Data Curation, Open Data, and Research Data Management – Page 5

"Towards a Quality Indicator for Research Data Publications and Research Software publications — A Vision from the Helmholtz Association"

Research data and software are widely accepted as an outcome of scientific work. However, in comparison to text-based publications, there is not yet an established process to assess and evaluate quality of research data and research software publications. This paper presents an attempt to fill this gap. Initiated by the Working Group Open Science of the Helmholtz Association the Task Group Helmholtz Quality Indicators for Data and Software Publications currently develops a quality indicator for research data and research software publications to be used within the Association. This report summarizes the vision of the group of what all contributes to such an indicator. The proposed approach relies on generic well-established concepts for quality criteria, such as the FAIR Principles and the COBIT Maturity Model. It does — on purpose — not limit itself to technical implementation possibilities to avoid using an existing metric for a new purpose. The intention of this paper is to share the current state for further discussion with all stakeholders, particularly with other groups also working on similar metrics but also with entities that use the metrics.

https://arxiv.org/abs/2401.08804

"Data Stewardship: Case Studies from North-American, Dutch, and Finnish Universities"

This work seeks to elaborate the picture of different data stewardship programs running in different institutional arrangements and research environments. Design/methodology/approach – Drawing from autoethnography and case study methods, this study described three distinct data stewardship programs from Purdue University (United States), Delft Technical University (Netherlands) and Aalto University (Finland). In addition, this work investigated the institutional arrangements and national research environments of the programs. The focus was on initiatives led by academic libraries or similar services. Findings – This work demonstrates that data stewardship may be understood differently within different national and institutional contexts. The data stewardship programs differed in terms of roles, organization and funding structures. Moreover, the mesh of policies and legislation, organizational structures, and national infrastructures differed.

https://arxiv.org/abs/2312.04092

"Fair Sharing of Health Data: A Systematic Review of Applicable Solutions"

Health science researchers face additional specific challenges. Firstly, ethical and legal issues are barriers regarding the sharing of IPD. Legislation, like the General Data Protection Regulation (GDPR [16]) in Europe or the Health Insurance Portability and Accountability Act (HIPAA [17]) in the USA, prevents research data from being openly shared. IPD can only be shared publicly after the removal of all information allowing the identification of the individual participants, unless explicit consent has been obtained from the individual participants. Furthermore, the legislation has been growing stronger over the years. State laws have emerged in the USA, like the CCPA in California [18], as well as European legislation such as the Convention 108 [19] or the proposal for a reform of ePrivacy legislation [20].

Secondly, health data are diverse and heterogeneous and can be of very different types and formats, depending on the field they belong to, e.g., imaging, genomics, and mass spectrometry. Handling these data requires specific expertise and tools which can usually only be found in the specialized, dedicated communities.

The objective of this paper is to identify and evaluate technical solutions to implement systematic data sharing in an academic context, in order to help researchers making their data FAIR. We will evaluate various software programs and online platforms used in academic projects to manage and store data through a systematic literature review focusing on the implementation of the FAIR principles and the ability to support sharing of Individual Participant Data (IPD).

https://doi.org/10.1007/s12553-023-00789-5

Paywall: "Value of Open Research Data: A Systematic Evaluation Framework Based on Multi-Stakeholder Survey"

Stakeholders such as funders, data centers and data curators need specific and detailed evidence to support and justify the value of their existing or proposed open data policies and practices. A questionnaire-based evaluation framework was designed through systematic review and expert interviews, focusing on the scientific, economic, and societal values of open research data. . . . On average, participants (strongly) agreed that open research data has scientific (83.97%), economic (76.94%), and societal (86.89%) value, all 37 statements of the framework were supported and confirmed. This framework is one of the most comprehensive and systematic tools for measuring data value, which can offer support to diverse stakeholders, especially funders, data centers, and data curators in managing and promoting open data systems.

https://doi.org/10.1016/j.lisr.2023.101269

Paywall: "Data Curation Education: Cross-Disciplinary Analysis of Master’s Programs "

