We evaluate an intervention designed to give lab-based research teams an opportunity to intentionally discuss project-related data management practices within their labs, examining how such communication might inform perceptions of the relationship between formal data management plans and lab members' day-to-day data management practices. In an earlier study, we developed a lab-based intervention that encouraged a deliberative approach to discussions among lab members regarding the practices of data management and authorship, and an exploration of the ethical dimensions of those practices. This present study builds on this prior work, both as partial replication and extension. Here we show the significant effects of the intervention across several dimensions, but importantly and specific to this project, this deliberative communication approach enhances the likelihood that lab members share an understanding of and a commitment to its data management practices, in part because they have been actively involved in shaping those practices. Fostering shared understanding and commitment is crucial for maintaining rigor and responsibility across all aspects of a lab's work, and is essential for cultivating legitimate, defensible, and ethical approaches to producing scientific knowledge.

Probiotic Human Study Design and Reporting (PRODARE): Recommendations to Improve Research Practice.

A multidisciplinary collaboration is needed to improve antiretroviral (ARV) therapy adherence among people with HIV (PWH) to ensure adequate patient outcomes. The AdhereP4 program was a collaboration among pharmacies, prescribers, payers, and public health agencies that identified PWH with a ≥30-day gap in ARV access using pharmacy claims data. While pharmacy claims data are useful for identifying adherence gaps, limited guidance exists on structures and processes needed to integrate such data in pharmacy and clinical services to better provide adherence support. The AdhereP4 program identified key programmatic structures and processes for a successful collaboration of pharmacy claims data with dispensing pharmacy and clinical patient data. Structures include staffing, data, and procedures while programmatic processes include adherence assessment, adherence intervention, and training/communication. AdhereP4 implementation required support from an information technologist, database managers, programmers, pharmacists, clinicians, social workers/case managers, and a public health specialist. Key lessons learned from the development and implementation of the AdhereP4 program were identified through monthly collaborator meetings and informal collaborator interviews. Lessons identified included (1) develop support and training for all collaborators; (2) develop a data dictionary for each site prior to data collection; (3) develop a standard operating procedure manual related to data management; and (4) complete periodic review of data to address any concerns early. Monthly pharmacy claims data can be successfully used by pharmacy and clinic staff to identify and address ARV adherence gaps. Successful implementation requires collaboration across stakeholders and a clear data management plan.

ABSTRACT This study investigates the Research Data Management (RDM) skillsets and competencies of library professionals within North Indian university libraries. Employing a survey method, data was collected from professionals, resulting in an 84% response rate. The data, analyzed using SPSS. The study reveals that a significant number of library professionals require further development in several key areas. These include awareness of new government initiatives (e.g. Shodh Chakra), proficiency in metadata creation (e.g. using Dublin Core standards), and advanced technical ICT skills (e.g. data storage infrastructure and architecture). Additionally, there is a need for enhanced subject-specific knowledge, familiarity with various research methods (e.g. data analysis and visualization), and competencies in data description, documentation, and curation. The study also highlights the importance of skills related to developing Data Management Plans (DMPs), staying current with RDM trends through refresher courses, utilizing originality checking tools, and understanding legal, policy, and advisory aspects (e.g. intellectual property, ethics, and licensing). This research underscores the critical need for ongoing professional development to equip library professionals with the necessary competencies to effectively support RDM practices in academic environments.

