International Journal of Digital Curation
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Application and Evaluation of the Hoffman et al. (2020) Data Rescue Framework using an historic Scottish Cloud and Rain Chemistry Dataset exemplar
No full textEnvironmental data are vitally important and valuable research outputs, and there are vast quantities in laboratory storage and on servers where they are not easily or openly accessible. It is imperative for preservation and for potential reuse purposes that historical data of long-term value are efficiently curated and made publicly available. We evaluated the Hoffman et al. (2020) data rescue framework (DRF) for the initial assessment stage of a data rescue by applying it to an historic Scottish cloud and rain chemistry dataset. The DRF facilitated workload prioritisation, anticipating potential obstacles, and approximating resources required. We used a novel points-based adaptation of the DRF to identify suitability of datasets for rescue and compare the dataset status before and after rescue, particularly taking FAIR principles into account. The reusability of the dataset was greatly improved by the Hoffman et al. (2020) framework, and it is now published in an appropriate open access data centre with detailed metadata. It is recommended that the traceable DRF and scoring system be adopted in future to begin moving twentieth and early twenty-first century environmental data into the public domain
The Copyrights Chain in the Digital Curation Process: “Which Copyright” Project at the Nazarian Library, University of Haifa
No full textThe internet era, open access movement, image sharing platforms, and mainly the rise of artificial intelligence (AI) emphasise the importance of providing moderated access and licences for the reuse of collections by memory institutes as a key step in the digital curation process.
Trusting individuals to control their data and its (re)use was an important concern since the early establishment of the digital collections in 1998 at the University of Haifa Library. However, there were no specialised tools for keeping the owner’s copy of rights, which led to the use of the note field in the metadata record.
This brief report will describe the experiences in a recent ongoing project to enrich the University of Haifa’s digital collections with clear copyright status, with preference to open Creative Commons licences to benefit the user and the owner’s experiences.
The steps performed will be explored as part of the workflow designed for the ‘Which Copyrights’ project 2024–2025. The scope of the project includes approximately 80,000 bibliographic records and more than 200,000 digital representations, covering local cultural heritage data. Within 7 months, over 52,000 records containing approximately 100,000 digital objects have been processed and are available with the copyright’s representation notice online. In total, 25% of those records have been updated with CC BY 4.0. The success encouraged the design of the next step, to use a public platform to make the dataset available for the public. The Digital collection of the Younes & Soraya Nazarian Library, University of Haifa offers an open access portal, primarily used by the academic community. Therefore, visibility and usage will be expanded to a broader public, including via non-academic platforms, such as Wikipedia or Wikimedia. By sharing these plans, ideas, and ongoing actions, the library experience could be useful to other institutions that work with digital heritage collections, for the benefit of researchers and the broader public
Improving the Transparency of Data Access Conditions in the SSH Domain: Recommendations based on a small-scale analysis of the conditions applied to restricted access datasets
No full textThe benefits of making data available for reuse are recognised by many. While some datasets can be openly available, others contain sensitive or personal data that needs to be protected. To allow the sharing of the latter datasets, many trustworthy digital repositories provide options to publish data restricted access. However, detailed standardised information about the access conditions for these restricted access datasets is often lacking from the metadata. Researchers interested in reusing these datasets can thus not judge whether they are eligible to reuse data and under what conditions.
To get a better understanding of how we can increase the transparency of access conditions, this paper aimed to investigate the access conditions and procedures that are commonly applied by depositors within the (Dutch) Social Sciences and Humanities (SSH) research community. The results of a survey that was conducted (n=45) indicated that various conditions are applied, and while some datasets can have few restrictions, for others reuse is highly restricted. Most respondents limit reuse to research purposes and prohibit commercial use. Some datasets are available for students or teaching, but often with additional requirements. A large majority of respondents required a motivation letter to evaluate before allowing reuse. Notably, respondents often chose ‘It depends’ when asked whether a specific condition was applied, showing a lot of nuances in the conditions and the evaluation of access requests. An important result from our survey was that clear procedures and decision-making guidelines seem to be lacking for many respondents. Requests are often evaluated ad-hoc and through email. Decisions are said to require an evaluation of the quality of the application, yet the evaluation criteria seem to be rarely specified and explicitly communicated at the time of data deposit.
