International Journal of Digital Curation
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Disciplinary Data Publication Guides
Get PDFMany academic disciplines have very comprehensive standard for data publication and clear guidance from funding bodies and academic publishers. In other cases, whilst much good-quality general guidance exists, there is a lack of information available to researchers to help them decide which specific data elements should be shared. This is a particular issue for disciplines with very varied data types, such as engineering, and presents an unnecessary barrier to researchers wishing to meet funder expectations on data sharing. This article outlines a project to provide simple, visual, discipline-specific guidance on data publication, undertaken at the University of Bristol at the request of the Faculty of Engineering
Data Mining Research with In-copyright and Use-limited Text Datasets: Preliminary Findings from a Systematic Literature Review and Stakeholder Interviews
Get PDFText data mining and analysis has emerged as a viable research method for scholars, following the growth of mass digitization, digital publishing, and scholarly interest in data re-use. Yet the texts that comprise datasets for analysis are frequently protected by copyright or other intellectual property rights that limit their access and use. This article discusses the role of libraries at the intersection of data mining and intellectual property, asserting that academic libraries are vital partners in enabling scholars to effectively incorporate text data mining into their research. We report on activities leading up to an IMLS-funded National Forum of stakeholders and discuss preliminary findings from a systematic literature review, as well as initial results of interviews with forum stakeholders. Emerging themes suggest the need for a multi-pronged distributed approach that includes a public campaign for building awareness and advocacy, development of best practice guides for library support services and training, and international efforts toward data standardization and copyright harmonization
It’s How Many Terabytes?! A Case Study on Managing Large Born Digital Audio-visual Acquisitions
Get PDFIn October 2014, the University of California Irvine (UCI) Special Collections and Archives acquired a born digital collection of 2.5 terabytes – the largest born digital collection acquired by the department to date. This case study describes the challenges we encountered when applying existing archival procedures to appraise, store, and provide access to a large born digital collection. It discusses solutions when they could be found and ideas for solutions when they could not, lessons learned from the experience, and the impact on born-digital policy and procedure at UCI Libraries. Working with a team of archivists, librarians, IT, and California Digital Library (CDL) staff, we discovered issues and determined solutions that will guide our procedures for future acquisitions of large and unwieldy born digital collections.Â
Building Tools to Facilitate Data Reuse
Get PDFThe Australian National Data Service (ANDS) has been funded by the Australian Government since 2009, with a goal to increase the value of data to researchers, research institutions and the nation. To achieve this goal, ANDS has funded more than 200 projects under seven programs. This paper provides an overview of one of these programs, the Applications Program, which focused on funding software infrastructure to enable data reuse to demonstrate the value of making data available to researchers. The paper also presents some representative projects, a summary of what the program has achieved, and lessons learned.Â
Education for Real-World Data Science Roles (Part 2): A Translational Approach to Curriculum Development
Get PDFThis study reports on the findings from Part 2 of a small-scale analysis of requirements for real-world data science positions and examines three further data science roles: data analyst, data engineer and data journalist. The study examines recent job descriptions and maps their requirements to the current curriculum within the graduate MLIS and Information Science and Technology Masters Programs in the School of Information Sciences (iSchool) at the University of Pittsburgh. From this mapping exercise, model ‘course pathways’ and module ‘stepping stones’ have been identified, as well as course topic gaps and opportunities for collaboration with other Schools. Competency in four specific tools or technologies was required by all three roles (Microsoft Excel, R, Python and SQL), as well as collaborative skills (with both teams of colleagues and with clients). The ability to connect the educational curriculum with real-world positions is viewed as further validation of the translational approach being developed as a foundational principle of the current MLIS curriculum review processÂ
Evaluating the Effectiveness of Data Management Training: DataONE’s Survey Instrument
Get PDFEffective management is a key component for preparing data to be retained for future long term access, use, and reuse by a broader community. Developing the skills to plan and perform data management tasks is important for individuals and institutions. Teaching data literacy skills may also help to mitigate the impact of data deluge and other effects of being overexposed to and overwhelmed by data.
The process of learning how to manage data effectively for the entire research data lifecycle can be complex. There are often multiple stages involved within a lifecycle for managing data, and each stage may require specific knowledge, expertise, and resources. Additionally, although a range of organizations offers data management education and training resources, it can often be difficult to assess how effective the resources are for educating users to meet their data management requirements.
In the case of Data Observation Network for Earth (DataONE), DataONE’s extensive collaboration with individuals and organizations has informed the development of multiple educational resources. Through these interactions, DataONE understands that the process of creating and maintaining educational materials that remain responsive to community needs is reliant on careful evaluations. Therefore, the impetus for a comprehensive, customizable Education EVAluation instrument (EEVA) is grounded in the need for tools to assess and improve current and future training and educational resources for research data management.
