Data Curation, Open Data, and Research Data Management

"Data Services at the Academic Library: A Natural History of Horses and Unicorns"

Methods: We used a web-based inventory of 25 academic libraries at U.S. Research 1 (R1) Carnegie institutions to assess the state of data services at university libraries. We categorized and quantified services, and tested for an effect of library resourcing on the size of library data service portfolios.

Results: Support for data management and geospatial services was relatively widespread, with increasing support in areas of data analyses and data visualization. There was significant variation among services in the modality in which they were offered (web, consult, instruction) and library resourcing had a significant effect on the number of data services a library offered.

https://doi.org/10.7191/jeslib.780

Research Data Management for Arts and Humanities: Intergrating Voices of the Community

Chapter one gives an overview of the European and national policy environment which has given rise to research data management and sharing mandates, as well as the institutional support structures around them. In chapter two, which is dedicated to implementation and everyday practice, the authors of this publication share how their institutions have developed capacities to accommodate data support professions, and also share their own career paths leading to such roles. After the first two chapters have set the stage and recounted the authors’ reflections on these new roles, the rest of the publication highlights and discusses some of the key domain-specificities of research data management in the Arts and Humanities. Chapter 3.1 reflects on the implications of the lack of consensus around the notion of data within the Arts and Humanities domain through a case study of digital critical editions. Chapter 3.2 addresses the challenges around the, essentially, multilingual character of arts and humanities data, with special focus on multilingual vocabularies and thesauri. Chapter 3.3 provides support for research scenarios where open data sharing is either impossible or is difficult due to legal and ethical limitations, and navigates the complexities of intellectual property and the application of regulatory frameworks, including restrictions on text and data mining, and authentication and authorisation in an open world. Clearly, the discourse on data sharing cannot be complete without discussing the current limitations within research assessment and rewards criteria, nor highlighting initiatives which aim to incentivise and reward data sharing in the working/professional contexts of the Working Group’s members. A discussion on rewards can be found in Chapter 3.4. Chapter 3.5 addresses one of the most widely shared data management challenges within the domain and brings together use cases concerning successful collaborations between cultural heritage institutions and arts and humanities research teams. Finally, Chapter 3.6 showcases good practices in long-term archiving

https://tinyurl.com/ycxbrh33

"Assessing Quality Variations in Early Career Researchers’ Data Management Plans"

This paper aims to better understand early career researchers’ (ECRs’) research data management (RDM) competencies by assessing the contents and quality of data management plans (DMPs) developed during a multi-stakeholder RDM course. We also aim to identify differences between DMPs in relation to several background variables (e.g., discipline, course track). The Basics of Research Data Management (BRDM) course has been held in two multi-faculty, research-intensive universities in Finland since 2020. In this study, 223 ECRs’ DMPs created in the BRDM of 2020 – 2022 were assessed, using the recommendations and criteria of the Finnish DMP Evaluation Guide + General Finnish DMP Guidance (FDEG). The median quality of DMPs appeared to be satisfactory. The differences in rating according to FDEG’s three-point performance criteria were statistically insignificant between DMPs developed in separate years, course tracks or disciplines. However, using content analysis, differences were found between disciplines or course tracks regarding DMP’s key characteristics such as sharing, storing, and preserving data. DMPs that contained a data table (DtDMPs) also differed highly significantly from prose DMPs. DtDMPs better acknowledged the data handling needs of different data types and improved the overall quality of a DMP. The results illustrated that the ECRs had learned the basic RDM competencies and grasped their significance to the integrity, reliability, and reusability of data. However, more focused, further training to reach the advanced competency is needed, especially in areas of handling and sharing personal data, legal issues, long-term preserving, and funders’ data policies. Equally important to the cultural change when RDM is an organic part of the research practices is to merge research support services, processes, and infrastructure into the research projects’ processes. Additionally, incentives are needed for sharing and reusing data.

https://doi.org/10.2218/ijdc.v18i1.873

"More CNI Spring 24′ Meeting Videos Live"

CNI has released eight new videos from its Spring 2024 meeting.