In January 2022, Italy fully implemented EU Regulation No. 536/2014, revolutionizing the national framework for clinical research on medicinal products. This marked a critical shift for non-profit sponsors, who are now required to align with high-quality standards and ICH-GCP guidelines. Understanding their level of compliance is essential to identify systemic barriers and areas needing support. In March 2024, a 50-item anonymous pilot survey was distributed via social media to assess the operational and regulatory compliance of non-profit sponsors managing clinical trials in Italy. The survey focused on three domains: data management, risk assessment, and monitoring practices. Responses were collected from 32 non-profit sponsors. The findings revealed substantial compliance gaps. Approximately 91% (n = 29) of respondents reported they rarely or never prepare core GCP-required documents, including Data Management Plans and Statistical Analysis Plans. Only 25% (n = 8) routinely conduct risk assessments before protocol drafting. Monitoring visits, either remote or on-site, were performed by 63% (n = 20) of sponsors. Among those not conducting on-site monitoring (n = 14), the primary constraints reported were staff shortages (29%, n = 4) and financial limitations (57%, n = 8). Alarmingly, within this same subgroup, 29% (n = 4) believed that on-site monitoring was unnecessary, despite regulatory mandates. This attitude extended to remote monitoring activities as well. The survey highlights major challenges faced by non-profit sponsors in meeting regulatory expectations. Limited resources and a lack of trained personnel significantly impair compliance with GCP standards. To ensure research integrity and patient safety, targeted support strategies and policy interventions are urgently needed to empower non-profit research in adapting to the evolving regulatory landscape.

Research data management plays a key role in ensuring research reproducibility and transparency by supporting data sharing in line with Open Science principles. Professional figures supporting data management practices, such as data stewards, are emerging in the international landscape, following different paths. The Italian Computing and Data Infrastructure, with the support of the Skills4EOSC project, conducted a national survey between April and December 2023 to map the presence, roles, and activities of data stewards or equivalent professionals across universities and research institutions, to provide an initial and systematic overview of the national landscape, which is known to be fragmented and lacking of clear professional recognition for research support professionals. The survey, administered in Italian through the EUSurvey platform, consisted of 13 closed-ended questions addressing institutional organisation, professional background, and support activities related to research data management. Data cleaning was performed on the 77 valid entries collected (out of 88 responses) before conducting the descriptive analyses. Results indicate that most institutions employ staff performing data management support tasks which map to the definition of data stewardship, though these professionals are rarely formally recognised with that title. Hence, the variety of job titles observed reflects the absence of a standardised professional profile. Among the data management support tasks investigated, the most common include FAIR data management support, data management plan writing, researcher training, and policy consultancy. These findings provide the basis to establish the Italian Data Steward Community in order to overcome the fragmentation through peer-to-peer knowledge sharing and support, and to advance the definition of a professionalisation pathway for data stewards in Italy. The findings of this survey can serve as a case study to help data stewards, research data professionals, and policymakers in other countries to map and understand their local landscape.

Research data management plays a key role in ensuring research reproducibility and transparency by supporting data sharing in line with Open Science principles. Professional figures supporting data management practices, such as data stewards, are emerging in the international landscape, following different paths. The Italian Computing and Data Infrastructure, with the support of the Skills4EOSC project, conducted a national survey between April and December 2023 to map the presence, roles, and activities of data stewards or equivalent professionals across universities and research institutions, to provide an initial and systematic overview of the national landscape, which is known to be fragmented and lacking of clear professional recognition for research support professionals. The survey, administered in Italian through the EUSurvey platform, consisted of 13 closed-ended questions addressing institutional organisation, professional background, and support activities related to research data management. Data cleaning was performed on the 77 valid entries collected (out of 88 responses) before conducting the descriptive analyses. Results indicate that most institutions employ staff performing data management support tasks which map to the definition of data stewardship, though these professionals are rarely formally recognised with that title. Hence, the variety of job titles observed reflects the absence of a standardised professional profile. Among the data management support tasks investigated, the most common include FAIR data management support, data management plan writing, researcher training, and policy consultancy. These findings provide the basis to establish the Italian Data Steward Community in order to overcome the fragmentation through peer-to-peer knowledge sharing and support, and to advance the definition of a professionalisation pathway for data stewards in Italy. The findings of this survey can serve as a case study to help data stewards, research data professionals, and policymakers in other countries to map and understand their local landscape.