The main goal of this study is to analyze the course content from the syllabi of various programs to understand what is being taught in LIS schools throughout graduate-level education. Further, because the need for data curation is apparent across different disciplines, and thus not only LIS but also other disciplines have been offering data curation courses, this study also analyzed syllabi from other disciplines. . . . Our findings suggest a notable growth in LIS education in data curation since 2012, but LIS education still provides less training in technical skills. There was also a distinctive difference in educational approach to teach data curation between LIS (user- and service-oriented) and other disciplines (technical skills-focused), which brought different strengths and weaknesses in curriculum.

https://tinyurl.com/bdfjwjbh

Scholarly Communication Librarianship and Open Knowledge

Scholarly Communication Librarianship and Open Knowledge is an open textbook and practitioner’s guide that collects theory, practice, and case studies from nearly 80 experts in scholarly communication and open education. Divided into three parts:

What is Scholarly Communication?

Scholarly Communication and Open Culture

Voices from the Field: Perspectives, Intersections, and Case Studies

The book delves into the economic, social, policy, and legal aspects of scholarly communication as well as open access, open data, open education, and open science and infrastructure. Practitioners provide insight into the relationship between university presses and academic libraries, defining collection development as operational scholarly communication, and promotion and tenure and the challenge for open access.

https://bit.ly/SCLAOK

The State of Open Data 2023

Support is not making its way to those who need it

Almost three-quarters of respondents had never received support with making their data openly available.

One size does not fit all

Variations in responses from different subject expertise and geographies highlight a need for a more nuanced approach to research data management support globally.

Challenging stereotypes

Are later career academics really opposed to progress? The results of the 2023 survey indicate that career stage is not a significant factor in open data awareness or support levels.

Credit is an ongoing issue

For eight years running, our survey has revealed a recurring concern among researchers: the perception that they don’t receive sufficient recognition for openly sharing their data.

AI awareness hasn’t translated to action

For the first time, this year we asked survey respondents to indicate if they were using ChatGPT or similar AI tools for data collection, processing and metadata creation.

https://tinyurl.com/mr28u6tt

| Research Data Publication and Citation Bibliography | Research Data Sharing and Reuse Bibliography | Research Data Curation and Management Bibliography | Digital Scholarship |

Paywall: "Cutting the Gordian (Workload) Knot? Adding Data Services to Academic Library Public Services"

The library and information science literature wants two irreconcilable things out of its workload data: 1) aggregate comparable data to document and measure use of libraries and its value; and 2) accurate descriptions to document and measure the individual work done by librarians. . . . We propose here to change the question asked: how can we achieve a reasonable balance of workload within a group of librarians? . . . The goal was to answer a common and longstanding question: we are in continual process of assessing what needs to be done and how/where to shift workloads, but how do we know we’re doing it in a reasonable and fair way beyond anecdotes and intuitions? We developed a weighted measure of public services workload in order to assess and track and assign a) areas of declining workload, b) areas of increasing workload (data services), and c) a balance between library divisions contributing to public services.

https://doi.org/10.1016/j.acalib.2023.102801

| Research Data Publication and Citation Bibliography | Research Data Sharing and Reuse Bibliography | Research Data Curation and Management Bibliography | Digital Scholarship |

"Structural Elements and Spheres of Expertise: Creating a Healthy Ecosystem for Cultural Data Initiatives"

While technology affords creation of digital collections, and promises access to all, the reality is that many cultural data collections exist in a precarious ecosystem, where erratic funding, fragmented support, and disconnected expertise threaten their continued existence. As a significant branch of the broader information ecosystem, cultural data collections range in size and scope, from national institutions to bespoke local collections supported by individuals. This exploratory, qualitative study engaged cultural data experts in Australia, Canada, and the United Kingdom to map the broad cultural data ecosystem and to identify opportunities for healthier growth. The development and maintenance of cultural data collections requires integration across the spheres of expertise of creators, curators, subject matter experts, information science, and computing and technology. The foundational structural elements of the ecosystem include funding, policies, access to existing data, community context, and technological infrastructure. The key elements of a healthy data ecosystem are clarity of purpose, user-focused design, sustainability, allied coproduction, and reciprocal interconnection. A healthier cultural data ecosystem means more collections and initiatives will have positive impacts for research, knowledge, and diverse communities, contributing positively to the broader information ecosystem and to society, at large.

https://doi.org/10.1002/asi.24849

"Training to Act FAIR: A Pre-post Study on Teaching FAIR Guiding Principles to (Future) Researchers in Higher Education."