Here are three examples:

The Open Access Tracking Project Is Now 15 Years Old

Peter Suber has announced that the Open Access Tracking Project is now 15 years old. This project has made an invaluable contribution to the Open Access and Open Science movements. Readers are encouraged to considering joining it and posting new works of interest to it. Even occasional contributions are meaningful.

Here is a description of the project from its home page:

OATP is a crowd-sourced social-tagging project running on free software to capture news and comment on open access to research.

Its mission is (1) to create real-time alerts for OA-related news and comment, and (2) to organize knowledge of the field, by tag or subtopic, for easy searching and sharing.

OATP publishes a comprehensive primary feed of new OA developments, and hundreds of smaller secondary feeds on subtopics or subsets, for example, one feed for each project tag, one for each search, and one for each user-created boolean combination of its other feeds.

OATP runs on TagTeam, open-source software developed specifically for OATP and now available for open, tag-based research projects on any topic. See the OATP hub within TagTeam. TagTeam stores all OATP tag records for deduping, export, preservation, modification, and search. OATP started on Connotea and moved to TagTeam in September 2012.

Peter Suber launched OATP in April 2009, and wrote a full-length description of it in the SPARC Open Access Newsletter for May 2009. In mid-2011 OATP became part of the Harvard Open Access Project (HOAP).

https://tinyurl.com/m5ku5mxh

Digital Scholarship and DigitalKoans Are Now 19 Years Old

Digital Scholarship and DigitalKoans were established on 4/20/2005. Digital Scholarship provides information and commentary about artificial intelligence, digital copyright, digital curation, open access, research data management, scholarly communication, and other digital information issues. Digital Scholarship is an open access noncommercial publisher. All of its publications are currently under a Creative Commons Attribution License.

DigitalKoans has published over 16,200 posts. Since 2008, over 5,600 job ads have been posted, with slightly over 4,000 of them for digital library jobs.

Digital Scholarship has published the following books and book supplements: the Open Access Bibliography: Liberating Scholarly Literature with E-Prints and Open Access Journals (2005; published with the Association of Research Libraries), the Scholarly Electronic Publishing Bibliography: 2008 Annual Edition (2009), Digital Scholarship 2009 (2010), Transforming Scholarly Publishing through Open Access: A Bibliography (2010), the Scholarly Electronic Publishing Bibliography 2010 (2011), the Digital Curation and Preservation Bibliography 2010 (2011), the Institutional Repository and ETD Bibliography 2011 (2011), the Digital Curation Bibliography: Preservation and Stewardship of Scholarly Works (2012), the Digital Curation Bibliography: Preservation and Stewardship of Scholarly Works, 2012 Supplement (2013), and the Research Data Curation and Management Bibliography (2021).

It has also published and updated the following bibliographies, webliographies, and weblogs: the Scholarly Electronic Publishing Bibliography (1996-2011), the Scholarly Electronic Publishing Weblog (2001-2013), the Electronic Theses and Dissertations Bibliography (2005-2021), the Google Books Bibliography (2005-2011), the Institutional Repository Bibliography (2009-2011), the Open Access Journals Bibliography (2010), the Digital Curation and Preservation Bibliography (2010-2011), the E-science and Academic Libraries Bibliography (2011), the Digital Curation Resource Guide (2012), the Research Data Curation Bibliography (2012-2019), the Altmetrics Bibliography (2013), the Transforming Peer Review Bibliography (2014), the Academic Library as Scholarly Publisher Bibliography (2018-2023), the Research Data Sharing and Reuse Bibliography (2021), the Research Data Publication and Citation Bibliography (2022), Digital Curation Certificate and Master’s Degree Programs (2023), the Academic Libraries and Research Data Management Bibliography (2023), and the Artificial Intelligence and Libraries Bibliography (2023).