Data Management Plans (DMPs) are relevant documents that help ensure data integrity and transparency. In this study, we analyze tools for constructing DMPs based on the fundamental aspects needed for proper scientific data management. Our methodology includes an extensive literature review and a detailed, hands-on analysis of selected DMP tools, including DMPTool, DMPonline, PGD-BR, DS-Wizard, and OpenDMP. We evaluate these tools against a refined set of criteria organized into subcategories, focusing on their practical implications for researchers, such as the level of repository integration, support for machine-actionable outputs, and customization capabilities. The results indicate that, despite practical challenges, these tools can improve data management, promote transparency, and increase the reproducibility of scientific research. This paper provides a decision matrix with a clear scoring system for tool selection, practical application scenarios, and strategic recommendations for stakeholders. The study concludes that adopting well-designed DMP tools is fundamental for sustainable scientific data management and highlights the need for continued investment in specialized training and the development of tools to meet emerging challenges, particularly in automation and interoperability. Publisher’s Note: A correction article relating to this paper has been published and can be found at https://datascience.codata.org/articles/10.5334/dsj-2026-011.

Model-informed drug development is increasingly integrated across the drug development continuum, enabling more efficient, cost-effective, and targeted trials while reducing reliance on animal studies. Achieving pharmacoequity requires not only equitable access to medicines but also to the data and knowledge that inform drug development and regulatory decisions. To address challenges in pharmacokinetic data sharing, PKRxiv (https://pkrxiv.org/) was developed as a discipline-specific repository designed around Findable, Accessible, Interoperable, Reusable (FAIR) principles. This tutorial introduces PKRxiv's rationale, design, data submission and access workflows, and practical use cases. Available datasets at the end of September 2025 include over 5,500 individual drug concentration-time data points from over 900 unique participants across 3 continents. The platform supports structured submission of pharmacokinetic, pharmacogenetic, and safety/efficacy data, with persistent digital object identifiers for discoverability and citation. Contributors can apply one of three data sharing models-unrestricted, noncommercial, or contributor-controlled-with optional embargo periods. Users can explore datasets using the Data Explorer or Data Cards, or submit requests after providing a statement of intended use case. It enables pooling of datasets across multiple studies. Recommendations to help advance the field are proposed as data sharing becomes more widely expected: obtaining consent for unspecified future research use of data, sharing data underlying peer-reviewed publications as standard practice, including discipline-specific repositories in data management plans, and incentivizing post-approval data sharing by industry. Supporting data from all therapeutic areas and population groups, PKRxiv is a critical step toward a more transparent, equitable, and collaborative future in clinical pharmacology research.

Introduction Immersive technologies enabled by AI present latent risks to human subjects’ protections in research settings. Standard methods of ensuring confidentiality, data management, and safety do not fully encompass the scope of data types, data flow, and user experience. A comprehensive take on risk assessment and mitigation strategy is warranted. Methods 100 research compliance officers analyzed three case studies (Biodata, Haptics, Motion Tracking) in a structured sequence (Open Inquiry, Technical Analysis, Risk Assessment, Mitigation Strategies). The text responses to the questions were thematically coded and summarized in the context of the review criteria (Data Management, Informed Consent, Safety, and Training). Results Biodata case study presented challenges in psychological safety that could be mitigated with improved withdrawal procedures. Haptics introduced novel physical safety concerns with direct brain stimulation, which called for thorough training of study personnel. Motion-tracking exposed the difficulty of anonymization, which may require enhanced data security measures in the data management plan. Discussion The technical depth of knowledge impacted compliance officers’ analysis of the case studies. Yet when informed, the adapted application of human subjects’ protections policies could capture much of the latent risk. The proposed review criteria establish a structure to assess research practices with immersive technology.

