking also provides greater insight into how researchers engage with LLM-generated definitions as well as the changes that occur. MatSci-YAMZ opens several avenues of research into crowdsourced vocabulary development among materials researchers. Current findings highlight the need for additional user testing and study to better understand human-in-the-loop vocabulary development with existing LLMs.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Indigenous Data Governance – Laying the Groundwork for a Broader Dialogue in the Aftermath of Truth and Reconciliation Committees in Sápmi]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-022</link>
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            <pubDate>Fri, 10 Jul 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[Context: Open science is gaining ground and aims to build trust and transparency in research through the FAIR principles (Fairness, Accessibility, Interoperability, and Reusability of data). The GIDA-Sápmi network advocates for an ethical and responsible use/reuse of research data and promotes the operationalisation of the CARE principles (Collective Benefit, Authority to Control, Responsibility, and Ethics) to Sámi research data.
Rationale: Research data are attached to a context and people, and the open data practice needs to address the social dimensions of data, which the FAIR principles overlook, and the CARE principles address. The first cross-national Sámi Science Week (2025) hosted two panels, where Sámi research data governance was addressed. This commentary summarises the panels, that is, the concerns raised with open data and solutions for how to apply this for Sápmi.
Findings: Key themes that emerged from the panels were the need for Sámi-specific governance principles, the development of Sámi-specific governance protocols, and the use of Sámi AI to support language revitalisation and culturally sensitive healthcare tools. However, concerns were raised about the risks of data misuse when data is outside Sámi control and management—in particular, in the recent data-driven technological advancements. The panels concluded that Sámi data governance is essential for ethical and responsible research practice, but this requires clear governance protocols that respect Sámi interests and Sámi epistemologies. Whilst challenges remain, the panel calls for the development of practical solutions for Sámi data governance, contributing to responsible and ethical use and reuse of data.]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Universal Mandates vs. Contextual Realities: A Scoping Review of Ethical Tensions and Power Asymmetries in Global Open Science]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-021</link>
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            <pubDate>Mon, 15 Jun 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[The global diffusion of open science is widely promoted as a pathway to transparency and the democratisation of knowledge production. However, growing evidence shows that universal openness mandates often conflict with diverse cultural, institutional, and socio-economic contexts, generating ethical tensions and reinforcing existing power asymmetries. This scoping review maps the ethical, governance, and equity implications of open science across heterogeneous research environments. Guided by PRISMA-ScR protocols and preregistered with the Open Science Framework, the review analysed 33 appraised studies published in multidisciplinary databases and grey literature. A three-dimensional analytical framework was developed comprising the Ethical Tension Index (ETI), Governance Maturity Level (GML), and Implementation Equity Score (IES). Findings indicate that ethical conflicts are systemic, arising where transparency norms intersect with collective ownership traditions, Indigenous data sovereignty, and resource disparities. Article processing charges, infrastructural gaps, and commercial platform control were major drivers of epistemic exclusion, particularly for Global South institutions. Most initiatives remain in the early governance maturity stages, characterised by compliance-driven policies with limited stakeholder participation. In contrast, equity-oriented models demonstrate higher governance maturity and improved equity outcomes. The study concludes that responsible global open science requires a shift from universalist mandates to pluralistic, context-sensitive governance frameworks that prioritise community authority.]]></description>
            <category>ARTICLE</category>
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            <title><![CDATA[FAIR Data in Action: The User-Centric Software Suite FAIRSave for Fully Digital, Data-Driven Studies in Materials Science]]></title>
            <link>https://reference-global.com/article/10.5334/dsj-2026-020</link>
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            <pubDate>Wed, 10 Jun 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[The increasing demand for FAIR (Findable, Accessible, Interoperable, Reusable) research data challenges experimental scientists to integrate structured data management directly into daily laboratory work. However, practical adoption is often hindered by high documentation effort, limited usability, and insufficient integration with experimental workflows. We present FAIR-Save (FS), a Python-based user-centered suite that extends the electronic lab notebook Kadi4Mat with controlled vocabularies (VocPopuli), guided record creation (FS-DigitalBook), quality checks (FS-Validator), and seamless instrument integration (FS-Instrument). The suite captures metadata at the bench, supports offline work, and generates QR code-based labels to ensure error-free linking of samples, processes, and files.
By using simple vocabularies rather than complex ontologies, FAIR-Save accelerates the creation of consistent metadata while fully complying with FAIR requirements. The activity of our research group demonstrates the impact of the FAIR-Save suite’s graphical user interface through the increased number of yearly recorded processes from 45 to over 2,000. The introduction of both FS-DigitalBook and key features for visualization significantly improved user adoption.
FAIR-Save reduces documentation burden and improves data consistency. These results demonstrate that a user-friendly, automated system can substantially raise the adoption of FAIR principles, thereby supporting open-science objectives and accelerating data-driven discovery.]]></description>
            <category>ARTICLE</category>
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