"CHORUS Forum: 12 Best Practices for Research Data Sharing — Summary And Comments"

At last month’s CHORUS Forum: 12 Best Practices for Research Data Sharing speakers addressed the Joint Statement on Research Data Sharing by STM, DataCite and Crossref. The forum was moderated by Howard Ratner, Executive Director, CHORUS and sponsored by AIP Publishing, Association of American Publishers, Crossref, GeoScienceWorld, and STM.

https://tinyurl.com/3ubnw4db

"Open Data Ownership and Sharing: Challenges and Opportunities for Application of Fair Principles and a Checklist for Data Managers"

The amount of data generated across various disciplines has been steadily increasing and is projected to experience exponential growth in the foreseeable future. This underscores the pressing need for proficient and streamlined data management. Data has proven to be a crucial tool in addressing complex societal challenges on a global scale. However, the challenge of producing and openly disseminating data that are easily discoverable, accessible, interoperable, and reusable (FAIR) has emerged as a significant concern for policymakers. The potential for data to be repurposed for advancing scientific research and innovation across different disciplines is contingent on its willingness to be shared. This paper employs a systematic literature review to investigate the motivating factors, advantages, and obstacles associated with open data sharing. Additionally, it explores governance frameworks that can create unique opportunities for implementing FAIR principles in real-time scientific research.

https://doi.org/10.1016/j.jafr.2024.101157

Paywall: "Global Status of Dataset Repositories at a Glance: Study Based on OpenDOAR"

Developed countries like the United Kingdom and the USA are primarily involved in the development of institutional open-access repositories comprising significant components of OpenDOAR. The most extensively used software is DSpace. Most data set archives are OAI-PMH compliant but do not follow open-access rules. . . . Furthermore, the study concludes that the number of data sets kept in repositories is insufficient, although the expansion of such repositories has been consistent over the years.

https://doi.org/10.1108/DLP-11-2023-0094

"The Future of Data in Research Publishing: From Nice to Have to Need to Have?"

Science policy promotes open access to research data for purposes of transparency and reuse of data in the public interest. We expect demands for open data in scholarly publishing to accelerate, at least partly in response to the opacity of artificial intelligence (AI) algorithms. Open data should be findable, accessible, interoperable, and reusable (FAIR), and also trustworthy and verifiable. The current state of open data in scholarly publishing is in transition from ‘nice to have’ to ‘need to have.’ Research data are valuable, interpretable, and verifiable only in context of their origin, and with sufficient infrastructure to facilitate reuse. Making research data useful is expensive; benefits and costs are distributed unevenly. Open data also poses risks for provenance, intellectual property, misuse, and misappropriation in an era of trolls and hallucinating AI algorithms. Scholars and scholarly publishers must make evidentiary data more widely available to promote public trust in research. To make research processes more trustworthy, transparent, and verifiable, stakeholders need to make greater investments in data stewardship and knowledge infrastructures.

https://doi.org/10.1162/99608f92.b73aae77

"Common Metadata Framework for Research Data Repository: Necessity to Support Open Science"

The present study describes the features of a select number of RDRs and analyzes their metadata practices: Harvard Dataverse, Dryad, Figshare, Zenodo, and the Open Science Framework (OSF). It further examines the total number of metadata elements, common metadata elements, required metadata elements, and item-level metadata. Results indicate that even though Harvard Dataverse has the most metadata elements, Dryad provides rich metadata concerning item level. This study suggests a common metadata framework, richer metadata elements, and more features to make the research data’s interoperability possible from one RDR to another.

https://doi.org/10.1080/19386389.2024.2329370

"The Fair for Research Software Principles after Two Years: An Adoption Update"

It should be noted that while the many activities listed here support increasing FAIRness of research software, most of them do not address aspects of all four of the FAIRness of research software foundational principles. . . . This reflects that the FAIR4RS Principles are aspirational and high-level, and do not contain detailed guidance on how to achieve them. This is because specific technologies and tools are always changing, while the principles are intended to be long-lasting. Consequently, additional work is needed to make it simpler for people wanting to follow the FAIR4RS Principles to know how to practically do so. The following initiatives are assisting in achieving this, with some of these initiatives specifically addressing the range of opportunities for future work identified in 2022 by the FAIR4RS Working Group, which developed the FAIR4RS Principles.