The South Asian American (SAA) community often encounters substantial traumas and reports distress after these experiences. Simultaneously, many SAAs underutilize mental health services. Two significant factors contributing to such disparities in access to care are the lack of (a) culturally responsive traumatic stress interventions for SAAs and (b) SAA-specific methodological structures to be used in traumatic stress intervention research. Thus, we outline a methodological protocol article based on process-oriented insights to develop culturally responsive traumatic stress interventions for SAAs, focusing on centering community voices to understand the experience of trauma and its impacts within the cultural context of this community. We delineated steps, considerations, and lessons that we learned in the process, specifically how to (a) develop a collaborative team with a specific range of stakeholders and to integrate their input, (b) create and implement a study protocol and data management plan, and (c) devise and roll out a culturally informed participant recruitment and retention protocol. Using our work in this community as an example, we highlight the strengths of the methodological approach taken and areas that would be important to address in future work with SAAs. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

BackgroundEvaluating implementation of digital health interventions (DHIs) in practice settings is complex, involving diverse users and multistep processes. Proactive planning can ensure implementation determinants and outcomes are captured for hybrid studies, but operational guidance for designing or planning hybrid DHI studies is limited.ObjectiveThis study aimed to proactively define, prioritize, and operationalize measurement of implementation outcomes and determinants for a DHI hybrid effectiveness-implementation trial. We describe unique advantages and limitations of planning the trial implementation evaluation among a large-scale cohort study population and share results of a pretrial organizational readiness assessment.MethodsWe planned a cluster-randomized, type II hybrid effectiveness-implementation trial testing PositiveLinks, a smartphone app for HIV care, compared to usual care (n=6 sites per arm), among HIV outpatient sites in the DC Cohort Longitudinal HIV Study in Washington, DC. We (1) defined components of the DHI and associated implementation strategy; (2) selected implementation science frameworks to accomplish evaluation aims; (3) mapped framework dimensions, domains, and constructs to implementation strategy steps; (4) modified or created instruments to collect data for implementation outcome measures and determinants; and (5) developed a compatible implementation science data collection and management plan. Provider baseline surveys administered at intervention sites probed usage of digital tools and assessed provider readiness for implementation with the Organizational Readiness to Implement Change tool.ResultsWe specified DHI and implementation strategy toward planning measurement of DHI and broader program reach and adoption. Mapping of implementation strategy steps to the Reach Effectiveness Adoption Implementation Maintenance framework prompted considerations for how to capture understudied aspects of each dimension: denominators and demographic representativeness within reach or adoption, and provider or organization-level adaptations, dose, and fidelity within the implementation dimension. Our process also prompted the creation of tools to obtain detailed determinants across domains and constructs of the Consolidated Framework for Implementation Research within a large sample at multiple time points. Some aspects of real-world PositiveLinks implementation were not reflected within the planned hybrid trial (eg, research assistants selected as de facto site implementation leads) or were modified to preserve internal validity of effectiveness measurement (eg, “Community of Practice”). Providers and research assistants (n=17) at intervention sites self-reported high baseline use of digital tools to communicate with patients. Readiness assessment revealed high median (48, IQR 45‐54) total Organizational Readiness to Implement Change scores, with research assistants scoring higher than physicians (52.5, IQR 44-55 vs 48.0, IQR 46-49).ConclusionsKey takeaways, challenges, and opportunities arose in planning the implementation evaluation within a hybrid DHI trial among a cohort population. Prospective trial planning must balance generalizability of implementation processes to “real world” conditions with rigorous procedures to measure intervention effectiveness. Rapid, scalable tools require further study to enable evaluations within large multisite hybrid studies.

This chapter provides a comprehensive overview of FAIR principles applied to omics data management, addressing key challenges in handling large-scale, heterogeneous datasets while promoting reproducibility, collaboration, and open science practices. It covers essential strategies including Data Management Plans (DMPs), file organization, metadata standards, ontologies, repository selection, interoperability protocols, and security measures for privacy and ethics compliance. Best practices are outlined for achieving Findable, Accessible, Interoperable, and Reusable data, with recommendations for continuous improvement to support cross-omics integration and long-term data stewardship.