Before FAIR training, 81.1% of students suggest scientific actions not in line with the FAIR guiding principles. However, after the training, there is a 3.75-fold increase in scientific actions that adhere to these principles. Interestingly, the training does not significantly impact how students justify FAIR actions. The study observes a positive correlation between the presence of university legal frameworks on FAIR guiding principles and students’ inclination towards FAIR training. It explicates safe space, participation, motivation, usefulness, and satisfaction as the five highest-rated learning factors in FAIR training.

https://doi.org/10.21203/rs.3.rs-3409769/v1

"Dissemination Effect of Data Papers on Scientific Datasets"

This study aims to investigate the citation practices associated with data papers and to explore the role of data papers in disseminating scientific datasets. . . . The findings indicate a consistent growth in the number of biomedical data journals published in recent years, with data papers gaining attention and recognition as both publications and data sources. Although the use of data papers as citation sources for data remains relatively rare, there has been a steady increase in data paper citations for data utilization through formal data citations.

https://doi.org/10.1002/asi.24843

"Repository Staff Perspectives on the Benefits Of Trustworthy Digital Repository Certification"

This paper reports on the results from a qualitative study that asks whether and how staff members from TRAC certified repositories find value in the audit and certification process. While some interviewees found certification valuable, others argued that the costs outweighed the benefits or expressed ambivalence towards certification. Findings indicate that TRAC certification offered both internal and external benefits, such as improved documentation, accountability, transparency, communication, and standards, but there were concerns about high costs, implementation problems, and lack of objective evaluation criteria.

https://tinyurl.com/bddmuwjy

"FAIR EVA: Bringing Institutional Multidisciplinary Repositories into the FAIR Picture"

The FAIR Principles are a set of good practices to improve the reproducibility and quality of data in an Open Science context. Different sets of indicators have been proposed to evaluate the FAIRness of digital objects, including datasets that are usually stored in repositories or data portals. However, indicators like those proposed by the Research Data Alliance are provided from a high-level perspective that can be interpreted and they are not always realistic to particular environments like multidisciplinary repositories. This paper describes FAIR EVA, a new tool developed within the European Open Science Cloud context that is oriented to particular data management systems like open repositories, which can be customized to a specific case in a scalable and automatic environment. It aims to be adaptive enough to work for different environments, repository software and disciplines, taking into account the flexibility of the FAIR Principles. As an example, we present DIGITAL.CSIC repository as the first target of the tool, gathering the particular needs of a multidisciplinary institution as well as its institutional repository.

https://doi.org/10.1038/s41597-023-02652-8

"Understanding the Value of Curation: A Survey of Researcher Perspectives of Data Curation Services from Six Us Institutions"

Data curation encompasses a range of actions undertaken to ensure that research data are fit for purpose and available for discovery and reuse, and can help to improve the likelihood that data is more FAIR (Findable, Accessible, Interoperable, and Reusable). The Data Curation Network (DCN) has taken a collaborative approach to data curation, sharing curation expertise across a network of partner institutions and data repositories, and enabling those member institutions to provide expert curation for a wide variety of data types and discipline-specific datasets. This study sought to assess the satisfaction of researchers who had received data curation services, and to learn more about what curation actions were most valued by researchers. By surveying researchers who had deposited data into one of six academic generalist data repositories between 2019–2021, this study set out to collect feedback on the value of curation from the researchers themselves. A total of 568 researchers were surveyed; 42% (238) responded. Respondents were positive in their evaluation of the importance and value of curation, indicating that the participants not only value curation services, but are largely satisfied with the services provided. An overwhelming majority 97% of researchers agreed that data curation adds value to the data sharing process, 96% agreed it was worth the effort, and 90% felt more confident sharing their data due to the curation process. We share these results to provide insights into researchers’ perceptions and experience of data curation, and to contribute evidence of the positive impact of curation on repository depositors. From the perspective of researchers we surveyed, curation is worth the effort, increases their comfort with data sharing, and makes data more findable, accessible, interoperable, and reusable.