In this paper, the authors outline and provide context for the background and motivations that led to creating EEVA for evaluating the effectiveness of data management educational resources. The paper details the process and results of the current version of EEVA. Finally, the paper highlights the key features, potential uses, and the next steps in order to improve future extensions and revisions of EEVA
Curation After the Fact: Practical and Ethical Challenges of Archiving Legacy Evaluation Data
Get PDFOver a 12-year period, the Atlantic Philanthropies invested more than €127m in agencies and community groups, running 52 prevention and early intervention (PEI) programmes and services in the children and youth sector throughout Ireland. As a condition of this funding, each PEI programme was evaluated by a university-based research team, resulting in a substantial collection of metric and qualitative information about ways to improve the lives of vulnerable Irish families. In 2016, the Atlantic Philanthropies funded the Prevention and Early Intervention Research Initiative at the Children’s Research Network of Ireland and Northern Ireland (hereafter, the Initiative) to gather, prepare and share this evaluation data through the public data archives.
The Initiative faces several challenges in its objective to archive this extensive collection of legacy data, and this paper will present two of the more salient challenges: how to share this data so that it is both (1) meaningful and (2) ethical. The paper pays particular attention to the challenges of safely sharing evaluation data through anonymisation and restricted access conditions; and also, the practical and ethical challenges of retroactively preparing these datasets for the archive.
A series of publicly available documents that guide each stage of the Initiative are in development, and are emerging as a key output. This paper will describe two pivotal documents, namely the CRN-PEI Guiding Principles, and the CRN-PEI Protocols for preparing and archiving evaluation data. The CRN-PEI Guiding Principles outline the key legal and ethical obligations of archiving this legacy evaluation data, and act as moral compass to steer our progress through these uncharted waters. The CRN-PEI Protocols define the standards for how data included in the Initiative is prepared for deposition in the public data archives, so they are easily located, interpretable and comparable in the long term. This protocol is based upon best practice documentation from a number of international sources and our primary aim is to generate ‘safe, useful data’ (Elliot at al., 2016)
Persistent Identification and Citation of Software
Get PDFSoftware underpins the academic research process across disciplines. To be able to understand, use/reuse and preserve data, the software code that generated, analysed or presented the data will need to be retained and executed. An important part of this process is being able to persistently identify the software concerned. This paper discusses the reasons for doing so and introduces a model of software entities to enable better identification of what is being identified. The DataCite metadata schema provides a persistent identification scheme and we consider how this scheme can be applied to software. We then explore examples of persistent identification and reuse. The examples show the differences and similarities of software used in academic research, which has been written and reused at different scales. The key concepts of being able to identify what precisely is being used and provide a mechanism for appropriate credit are important to both of them. Â
A Survey of Digital Preservation Challenges in Nigerian Libraries: Librarians\u27 Perspectives
Get PDFThis paper investigates digital preservation challenges in Nigerian libraries. In carrying out this study four research questions were posed. The study sample population comprised of 172 participants at the 2nd Conference of Certified Librarians from various libraries and institutions across Nigeria, organised by the Librarians’ Registration Council of Nigeria (LRCN) in Abuja on the 11th – 16th October, 2015. The outcome of the study revealed that digital preservation challenges persist despite the awareness of digital preservation strategies by librarians in Nigerian libraries. The findings revealed major challenges facing digital preservation, such as hardware and software obsolesces, lack of training, lack of backup and standards, lack of strategy policy, lack of funds, lukewarm attitude among the librarians and lack of legal right to preservation of content. Recommendations were made to protect and safeguard digital preservation challenges in the libraries, including the recommendation that the Nigerian Library Association (NLA), Librarians Registration Council of Nigeria (LRCN), University management and Library stakeholders should create a standard policy, provide needed skills for the librarians, lobby government for more funds and ensure that funds allocated to the libraries are properly utilised for effective digitization of library resources for future use
Research Transparency: A Preliminary Study of Disciplinary Conceptualisation, Drivers, Tools and Support Services
Get PDFThis paper describes a preliminary study of research transparency, which draws on the findings from four focus group sessions with faculty in chemistry, law, urban and social studies, and civil and environmental engineering. The multi-faceted nature of transparency is highlighted by the broad ways in which the faculty conceptualised the concept (data sharing, ethics, replicability) and the vocabulary they used with common core terms identified (data, methods, full disclosure). The associated concepts of reproducibility and trust are noted. The research lifecycle stages are used as a foundation to identify the action verbs and software tools associated with transparency. A range of transparency drivers and motivations are listed. The role of libraries and data scientists is discussed in the context of the provision of transparency services for researchers