The concept of the ‘teaching library’, which originated in the Anglo-American world, describes all activities of libraries in the field of promoting information, media, and data literacy, as well as other skills in dealing with analog and digital media. Although data literacy is explicitly mentioned in this definition, many training courses in academic libraries seem to focus more on promoting library use, information, and media literacy. Given that the creation of data management plans, along with the indexing, storage, and reuse of research data, have become standard elements of the research process, this article discusses the growing importance of academic libraries in teaching data literacy. It presents a modular course framework, developed in exchange with the university library, as a reusable model for data literacy education. The primary objective is to introduce this framework and illustrate its application; preliminary, exploratory insights from a self-assessment survey are provided to support this presentation. The limited participant count in the pre- and post-evaluations restricts the statistical generalizability of the findings but provides a solid empirical impression of the effectiveness of the course format. Results indicate substantial learning progress in fields where academic libraries have proven expertise. The main conclusion is that such library-integrated interdisciplinary courses provide a valuable framework for data literacy education and highlight strategic areas for library involvement.

Objective. To examine the attitudes of Ukrainian researchers toward open access principles, open science, and research data management, as well as the role of libraries in promoting open science principles and practices, based on selected results from a sociological survey conducted by the State Scientific and Technical Library of Ukraine in April-August 2025. Methods. The study involved 702 respondents from various scientific disciplines and academic institutions, with librarians comprising nearly 10% of participants. The survey aimed to assess awareness levels, current practices, and readiness to implement open science approaches. Results. The findings demonstrate generally positive attitudes toward open access and open science while revealing limited practical implementation due to infrastructural, regulatory, or cultural barriers. Researchers identified key obstacles to sharing publications and data: lack of technical knowledge, uncertainty about legal aspects, absence of clear institutional policies, and inadequate organizational infrastructure. The survey also revealed significant gaps in researchers' knowledge regarding data management planning and FAIR principles. Academic libraries can and should fill these gaps as key intermediaries in the transition to open science through comprehensive researcher support: advocacy, training, consulting, development of publication and data repositories, assistance in creating metadata and data management plans. Conclusions. Academic libraries in Ukraine continue to actively participate in building open science and implementing its principles and practices. However, to ensure an effective transition to open science, they need to strengthen their role or even lead processes of creating and implementing institutional policies and data management infrastructure, developing systematic training, and providing comprehensive support to researchers at all stages of the research lifecycle.

Water utilities are vital for urban health and economic growth, but face sustainability challenges, especially in low- and middle-income countries. In Nigeria, despite long-term investment, urban water utilities struggle with operational inefficiencies, frequent service interruptions, high non-revenue water, and low customer satisfaction. This study examined how performance monitoring can improve the operational sustainability of State Water Utilities in Nigeria. The objectives were to assess institutional performance monitoring practices and to evaluate the use of key performance indicators in tracking operations. A mixed-methods, cross-sectional case study was conducted in six urban utilities across six states. The data was collected in September 2022 through document re-views, structured questionnaires, and in-depth interviews. Descriptive statistics was used to analyze quantitative data; NVivo facilitated qualitative thematic analysis. Findings show all utilities have functional M&E departments responsible for performance monitoring activities, but M&E plan implementation varies (50%), with notable capacity gaps, inconsistent data management (only one utility has a Data Management Plan), and 7–22 indicators per utility. Baseline and target-setting are weak (pre-sent in 50% of utilities), and dissemination beyond internal reporting is limited. Recommendations include institutional reforms, capacity development, allocating 10% of budgets to performance monitoring, and embedding adaptive learning to enhance sustainability, effectiveness, and public trust.