https://doi.org/10.1371/journal.pone.0293534

Digital Preservation Coalition: The Global ‘Bit List’ of Endangered Digital Species

A free-to-access and open resource for digital preservation advocacy, the DPC’s Global Bit List of Endangered Digital Species (or Bit List for short) is a community-sourced list of at-risk digital materials which is revised every two years. Entries to the list are nominated by the community, who are at the forefront of digital preservation efforts, and reviewed by international organizations which represent global expertise in the preservation of the listed digital species.

https://tinyurl.com/jevyn9mj

"The Impacts of Changes in Journal Data Policies: A Cross-disciplinary Survey"

This discipline-specific survey of journal DSP and SMP highlighted the increasing adoption rates and rankings of DSP over time. Furthermore, the findings suggest that DSP adoption may have a notable impact on the increase in JIF. The adoption of DSP by journals may be associated with the increased attention and credibility of the articles.

https://doi.org/10.1002/pra2.924

| Research Data Publication and Citation Bibliography | Research Data Sharing and Reuse Bibliography | Research Data Curation and Management Bibliography | Digital Scholarship |

"How Can Open Data Sharing Policies Be More Attentive to Qualitative Researchers?"

The expected and prescriptive ways of preparing data are a key part of the problem. These are governed largely by quantitative data management strategies. Qualitative data is the outcome of personal interactions between researchers and participants. Yet, data sharing guidance is seldom attentive to the co-constructed nature of qualitative material. "The identities of researchers and what they reflexively reveal of themselves, how they interact with participants, their techniques and approaches and the messiness of qualitative work are laid bare within the artefacts of qualitative data" (Weller 2023: 9). This can make researchers especially vulnerable to personal and professional scrutiny in a way that survey and other quantitative researchers are not.

https://tinyurl.com/2fpr82vr

Paywall: "The New Information Retrieval Problem: Data Availability"

In this paper, we discuss a method for exploring and locating datasets made available by scientists from federally funded projects in the US. The data pathways method was tested on federal awards. Here we describe the method and the results from analyzing fifty federal awards granted by the National Science Foundation to pursue data resources and their availability in publications, data repositories, or institutional repositories. The data pathways approach contributes to the development of a practical approach on availability that captures the current ways in which data are accessible from federally funded science projects –ranging from institutional repositories, journal data deposit, PI and project web pages, and science data platforms, among other found possibilities

https://doi.org/10.1002/pra2.796

Paywall: "’Garbage Bags Full of Files: Exploring Sociotechnical Perceptions of Formats within the Recovery and Reuse of Scientific Data"

This paper explores the social and technical perceptions of physical and digital formats as they relate to work in the recovery and reuse of scientific data, specifically historical, archival, and defunct data sources. . . . Based on 23 qualitative interviews with practitioners conducting data recovery and reuse, ranging from marine biologists to data librarians, we study how they understand, engage with, and utilize formats within their data curation work. . . . The paper focuses on practitioner perceptions of formats around the following themes: how practitioners’ historical relationships to certain challenging formats inform their ongoing curation practices; the importance of contexts in prioritizing or ignoring formats within scientific curation work; and how formats reveal larger sociotechnical issues.

https://doi.org/10.1002/pra2.798

"Conceptualizing Slow Curation"

