http://www.ijdc.net/issue/feed International Journal of Digital Curation 2019-11-21T02:14:53+00:00 IJDC Editorial Team ijdc@mlist.is.ed.ac.uk Open Journal Systems <p>The IJDC publishes pre-prints, peer-reviewed papers, articles and editorials on digital curation, research data management and related issues. &nbsp;It complements the International Conference on Digital Curation (IDCC) and includes selected proceedings.</p> http://www.ijdc.net/article/view/556 Digital Curation Education at the Universities of Ibadan and Liverpool 2019-11-21T02:14:52+00:00 Abiola Abioye biolaabioye@gmail.com James Lowry jlowry@liverpool.ac.uk Rosemary Lynch rosemaryclarelynch@gmail.com <p>This article presents the findings of the Ibadan/Liverpool Digital Curation Curriculum Review Project, a research project conducted to formally benchmark the teaching of digital curation in the archival education programmes at the University of Liverpool, United Kingdom and the University of Ibadan, Nigeria. It provides background to the history and establishment of both universities and the development of their archives curricula. A matrix was developed using the DigCurV Curriculum Framework to assess whether digital curation skills and knowledge outlined in the framework are being taught, practised and tested in the Master’s programmes. These skills and knowledge were assessed according to the four domains outlined in DigCurV: Knowledge and Intellectual Abilities (KIA), Personal Qualities (PQ), Professional Conduct (PC), and Management and Quality Assurance (MQA), to levels appropriate to practitioners and managers. The exercise identified skill and knowledge areas where teaching materials could be shared between the universities, and areas where new materials are needed.</p> 2019-09-11T10:00:11+01:00 ##submission.copyrightStatement## http://www.ijdc.net/article/view/595 Progress in Research Data Services 2019-11-21T02:14:48+00:00 Andrew M Cox, Dr a.m.cox@sheffield.ac.uk Mary Anne Kennan, Dr maryanne.kennan@gmail.com Elizabeth Josephine Lyon, Dr elyon@pitt.edu Stephen Pinfield, Dr s.pinfield@sheffield.ac.uk Laura Sbaffi, Dr l.sbaffi@sheffield.ac.uk <p class="abstract-western">University libraries have played an important role in constructing an infrastructure of support for Research Data Management at an institutional level. This paper presents a comparative analysis of two international surveys of libraries about their involvement in Research Data Services conducted in 2014 and 2018. The aim was to explore how services had developed over this time period, and to explore the drivers and barriers to change. In particular, there was an interest in how far the FAIR data principles had been adopted.</p> <p class="abstract-western">Services in nearly every area were more developed in 2018 than before, but technical services remained less developed than advisory. Progress on institutional policy was also evident. However, priorities did not seem to have shifted significantly. Open ended answers suggested that funder policy, rather than researcher demand, remained the main driver of service development and that resources and skills gaps remained issues. While widely understood as an important reference point and standard, because of their relatively recent publication date, FAIR principles had not been widely adopted explicitly in policy.</p> 2019-09-11T10:25:44+01:00 ##submission.copyrightStatement## http://www.ijdc.net/article/view/594 Putting the Trust into Trusted Data Repositories: A Federated Solution for the Australian National Imaging Facility 2019-11-21T02:14:51+00:00 Andrew James Mehnert andrew.mehnert@uwa.edu.au Andrew Janke andrew.janke@sydney.edu.au Marco Gruwel marco.gruwel@gmail.com Wojtek James Goscinski wojtek.goscinski@monash.edu Thomas Close tom.close@monash.edu Dean Taylor dean.taylor@uwa.edu.au Aswin Narayanan a.narayanan@uq.edu.au George Vidalis george.vidalis@monash.edu Graham Galloway g.galloway@uq.edu.au Andrew Treloar andrew.treloar@ardc.edu.au <p align="justify"><span style="font-size: small;">The National Imaging Facility (NIF) provides Australian researchers with state-of-the-art instrumentation—including magnetic resonance imaging (MRI), positron emission tomography (PET), X-ray computed tomography (CT) and multispectral imaging – and expertise for the characterisation of animals, plants and materials. </span></p> <p align="justify"><span style="font-size: small;">To maximise research outcomes, as well as to facilitate collaboration and sharing, it is essential not only that the data acquired using these instruments be managed, curated and archived in a trusted data repository service, but also that the data itself be of verifiable quality. In 2017, several NIF nodes collaborated on a national project to define the requirements and best practices necessary to achieve this, and to establish exemplar services for both preclinical MRI data and clinical ataxia MRI data.</span></p> <p align="justify"><span style="font-size: small;">In this paper we describe the project, its key outcomes, challenges and lessons learned, and future developments, including extension to other characterisation facilities and instruments/modalities.