Based on the results of the small-scale survey, we conclude with a set of six recommendations directed at data owners and repositories outlining how information about access conditions and procedures can be made more transparent in the future. This work should be seen as a starting point to improve the accessibility and reusability of restricted access datasets in the SSH domain
Mad with the Writing: 100 Years of Collecting, 20 years of Digitising, 3% Completed
No full textThis is a story about the Australian War Memorial’s historically significant, preeminent archive, which represents 100 years of collecting, 20 years of digitising and to date is three per cent digitised! Whether the format of the original record is created in paper or digital, we are all still “mad for the writing”, and there is only one thing for certain: that for the next 20 years, we will still be digitising! We all want to read and access collections online. It is hoped that developments in technology will continue to make that desired access faster, easier, safer and more efficient. Artificial Intelligence will most certainly play a role in ensuring that we will not be trying to “drink from the fire hose” when accessing digital collections into the future. Transcription technologies will continue to deliver research data that is relevant today in a variety of contexts
Development of an Integrated Lifecycle of RDM Tools: Looking Back and Forward at KU Leuven
No full textAfter the creation of an institutional research data management (RDM) policy some years ago, KU Leuven decided it was crucial to create an ecosystem of RDM tools for the entire RDM life cycle to enable KU Leuven researchers to manage their data well and in a FAIR way. In 2018, KU Leuven started on the road to an institutional data repository, which resulted in the launch of the Dataverse-based Research Data Repository (RDR) in January 2022. In line with this, there was a strong focus on tools to manage data in a structured and metadata-rich way during the research project, when data was still being worked on. Based on this, an Integrated Rule-Oriented Data System (iRODS) instance that would enable easy and integrated metadata management from the start of a research project via a self-developed portal was launched in March 2023 under the name “ManGO,” which is a shortened version of MANagement van Gegevens voor Onderzoek. Because one of the four FAIR principles is interoperability, and to fully enable FAIR data management, it was important to facilitate this interoperability of data by ensuring that KU Leuven RDM tools are interoperable, with a first focus being the connection between ManGO and RDR to select and copy data ready for publication. As with ManGO, RDR, the integration work, and other RDM developments made or adapted at KU Leuven, all relevant work will continue to be shared in open source where possible to ensure that investments that the university makes in RDM tool development can be used by and are accessible to other institutions
The Standardized Data Management Plan for Educational Research: an Approach to Foster Tailored Data Management
No full textAlthough there is an increasing number of tools and support opportunities, research data management is still challenging. Conventional templates of data management plans (DMP) guide users, but hardly support them in implementing and realizing data management. Instead, users of conventional templates require more tailored guidance to better understand how to manage their data according to the needs of their research discipline, and its methods and practises, e.g., regarding data sharing. To provide more tailored, discipline-specific guidance, Science Europe (2018) suggests developing and using so-called Domain Data Protocols, i.e., a model DMP for a given discipline or community. The project Domain Data Protocols for Empirical Educational Research was one of the first to turn this concept into a practically useable DMP template tailored to educational research by developing the Standardised Data Management Plan for Educational Research (Stamp). The Stamp is designed to assist researchers in managing their data, appropriately, and to ensure shareable data according to the FAIR Data Principles. Due to its flexible structure, its checklist and auxiliary materials, the Stamp tackles most of the challenges of conventional DMP templates. Providing tailored, discipline-specific guidance and enabling to manage various types of data, the Stamp is an innovative approach to further professionalize data management
Reproducible preservation of databases through executable specifications
No full textWe propose a new preservation method for relational data and a corresponding tool. The method involves writing a specification that can later be executed by the tool without user interaction, transforming the input files and databases into an encapsulated package suitable for archiving. Thus, the transformation steps become reproducible, which facilitates automation by reusing the specifications and allows for an iterative process, where for each iteration the specification is extended or adjusted and then executed to check that the result is closer to fulfilling future access requirements
Realising Open Data Principles In UK Research Institutions: Key insights from the STAR (Sustainable & TrAnsparent Research data) project, led by the UK Reproducibility Network (UKRN)
No full textWe report on the state of open research data (ORD) policy and practice across UK research institutions through the STAR (Sustainable & TrAnsparent Research data) project. Through qualitative interviews, focus groups, and workshops involving 52 university staff across 21 UK institutions, we investigated the progress and challenges in ORD practices since 2016 publication of the Concordat on Open Research Data.
