Research Data Management Training for Geographers: First Impressions

This paper will describe the efforts and findings of the JISC Data Management Skills Support Initiative (‘DaMSSI’). DaMSSI was co-funded by the JISC Managing Research Data programme and the Research Information Network (RIN), in partnership with the Digital Curation Centre, to review, synthesise and augment the training offerings of the JISC Research Data Management Training Materials (‘RDMTrain’) projects.DaMSSI tested the effectiveness of the Society of College, National and University Libraries’ Seven Pillars of Information Literacy model (SCONUL, 2011), and Vitae’s Researcher Development Framework (‘Vitae RDF’) for consistently describing research data management (‘RDM’) skills and skills development paths in UK HEI postgraduate courses.With the collaboration of the RDMTrain projects, we mapped individual course modules to these two models and identified basic generic data management skills alongside discipline-specific requirements. A synthesis of the training outputs of the projects was then carried out, which further investigated the generic versus discipline-specific considerations and other successful approaches to training that had been identified as a result of the projects’ work. In addition we produced a series of career profiles to help illustrate the fact that data management is an essential component – in obvious and not-so-obvious ways – of a wide range of professions.We found that both models had potential for consistently and coherently describing data management skills training and embedding this within broader institutional postgraduate curricula. However, we feel that additional discipline-specific references to data management skills could also be beneficial for effective use of these models. Our synthesis work identified that the majority of core skills were generic across disciplines at the postgraduate level, with the discipline-specific approach showing its value in engaging the audience and providing context for the generic principles.Findings were fed back to SCONUL and Vitae to help in the refinement of their respective models, and we are working with a number of other projects, such as the DCC and the EC-funded Digital Curator Vocational Education Europe (DigCurV2) initiative, to investigate ways to take forward the training profiling work we have begun.

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Researcher training in spreadsheet curation

International Journal of Digital Curation ◽

10.2218/ijdc.v12i2.507 ◽

2018 ◽

Vol 12 (2) ◽

pp. 116-124

Author(s):

Gene Lyddon Melzack

Keyword(s):

Data Management ◽

Management Training ◽

Skills Training ◽

Research Data ◽

Practical Skills ◽

Research Data Management ◽

Qualitative Feedback ◽

Hands On ◽

Software Skills ◽

Data Documentation

Spreadsheets are commonly used across most academic discplines, however their use has been associated with a number of issues that affect the accuracy and integrity of research data. In 2016, new training on spreadsheet curation was introduced at the University of Sydney to address a gap between practical software skills training and generalised research data management training. The approach to spreadsheet curation behind the training was defined and the training's distinction from other spreadsheet curation training offering described.\parThe uptake of and feedback on the training were evaluated. Training attendance was analysed by discipline and by role. Quantitative and qualitative feedback were analysed and discussed. Feedback revealed that many attendees had been expecting and desired practical spreadsheet software skills training. Issues relating to whether or not practical skills training should and can be integrated with curation training were discussed. While attendees were found to be predominantly from science disciplines, qualitative feedback suggests that humanities attendees have specific needs in relation to managing data with spreadsheets that are currently not being met. Feedback also suggested that some attendees would prefer the curation training to be delivered as a longer, more in depth, hands on workshop.\parThe impact of the training was measured using data collected from the University's Research Data Management Planning (RDMP) tool and the Sydney eScholarship Repository. RDMP descriptions of spreadsheet data and records of tabular datasets published in the repository were analysed and assessed for quality and for accompanying data documentation. No significant improvements in data documentation or quality were found, however it is likely too soon after the launch of the training program to have seen much in the way of impact.\parIdentified next steps include clarifying the marketing material promoting to the training to better communicate the curation focus, investigating the needs of humanities researchers working with qualitative data in spreadsheets, and incorporating new material into the training in order to address those needs. Integrating curation training with practical skills training and modifying the training to be more hands on are changes that may be considered in future, but will not be implemented at this stage.

