International Journal of Digital Curation
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Reshaping the DCC Institutional Engagement Programme
Get PDFThis paper shares results from the Digital Curation Centre’s programme of Institutional Engagements (IEs), and describes how we continue to provide tailored support on Research Data Management (RDM) to the UK higher education sector.Between Spring 2011 and Spring 2013, the DCC ran a series of 21 Institutional Engagements. The engagement programme involved helping institutions to assess their needs, develop policy and strategy, and begin to implement a range of RDM services.We have conducted a synthesis and evaluation of the programme, analysing the types of assistance requested and the impact of our support. The findings and lessons to emerge from these exercises have informed our future strategy and helped reshape the programme
Building Infrastructure for Preservation and Publication of Earthquake Engineering Research Data
Get PDFThe objective of this paper is to showcase the progress of the earthquake engineering community during a decade-long effort supported by the National Science Foundation in the George E. Brown Jr., Network for Earthquake Engineering Simulation (NEES). During the four years that NEES network operations have been headquartered at Purdue University, the NEEScomm management team has facilitated an unprecedented cultural change in the ways research is performed in earthquake engineering. NEES has not only played a major role in advancing the cyberinfrastructure required for transformative engineering research, but NEES research outcomes are making an impact by contributing to safer structures throughout the USA and abroad. This paper reflects on some of the developments and initiatives that helped instil change in the ways that the earthquake engineering and tsunami community share and reuse data and collaborate in general
Process Management Plans
Get PDFIn the era of research infrastructures and big data, sophisticated data management practices are becoming essential building blocks of successful science. Most practices follow a data-centric approach, which does not take into account the processes that created, analysed and presented the data. This fact limits the possibilities for reliable verification of results. Furthermore, it does not guarantee the reuse of research, which is one of the key aspects of credible data-driven science. For that reason, we propose the introduction of the new concept of Process Management Plans, which focus on the identification, description, sharing and preservation of the entire scientific processes. They enable verification and later reuse of result data and processes of scientific experiments. In this paper we describe the structure and explain the novelty of Process Management Plans by showing in what way they complement existing Data Management Plans. We also highlight key differences, major advantages, as well as references to tools and solutions that can facilitate the introduction of Process Management Plans
Data Producers Courting Data Reusers: Two Cases from Modeling Communities
Get PDFData sharing is a difficult process for both the data producer and the data reuser. Both parties are faced with more disincentives than incentives. Data producers need to sink time and resources into adding metadata for data to be findable and usable, and there is no promise of receiving credit for this effort. Making data available also leaves data producers vulnerable to being scooped or data misuse. Data reusers also need to sink time and resources into evaluating data and trying to understand them, making collecting their own data a more attractive option. In spite of these difficulties, some data producers are looking for new ways to make data sharing and reuse a more viable option. This paper presents two cases from the surface and climate modeling communities, where researchers who produce data are reaching out to other researchers who would be interested in reusing the data. These cases are evaluated as a strategy to identify ways to overcome the challenges typically experienced by both data producers and data reusers. By working together with reusers, data producers are able to mitigate the disincentives and create incentives for sharing data. By working with data producers, data reusers are able to circumvent the hurdles that make data reuse so challenging
Committing to Data Quality Review
Get PDFAmid the pressure and enthusiasm for researchers to share data, a rapidly growing number of tools and services have emerged. What do we know about the quality of these data? Why does quality matter? And who should be responsible for data quality? We believe an essential measure of data quality is the ability to engage in informed reuse, which requires that data are independently understandable. In practice, this means that data must undergo quality review, a process whereby data and associated files are assessed and required actions are taken to ensure files are independently understandable for informed reuse. This paper explains what we mean by data quality review, what measures can be applied to it, and how it is practiced in three domain-specific archives. We explore a selection of other data repositories in the research data ecosystem, as well as the roles of researchers, academic libraries, and scholarly journals in regard to their application of data quality measures in practice. We end with thoughts about the need to commit to data quality and who might be able to take on those tasks
Towards Automated Design, Analysis and Optimization of Declarative Curation Workflows