We observed that while institutions have made progress establishing ORD specialist roles, developing policies, and creating repository infrastructures, systematic monitoring processes and widespread adoption remain stalled. Key challenges include capacity constraints in institutional repositories, limited workload recognition, insufficient funding for long-term archiving, and varying disciplinary interpretations of ORD relevance.
Based on workshops with participants, we recommend recognition of ORD in academic career frameworks, development of disciplinary-relevant data sharing practices, improved infrastructure for monitoring ORD practices, and enhanced support for external disciplinary repositories. The study emphasizes the need for a values-driven rather than compliance-driven approach to ORD implementation, calling for deeper engagement with diverse academic communities to ensure ORD requirements remain meaningful and relevant across disciplines. These findings provide insights for research institutions and funding bodies in developing more effective and inclusive ORD policies
Professionalising Social Science Research Data Management with RDM Compas
No full textIt is not only since the publication of the FAIR principles, requiring the Findable, Accessible, Interoperable, and Reusable organisation of research outputs, that the demands placed on researchers when conducting good scientific practices have increased. Universities and other research institutions have responded to this and offer increasing support, especially regarding research data management (RDM). This is to support their researchers in the FAIR organisation and thus transparent sharing of all their research outputs. However, digital curation and RDM are complex and demand an interplay of various skills and knowledge. So far, there are no established training programmes. Therefore, projects aiming to support researchers in RDM often face one major challenge: Recruiting staff well trained in RDM.
In our project, we examined data curation skill needs and various approaches to define these needs. Paired with the DCC Curation Lifecycle Model and survey results from Social Science Research Data Centres in Germany, we defined curation skill needs and learning trajectories and implemented these in an information and training platform for data curation in the social sciences, RDM Compas, with its content organized along the DCC Curation Lifecycle Model. A newly developed data curation module in a nationwide RDM certification course compliments the training path toward professional RDM
Good Support Helps To Avoid Data Horror. Experiences With Organising Research Data Management Support
No full textThe complexity around data management decisions is a tangible burden to researchers and can be a significant barrier to engaging with Open Science principles. Researchers often face a multitude of choices regarding storage solutions, sharing technologies, security, and legal and ethical concerns, each with its own set of implications for their work. Simplifying these processes through the development of intuitive tools, clear guidelines, and nearby support is crucial for demystifying the preservation of research data and making it more approachable.
Since 2018, Vrije Universiteit (VU) Amsterdam has been steadily developing a data management ecosystem consisting of professional support services, an adequate technical infrastructure, and an awareness-raising and training programme to increase the skillset of researchers on data and software management. This ecosystem is organised as a collaborative effort in which faculty and central services are strongly involved in a network organisation, the Network for Research Data Support (NeRDS). Operational since April 2021, NeRDS focuses on professionalising Research Data Management (RDM) and services through four main tasks: (1) providing user support on tooling and sustainable data and software management services; (2) maintaining the technical solutions on data and software management; (3) innovating and developing new services based on researcher demand; and (4) offering data and software management information and training within a community