</span></p> 2019-09-11T10:14:29+01:00 ##submission.copyrightStatement## http://www.ijdc.net/article/view/643 Updating the Data Curation Continuum 2019-11-21T02:14:51+00:00 Andrew Treloar andrew.treloar@ands.org.au Jens Klump jens.klump@csiro.au <p class="Abstract"><span lang="EN-GB">The Data Curation Continuum was developed as a way of thinking about data repository infrastructure. Since its original development over a decade ago, a number of things have changed in the data infrastructure domain. This paper revisits the thinking behind the original data curation continuum and updates it to respond to changes in research objects, storage models, and the repository landscape in general. </span></p> <p>&nbsp;</p> 2019-09-11T10:10:47+01:00 ##submission.copyrightStatement## http://www.ijdc.net/article/view/586 Identifying Topical Coverages of Curricula using Topic Modeling and Visualization Techniques: A Case of Digital and Data Curation 2019-11-21T02:14:52+00:00 Seungwon Yang seungwonyang@lsu.edu Boryung Ju bju1@lsu.edu Haeyong Chung haeyong.chung@uah.edu <p>Digital/data curation curricula have been around for a couple of decades. Currently, several ALA-accredited LIS programs offer digital/data curation courses and certificate programs to address the high demand for professionals with the knowledge and skills to handle digital content and research data in an ever-changing information environment.&nbsp; In this study, we aimed to examine the topical scopes of digital/data curation curricula in the context of the LIS field.&nbsp; We collected 16 syllabi from the digital/data curation courses, as well as textual descriptions of the 11 programs and their core courses offered in the U.S., Canada, and the U.K. The collected data were analyzed using a probabilistic topic modeling technique, Latent Dirichlet Allocation, to identify both common and unique topics. The results are the identification of 20 topics both at the program- and course-levels. Comparison between the program- and course-level topics uncovered a set of unique topics, and a number of common topics.&nbsp; Furthermore, we provide interactive visualizations for digital/data curation programs and courses for further analysis of topical distributions. We believe that our combined approach of a topic modeling and visualizations may provide insight for identifying emerging trends and co-occurrences of topics among digital/data curation curricula in the LIS field.</p> 2019-09-11T10:04:22+01:00 ##submission.copyrightStatement## http://www.ijdc.net/article/view/590 Developing a data management consultation service for faculty researchers: A case study from a large Midwestern public university 2019-11-21T02:14:53+00:00 Virginia A Dressler vdressle@kent.edu Kristin Yeager kyeager4@kent.edu Elizabeth Richardson earicha1@kent.edu <p class="abstract-western" lang="en-US">To inform the development of data management services, a library research team at Kent State University conducted a survey of all tenured, tenure-track, and non-tenure track faculty about their data management practices and perceptions. The methodology and results will be presented in the article, as well as how this information was used to inform future work in the library’s internal working group. Recommendations will be presented that other academic libraries could model in order to develop similar services at their institutions. Personal anecdotes are included that help ascertain current practices and sentiments around research data from the perspective of the researcher. The article addresses the particular needs of a large Midwestern U.S. academic campus, which are not currently reflected in literature on the topic.</p> 2019-09-11T09:57:14+01:00 ##submission.copyrightStatement## http://www.ijdc.net/article/view/637 Experimental Data Curation at Large Instrument Facilities with Open Source Software 2019-11-21T02:14:51+00:00 Line Pouchard pouchard@bnl.gov Kerstin Kleese van Dam kleese@bnl.gov Stuart I Campbell scampbell@bnl.gov <p>The National Synchrotron Light Source II operating at Brookhaven National Laboratory since 2014 for the US Department of Energy is one of the newest and brightest storage-ring synchrotron facility in the world.&nbsp; NSLS-II, like other facilities, provides pre-processing of the raw data and some analysis capabilities to its users. We describe the research collaborations and open source infrastructure &nbsp;developed at large instrument facilities such as NSLS-II for the purpose of curating high value scientific data along the early stages of the data lifecycle.&nbsp; Data acquisition and curation tasks include storing experiment configuration, detector metadata, raw data acquisition with infrastructure that converts proprietary instrument formats to industry standards.&nbsp; In addition, we describe a specific effort for discovering sample information at NSLS-II and tracing the provenance of analysis performed on acquired images.&nbsp; We show that curation tasks must be embedded into software along the data life cycle for effectiveness and ease of use, and that loosely defined collaborations evolve around shared open source tools.&nbsp; Finally we discuss best practices for experimental metadata capture in such facilities, data access and the new challenges of scale and complexity posed by AI-based discovery for the synthesis of new materials.</p> 2019-09-11T10:22:22+01:00 ##submission.copyrightStatement##