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Building and Development of Research Data Management Training Tool

Joho Chishiki Gakkaishi ◽

10.2964/jsik_2017_042 ◽

2017 ◽

Vol 27 (4) ◽

pp. 362-365

Author(s):

Mao Tsunekawa ◽

Eriko Amano ◽

Hayahiko Ozono ◽

Yui Nishizono ◽

Shota Maeda ◽

...

Keyword(s):

Data Management ◽

Management Training ◽

Research Data ◽

Training Tool ◽

Research Data Management

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Delineating the successful features of research data management training: a systematic review

The International Journal for Academic Development ◽

10.1080/1360144x.2021.1898399 ◽

2021 ◽

pp. 1-16

Author(s):

Cherry Zin Oo ◽

Adrian W. Chew ◽

Adeline L. H. Wong ◽

Joanne Gladding ◽

Cecilia Stenstrom

Keyword(s):

Systematic Review ◽

Data Management ◽

Management Training ◽

Research Data ◽

Research Data Management

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Education Needs in Research Data Management for Science-Based Disciplines

Issues in Science and Technology Librarianship ◽

10.29173/istl12 ◽

2019 ◽

Author(s):

Judith E Pasek ◽

Jennifer Mayer

Keyword(s):

Graduate Students ◽

Data Management ◽

Data Visualization ◽

Management Training ◽

Research Data ◽

Academic Community ◽

Data Conversion ◽

Data Preservation ◽

Research Data Management ◽

Doctoral Universities

Research data management is a prominent and evolving consideration for the academic community, especially in scientific disciplines. This research study surveyed 131 graduate students and 79 faculty members in the sciences at two public doctoral universities to determine the importance, knowledge, and interest levels around research data management training and education. The authors adapted 12 competencies for measurement in the study. Graduate students and faculty ranked the following areas most important among the 12 competencies: ethics and attribution, data visualization, and quality assurance. Graduate students indicated they were least knowledgeable and skilled in data curation and re-use, metadata and data description, data conversion and interoperability, and data preservation. Their responses generally matched the perceptions of faculty. The study also examined how graduate students learn research data management, and how faculty perceive that their students learn research data management. Results showed that graduate students utilize self-learning most often and that faculty may be less influential in research data management education than they perceive. Responses for graduate students between the two institutions were not statistically different, except in the area of perceived deficiencies in data visualization competency.

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On a Quest for Cultural Change - Surveying Research Data Management Practices at Delft University of Technology

10.31219/osf.io/mq23t ◽

2019 ◽

Author(s):

Heather Andrews ◽

Marta Teperek ◽

Jasper van Dijck ◽

Kees den Heijer ◽

Robbert Eggermont ◽

...

Keyword(s):

Data Management ◽

Management Practices ◽

Management Training ◽

Research Data ◽

Data Repositories ◽

Automatic Data ◽

Awareness Campaigns ◽

Research Data Management ◽

University Of Technology ◽

Data Stewardship

The Data Stewardship project is a new initiative from the Delft University of Technology (TU Delft) in the Netherlands. Its aim is to create mature working practices and policies regarding research data management across all TU Delft faculties. The novelty of this project relies on having a dedicated person, the so-called ‘Data Steward’, embedded in each faculty to approach research data management from a more discipline-specific perspective. It is within this framework that a research data management survey was carried out at the faculties that had a Data Steward in place by July 2018. The goal was to get an overview of the general data management practices, and use its results as a benchmark for the project. The total response rate was 11 to 37% depending on the faculty. Overall, the results show similar trends in all faculties, and indicate lack of awareness regarding different data management topics such as automatic data backups, data ownership, relevance of data management plans, awareness of FAIR data principles and usage of research data repositories. The results also show great interest towards data management, as more than ~80% of the respondents in each faculty claimed to be interested in data management training and wished to see the summary of survey results. Thus, the survey helped identified the topics the Data Stewardship project is currently focusing on, by carrying out awareness campaigns and providing training at both university and faculty levels.