Get PDFData curation is increasingly important. Our previous work on a Kepler curation package has demonstrated advantages that come from automating data curation pipelines by using workflow systems. However, manually designed curation workflows can be error-prone and inefficient due to a lack of user understanding of the workflow system, misuse of actors, or human error. Correcting problematic workflows is often very time-consuming. A more proactive workflow system can help users avoid such pitfalls. For example, static analysis before execution can be used to detect the potential problems in a workflow and help the user to improve workflow design. In this paper, we propose a declarative workflow approach that supports semi-automated workflow design, analysis and optimization. We show how the workflow design engine helps users to construct data curation workflows, how the workflow analysis engine detects different design problems of workflows and how workflows can be optimized by exploiting parallelism
Guidelines on Recommending Data Repositories as Partners in Publishing Research Data
Get PDFThis document summarises guidelines produced by the UK Jisc-funded PREPARDE data publication project on the key issues of repository accreditation. It aims to lay out the principles and the requirements for data repositories intent on providing a dataset as part of the research record and as part of a research publication. The data publication requirements that repository accreditation may support are rapidly changing, hence this paper is intended as a provocation for further discussion and development in the future
The DigCurV Curriculum Framework for Digital Curation in the Cultural Heritage Sector
Get PDFIn 2013, the DigCurV collaborative network completed development of a Curriculum Framework for digital curation skills in the European cultural heritage sector. DigCurV synthesised a variety of established skills and competence models in the digital curation and LIS sectors with expertise from digital curation professionals, in order to develop a new Curriculum Framework. The resulting Framework provides a common language and helps define the skills, knowledge and abilities that are necessary for the development of digital curation training; for benchmarking existing programmes; and for promoting the continuing production, improvement and refinement of digital curation training programmes. This paper describes the salient points of this work, including how the project team conducted the research necessary to develop the Framework, the structure of the Framework, the processes used to validate the Framework, and three ‘lenses’ onto the Framework. The paper also provides suggestions as to how the Framework might be used, including a description of potential audiences and purposes
A Digital Archives Framework for the Preservation of Cultural Artifacts with Technological Components
No full textThe preservation of artistic works with technological components, such as musical works, is recognised as an issue by both the artistic community and the archival community. Preserving such works involves tackling the difficulties associated with digital information in general, but also raises its own specific problems, such as constantly evolving digital instruments embodied within software and idiosyncratic human-computer interactions. Because of these issues, standards in place for archiving digital information are not always suitable for the preservation of these works. The impact on the organisation and the descriptions of such archives need to be conceptualised in order to provide these technological components with readability, authenticity and intelligibility. While previous projects emphasized readability and authenticity, less effort has been dedicated to addressing intelligibility issues.The research into the specification of significant properties and its extension, namely significant knowledge, offers some grounds for reflecting on this question. Furthermore, the relevance of taking into account the creative process involved in the production of technological components offers an opportunity to redefine the status of technological agents in the performative aspect of digital records. Altogether, the research on significant knowledge and creative processes provide us with a conceptual framework that we propose to bring together with digital archives models to form a coherent framework
Meeting the Data Management Compliance Challenge: Funder Expectations and Institutional Reality
Get PDFIn common with many global research funding agencies, in 2011 the UK Engineering and Physical Sciences Research Council (EPSRC) published its Policy Framework on Research Data along with a mandate that institutions be fully compliant with the policy by May 2015. The University of Bath has a strong applied science and engineering research focus and, as such, the EPSRC is a major funder of the university’s research. In this paper, the Jisc-funded Research360 project shares its experience in developing the infrastructure required to enable a research-intensive institution to achieve full compliance with a particular funder’s policy, in such a way as to support the varied data management needs of both the University of Bath and its external stakeholders. A key feature of the Research360 project was to ensure that after the project’s completion in summer 2013 the newly developed data management infrastructure would be maintained up to and beyond the EPSRC’s 2015 deadline. Central to these plans was the ‘University of Bath Roadmap for EPSRC’, which was identified as an exemplar response by the EPSRC. This paper explores how a roadmap designed to meet a single funder’s requirements can be compatible with the strategic goals of an institution. Also discussed is how the project worked with Charles Beagrie Ltd to develop a supporting business case, thus ensuring implementation of these long-term objectives. This paper describes how two new data management roles, the Institutional Data Scientist and Technical Data Coordinator, have contributed to delivery of the Research360 project and the importance of these new types of cross-institutional roles for embedding a new data management infrastructure within an institution. Finally, the experience of developing a new institutional data policy is shared. This policy represents a particular example of the need to reconcile a funder’s expectations with the needs of individual researchers and their collaborators