Heritage data management has become increasingly critical as regeneration initiatives generate vast quantities of digital information, yet systematic approaches to data governance remain inconsistent across the sector. This paper examines heritage data practices within England’s High Street Heritage Action Zone (High Street HAZ) programme, focusing on case studies from Northallerton, Kirkham, and Chester. Through semi-structured interviews, questionnaires, and data audits conducted between 2021–2024, this research investigates how heritage datasets are created, shared, and preserved within planning processes, community wellbeing initiatives, and heritage research projects. Key findings reveal widespread data reuse across all programme strands, alarmingly low awareness of Data Management Plans (DMPs), and fragmented approaches to data sharing and preservation. The study uncovers significant disparities between above-ground and below-ground archaeological data management, with the former lacking systematic archival requirements despite comparable heritage value. Commercial intellectual property practices often conflict with public access principles, whilst community-generated datasets face particular vulnerability without institutional support. The research demonstrates that easily accessible datasets are routinely reused whilst those requiring specialist access remain underutilised, highlighting the critical importance of data discoverability. The paper advocates for mandatory DMPs, hybrid governance models balancing local autonomy with national oversight, and clear intellectual property frameworks ensuring public benefit from publicly funded research. These findings contribute to emerging debates on digital heritage governance, offering evidence-based recommendations for improving data stewardship in heritage-led regeneration initiatives.

This article presents an analysis of research data management (RDM) practices at the University of Bologna (UniBO). It is based on qualitative data manually collected from 29 data management plans (DMPs) and recorded within a table based on 27 relevant ‘DMP variables’. The study examines aspects such as data types and formats, handling of personal data, and repository selection for long-term preservation. Using descriptive statistics, we address three core questions: (1) What is the diversity of research data managed at UniBO? (2) What recurring challenges and patterns can inform data stewardship services? (3) Is there evidence of interdisciplinary data production? Findings reveal significant overlaps across disciplines in terms of data types and formats, with limited emphasis on data reuse, while common challenges include confidentiality, privacy protection, intellectual property rights, and long-term preservation. The results underscore growing awareness of RDM and provide insight on the type of institutional training and support that should be prioritized to address emerging needs.

This paper introduces an energy-efficient communication structure and an independent data management plan for Wireless Sensor Networks (WSNs) in a real-time psychology class setting. Since the contemporary classroom is becoming highly dependent on the continuous collection of physiological and behavioral data, including engagement tracking, cognitive-load measurement, emotional-state detection, etc., the provision of sustainable, low-power, and self-organizing sensing systems is becoming an urgent issue. The suggested framework incorporates adaptive duty cycling, context-sensitive routing, and lightweight data aggregation to drastically reduce power consumption while preserving high data fidelity and low latency. Real-time preprocessing, noise filtering, and event-driven data prioritization are enabled by an autonomous data management layer backed by edge-level intelligence, ensuring that only valid data is transmitted to the centralized analysis unit. The protocol also includes predictive load balancing to increase network durability and fault resilience when used in dynamic classroom applications. Simulated psychology-class environment experimental assessments show significant enhancements in network lifetime, lower communication overhead, and consistent real-time performance across changes in student activity levels. The paper notes the possibility of intelligent WSN design to support emerging real-time psychological analytics, enabling more responsive, data-driven, and energy-aware learning settings.

The use of WebGIS in urban land planning and management has become a global trend. A Web-GIS system was developed specifically for planning management at HUCE’s Campus 2. While not yet fully complete, the findings indicate that this system has provided substantial support to stakeholders, including local authorities, planners, and the broader community. Through efficient data management and analysis, the WebGIS system has facilitated timely monitoring and adjustments during the construction process, while also enabling comprehensive modifications to land planning. Additionally, its field interaction function gathers valuable information for detecting damages requiring repair and maintenance, along with updates on the status of areas where land use rights have not yet been transferred. Despite certain limitations, such as challenges in integrating 3D model data and enhancing public consultation methods, the incorporation of these research findings offers significant potential to improve the effectiveness of urban land planning and management in the future.