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Teaching Research Data Management

Innovations in Teaching & Learning Conference Proceedings ◽

10.13021/g8fc73 ◽

2014 ◽

Vol 6 ◽

Author(s):

Wendy Mann

Keyword(s):

Graduate Students ◽

Data Management ◽

Management Training ◽

Boot Camp ◽

Research Data ◽

University Libraries ◽

Management Skills ◽

Data Services ◽

Research Data Management ◽

The University

In January 2014, Mason Libraries along with four other libraries in Virginia used 4-VA telepresence technology to teach a two-day boot camp to graduate students on research data management. Our workshop generated greater than expected interest from graduate students here at Mason. One lesson learned is that there appears to be a gap in the curriculum across all participating schools regarding the teaching of data management skills to budding researchers. This session will be an overview of the learning outcomes from the Data Management Boot Camp, how the University Libraries' Data Services carries out research data management training, and discussion of future plans for helping researchers organize and manage their data.

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An initial evaluation of research data management online training at the University of New South Wales

IFLA Journal ◽

10.1177/03400352211054120 ◽

2021 ◽

pp. 034003522110541

Author(s):

Adrian W Chew ◽

Cherry Zin Oo ◽

Adeline LH Wong ◽

Joanne Gladding

Keyword(s):

Data Management ◽

New South ◽

New South Wales ◽

Online Training ◽

Management Training ◽

Research Data ◽

Initial Evaluation ◽

Research Data Management ◽

South Wales ◽

The University

In response to low research data management engagement at the University of New South Wales, Australia, an introductory research data management online training was developed and rolled out to all newly enrolled Higher Degree Research candidates. This article outlines the development process of the research data management online training and provides an initial evaluation of the training from the perspectives of the candidates and the university. As such, this article joins up with existing literature on research data management training to assist institutions and research data management stakeholders with the development of research data management training to help researchers and research students enact research data management best practices. Overall, the majority of the candidates ( n = 643) were satisfied with the quality of the training and found it helpful. The benefits the training brought to the university are mapped out by linking institutional research data management problems, the research data management online training’s design and findings into a coherent narrative.

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Exploring digital preservation requirements

Records Management Journal ◽

10.1108/rmj-04-2017-0009 ◽

2017 ◽

Vol 27 (2) ◽

pp. 175-191 ◽

Cited By ~ 3

Author(s):

Jaana Pinnick

Keyword(s):

Data Management ◽

Digital Preservation ◽

Management Training ◽

Research Data ◽

Content Type ◽

Research Data Management ◽

Mixed Methods Case Study ◽

Management Processes ◽

Digital Asset

Purpose The aim of this paper was to explore digital preservation requirements within the wider National Geoscience Data Centre (NGDC) organisational framework in preparation for developing a preservation policy and integrating associated preservation workflows throughout the existing research data management processes. This case study is based on an MSc dissertation research undertaken at Northumbria University. Design/methodology/approach This mixed methods case study used quantitative and qualitative data to explore the preservation requirements and triangulation to strengthen the design validity. Corporate and the wider scientific priorities were identified through literature and a stakeholder survey. Organisational preparedness was investigated through staff interviews. Findings Stakeholders expect data to be reliable, reusable and available in preferred formats. To ensure digital continuity, the creation of high-quality metadata is critical, and data depositors need data management training to achieve this. Recommendations include completing a risk assessment, creating a digital asset register and a technology watch to mitigate against risks. Research limitations/implications The main constraint in this study is the lack of generalisability of results. As the NGDC is a unique organisation, it may not be possible to generalise the organisational findings, although those relating to research data management may be transferrable. Originality/value This research examines the specific nature of geoscience data retention requirements and looks at existing NGDC procedures in terms of enhancing digital continuity, providing new knowledge on the preservation requirements for a number of national datasets.

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