The pressure to do things quickly is a constant in our professional lives as data curators. But what if we slowed down our work? Taking inspiration from the Slow Movement and its various sub-genres, we propose the idea of Slow Curation, specifically for the application of curating research data. Data curation is the process of reviewing datasets to prepare them for sharing, use, and reuse. We have identified areas where Slow can be embraced in the Data Curation Network’s CURATE(D) model. We also advocate for a few ways, outside of curation, where data curators can collaboratively advocate for Slowing down our work for the better. Join us as we practice radical self-care and advocate for our communities by embracing Slow and easing our way out of Busy culture.

https://doi.org/10.7191/jeslib.740

"Implementation of a Federated Information System by Means of Reuse of Research Data Archived in Research Data Repositories"

At universities, research data is increasingly stored in research data repositories according to a data management plan (DMP) and thus made available for further use. The challenge of reusing hundreds, thousands, or millions of data sets is to obtain an overview of the data in a short period of time and to search through all the data. The high variability of the formats used to store research data requires a new approach to data reusability that focuses on the visualisation and searchability of archived research data, which can also be combined with each other. In this article, we present a practical DMP that describes how information systems can be created on demand by reusing research data archived in research data repositories and how these systems can be merged into a federated information system. As a result, in our projects, information systems have been created in minutes or a couple of hours with few resources. The initial effort to create a federated system remains; however, this allows federated searches to be performed. Extending a federated system to include other information systems can then be accomplished by making a few configurations and manageable adjustments to the source code.

https://doi.org/10.5334/dsj-2023-039

"Connecting Fragmented Support on Campus: Growing Research Data Services Programs Through Collaboration"

Research data services are provided by multiple units across and beyond the library, which is why communication and collaboration are paramount to building support for researchers. By exploring how Research Data Services (RDS) programs can function in the fragmented landscape of research support on campuses, we outline the role of collaboration in building programs. In this paper, we discuss building an RDS program by emphasizing three strategies for collaboration: collaborating within the library, collaborating across campus, and collaborating externally with those without direct ties to your organization. The aim of this paper is to offer attainable examples and strategies for building collaborations across campuses for libraries that have small or nascent RDS programs—how to approach and cultivate partnerships, how to set realistic goals, and how to work holistically within the fragmented academy.

https://tinyurl.com/9hbz49df

Paywall: "DMPFrame: A Conceptual Metadata Framework for Data Management Plans"

We have examined 12 open-source DMP tools, in particular, to evaluate the metadata adopted by these tools. The current study spots and highlights the gaps in the DMP metadata management in DMP tools and suggests DMPFrame as a conceptual framework addressing such gaps to improve the existing tools’ DMP metadata management practices. Based on the examined DMP tool’s metadata elements analysis and mapping, DMPFrame manages DMP metadata under 6 categories, namely, contributors, project, funding, organization, DMP, and output. The current study also suggests a systematic workflow that DMP tools could incorporate for metadata creation for DMPs.

https://doi.org/10.1080/19386389.2023.2268474

"Disappearing Repositories — Taking an Infrastructure Perspective on the Long-Term Availability of Research Data"

Currently, there is limited research investigating the phenomenon of research data repositories being shut down, and the impact this has on the long-term availability of data. This paper takes an infrastructure perspective on the preservation of research data by using a registry to identify 191 research data repositories that have been closed and presenting information on the shutdown process. The results show that 6.2 % of research data repositories indexed in the registry were shut down. The risks resulting in repository shutdown are varied. The median age of a repository when shutting down is 12 years. Strategies to prevent data loss at the infrastructure level are pursued to varying extent. 44 % of the repositories in the sample migrated data to another repository, and 12 % maintain limited access to their data collection. However, both strategies are not permanent solutions. Finally, the general lack of information on repository shutdown events as well as the effect on the findability of data and the permanence of the scholarly record are discussed.

https://arxiv.org/abs/2310.06712

"IFLA ARL Section’s ‘Inclusiveness through Openness’ Conference Proceedings Now Available!"

All videos and slides from this August IFLA Academic & Research Libraries Section (ARL) Satellite conference to the 2023 WLIC in Rotterdam IFLA conference are now available:

https://tinyurl.com/4cywvp9h