https://www.researchsoft.org/blog/2024-03/

"Publicly Shared Data: A Gap Analysis of Researcher Actions and Institutional Support throughout the Data Life Cycle"

[This report] examines research data management and sharing practices at six research-intensive academic institutions: Cornell University, Duke University, University of Michigan, University of Minnesota, Virginia Tech, and Washington University in St. Louis. Sponsored by the US National Science Foundation (grant #2135874) and part of ARL’s Realities of Academic Data Sharing (RADS) Initiative, this report highlights where service gaps may exist between researchers’ needs and the services and support provided by institutions.

https://tinyurl.com/mtdjvecu

"Research Data Management Sustainability: Services, Infrastructure, Accountability, and Planning"

This study aims to update on the status of RDMS service offerings, staffing and funding, and presents them according to the number of years a library has offered the service. This work also investigates RDMS service fulfillment, accountability in providing support, and planning strategies within the same institution sample. Updating the RDMS status, broadening the facets addressed, and presenting the data by cohort provides detail into how services have been maintained or developed so that institutions at a similar stage can make clearer decisions about how to keep RDMS sustainable.

https://tinyurl.com/22cexhrt

"Developing Text and Data Mining (TDM) Support within a University Research Library"

The introduction of the text and data mining (TDM) exception in 2014 led to researchers asking for support from staff within Library Services at the University of Birmingham. An initial involvement with a funded corpus linguistics project fostered an effective partnership between the Copyright and Licensing Team and the University’s Research Infrastructure Team. This case study traces the TDM journey that Library Services has subsequently undertaken. The article will look at how staff in Copyright and Licensing and the Research Skills Team identified the original service gap. It will also look at issues impacting on supporting TDM and the results of a TDM survey that was sent to researchers. It concludes with a reflection on how the service might evolve in the future — from the creation and availability of TDM datasets, to the skills development of both librarians and the university communities they support, and the impact artificial intelligence (AI) developments might have on TDM practices.

https://doi.org/10.1629/uksg.646

"The Challenges of Open Data Sharing for Qualitative Researchers"

"Open Science" advocates for open access to scientific research, as well as sharing data, analysis plans and code in order to enable replication of results. However, these requirements typically fail to account for methodological differences between quantitative and qualitative research, and serious ethical problems are raised by the suggestion that full qualitative datasets can or should be published alongside qualitative research papers. Aside from important ethical concerns, the idea of sharing qualitative data in order to enable replication is conceptually at odds with the underpinnings on most qualitative methodologies, which highlight the importance of the unique interpretative function of the researcher. The question of whether secondary analysis of qualitative data is acceptable is key, and in this commentary we argue that there are good conceptual, ethical and economic reasons to consider how funders, researchers and publishers can make better use of existing data.

https://doi.org/10.1177/13591053241237620

Open Data: From Theory to Practice: Case Studies and Commentary from Libraries, Publishers, Funders and Industry

From theory to practice is the first time in the nine-year history of The State of Open Data that a supplementary publication has expanded upon the main report’s years of survey results about open data, involving tens of thousands of researchers globally.

Each case study and commentary is told from the perspective of a research stakeholder group:

Funding bodies: The NIH Generalist Repository Ecosystem Initiative: meeting community needs for FAIR data sharing and discovery

Scholarly Publishers: Operationalize data policies through collaborative approaches – the momentum is now

University Libraries: One size does not fit all: an investigation into how institutional libraries are tailoring support to their researchers’ needs

Industry: How Open Pharma supports responsible data sharing for pharma research publications.

https://tinyurl.com/ytcxprn7

"Evaluating an Instructional Intervention for Research Data Management Training "

At a large research university in Canada, a research data management (RDM) specialist and two liaison librarians partnered to evaluate the effectiveness of an active learning component of their newly developed RDM training program. . . . This study relies on a pre- and post-test quasi-experimental intervention during introductory RDM workshops offered 12 times between February 2022 and January 2023. . . . Comparing the overall average scores for each participant pre- and post-instruction intervention, we find that workshop participants, in general, improved in proficiency. The results of a Wilcoxon signed-rank test demonstrate that the difference between the pre- and post-test observations is statistically significant with a high effect size.

https://tinyurl.com/2wvt5bhj

The Research Data Services Landscape at US and Canadian Higher Education Institutions

The following are our high-level findings:

While there are wide divergences in the number and variety of services offered both within and across Carnegie Classifications, R1 institutions offer approximately three times the number of services offered by R2s, and more than nine times the number offered by liberal arts colleges.

General research data services are the most common type offered regardless of institution type. Statistical services, geospatial services, and visualization services are also common at research universities, which typically offer a much wider range of specialized services than liberal arts colleges.

Libraries remain the largest provider of research data services at US and Canadian research universities, but IT and units associated with the research office play important collaborative roles, especially with specialized services.

Bioinformatics services are offered almost exclusively through the interdisciplinary units associated with the research office or core facilities associated with medical schools.

Consulting services are the most common mode of service provision, comprising almost three quarters of all data services.

https://doi.org/10.18665/sr.320420

"FAIRness of Research Data in the European Humanities Landscape "

This paper explores the landscape of research data in the humanities in the European context, delving into their diversity and the challenges of defining and sharing them. It investigates three aspects: the types of data in the humanities, their representation in repositories, and their alignment with the FAIR principles (Findable, Accessible, Interoperable, Reusable). By reviewing datasets in repositories, this research determines the dominant data types, their openness, licensing, and compliance with the FAIR principles. This research provides important insight into the heterogeneous nature of humanities data, their representation in the repository, and their alignment with FAIR principles, highlighting the need for improved accessibility and reusability to improve the overall quality and utility of humanities research data.

https://doi.org/10.3390/publications12010006

"A Decade of Progress: Insights of Open Data Practices in Biosciences at the University of Edinburgh"

Our analysis of research data sharing from 2014 to 2022 manually reviewed 193 journal articles against criteria for Openness and FAIRness, including the Completeness of data shared relative to data generated. The findings reveal an uptick in data completeness and reusability, with a clear influence of data type, and genomic data being shared more frequently than image data. Data availability statements (DAS) and preprint sharing show a strong correlation with higher Openness and FAIRness scores. Since 2016, when the FAIR guidelines were published, data Reusability increased along with the inclusion of Data Availability Statements. On the other hand, since the COVID-19 pandemic, we have found a substantial increase in preprint sharing and significant improvements in Completeness, Reusability, and Accessibility scores. This paper documents a local research institute’s journey towards Open Data, addressing the changes and advocating for best practices to nurture this progression.

https://doi.org/10.1101/2024.02.18.580901

"The Cost and Price of Public Access to Research Data: A Synthesis"

Beginning on or before 31 December 2025, all recipients of United States federal research funding will be required to make their federally funded scholarly outputs, including scientific data, freely available via public access venues with no delays or embargos. This paper focuses on research data as one of the key scholarly output types impacted by the requirements outlined in the Memorandum on Ensuring Free, Immediate and Equitable Access to Federally Funded Research issued by the US Office of Science and Technology Policy ?OSTP?, commonly called the "Nelson memo."

This paper sets out working definitions of four key terms: cost, price, reasonable, and allowable. Using these terms, we describe some of the pathways research data take to final publication, and summarize some of the extensive body of research on the costs of research data curation and sharing. We conclude that, for repositories leveraging sources of revenue other than deposit fees or other revenue streams that do not immediately scale up with increased deposits, sustainability is an important concern.

In the process, we look at cost modelling experimentation in the fields of research data management and digital preservation to consider what might be relevant from their approaches. Labour is the most significant cost for repositories and data curation, particularly in support of ingest and access, although the actual cost of data curation in repositories varies by discipline, characteristics of data, and level of curatorial services provided. If "reasonable” cost is not readily generalizable, greater clarity regarding allowable activities and more transparency in repositories" costs would aid researchers and funders in evaluating whether any deposit, membership, or other form of fees that are charged are appropriate for the services rendered. Where some or all of the effort associated with meeting public access requirements is performed by members of the research team, costs could be properly allocated to research and to publication components of grant budgets.

https://doi.org/10.5281/zenodo.10729575

"Stamp—Standardized Data Management Plan for Educational Research: A Blueprint to Improve Data Management across Disciplines"

To provide more tailored, discipline-specific guidance on data management, Science Europe suggested the concept of domain data protocols. Based on this concept, the project Domain Data Protocols for Educational Research developed a first domain data protocol for educational research, titled Standardized Data Management Plan for Educational Research (Stamp). Its multi-level approach includes minimal conditions on managing data according to the FAIR Data Principles and checklists with concrete activities to reach each minimal condition; also included are auxiliary materials to support researchers in educational research in planning, implementing, and realizing different data management activities. Although we developed the Stamp for educational research, its design and flexible structure enables transferring it to other (research) domains and communities. To investigate this flexibility, we organized two workshops, discussing to what extent the Stamp can be used beyond educational research, with representatives from other social science domains as well as from research domains beyond the social sciences. In sum, there was consensus among participants of both workshops on the usability of the Stamp outside educational research, at least if the same types of data are processed and analyzed with similar methods. For other types of data, the Stamp serves as a blueprint to develop further domain data protocols, in terms of standardized data management plans, according to the specific needs of the respective domain.

https://doi.org/10.5334/dsj-2024-007

"Thinking Outside the Black Box: Insights from a Digital Exhibition in the Humanities"

One of the main goals of Open Science is to make research more reproducible. There is no consensus, however, on what exactly "reproducibility" is, as opposed for example to "replicability", and how it applies to different research fields. After a short review of the literature on reproducibility/replicability with a focus on the humanities, we describe how the creation of the digital twin of the temporary exhibition "The Other Renaissance" has been documented throughout, with different methods, but with constant attention to research transparency, openness and accountability. A careful documentation of the study design, data collection and analysis techniques helps reflect and make all possible influencing factors explicit, and is a fundamental tool for reliability and rigour and for opening the "black box" of research.

https://arxiv.org/abs/2402.12000

"Identifying the Most Important Facilitators of Open Research Data Sharing and Reuse in Epidemiology: A Mixed-Methods Study"

To understand how open research data sharing and reuse can be further improved in the field of Epidemiology, this study explores the facilitating role that infrastructural and institutional arrangements play in this research discipline. It addresses two research questions: 1) What influence do infrastructural and institutional arrangements have on open research data sharing and reuse practices in the field of Epidemiology? And 2) how could infrastructural and institutional instruments used in Epidemiology potentially be useful to other research disciplines? First, based on a systematic literature review, a conceptual framework of infrastructural and institutional instruments for open research data facilitation is developed. Second, the conceptual framework is applied in interviews with Epidemiology researchers. The interviews show that two infrastructural and institutional instruments have a very high influence on open research data sharing and reuse practices in the field of Epidemiology, namely (a) access to a powerful search engine that meets open data search needs and (b) support by data stewards and data managers. Third, infrastructural and institutional instruments with a medium, high, or very high influence were discussed in a research workshop involving data stewards and research data officers from different research fields. This workshop suggests that none of the influential instruments identified in the interviews are specific to Epidemiology. Some of our findings thus seem to apply to multiple other disciplines. This study contributes to Science by identifying field-specific facilitators and challenges for open research data in Epidemiology, while at the same time revealing that none of the identified influential infrastructural and institutional instruments were specific to this field. Practically, this implies that open data infrastructure developers, policymakers, and research funding organizations may apply certain infrastructural and institutional arrangements to multiple research disciplines to facilitate and enhance open research data sharing and reuse.

https://doi.org/10.1371/journal.pone.0297969