Education Needs in Research Data Management for Science-Based Disciplines

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.

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 ◽

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.

Research Data Management Training for Geographers: First Impressions

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi5040040 ◽

2016 ◽

Vol 5 (4) ◽

pp. 40 ◽

Cited By ~ 1

Author(s):

Kerstin Helbig

Keyword(s):

Data Management ◽

Management Training ◽

Research Data ◽

First Impressions ◽

The Data Management Skills Support Initiative: Synthesising Postgraduate Training in Research Data Management

International Journal of Digital Curation ◽

10.2218/ijdc.v7i2.233 ◽

2012 ◽

Vol 7 (2) ◽

pp. 101-109 ◽

Cited By ~ 5

Author(s):

Laura Molloy ◽

Kellie Snow

Keyword(s):

Data Management ◽

Management Training ◽

Skills Training ◽

Research Data ◽

Management Skills ◽

Research Information ◽

Researcher Development ◽

Development Framework ◽

Wide Range

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.

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 ◽

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.

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 ◽

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 ◽

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 ◽

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.

Doctoral Students' Educational Needs in Research Data Management: Perceived Importance and Current Competencies

International Journal of Digital Curation ◽

10.2218/ijdc.v16i1.684 ◽

2021 ◽

Vol 16 (1) ◽

pp. 36

Author(s):

Jukka Rantasaari

Keyword(s):

Data Management ◽

Doctoral Students ◽

Educational Needs ◽

Research Data ◽

Structured Interviews ◽

High Quality Research ◽

Management Planning ◽

Data Preservation ◽

Data Lifecycle

Sound research data management (RDM) competencies are elementary tools used by researchers to ensure integrated, reliable, and re-usable data, and to produce high quality research results. In this study, 35 doctoral students and faculty members were asked to self-rate or rate doctoral students’ current RDM competencies and rate the importance of these competencies. Structured interviews were conducted, using close-ended and open-ended questions, covering research data lifecycle phases such as collection, storing, organization, documentation, processing, analysis, preservation, and data sharing. The quantitative analysis of the respondents’ answers indicated a wide gap between doctoral students’ rated/self-rated current competencies and the rated importance of these competencies. In conclusion, two major educational needs were identified in the qualitative analysis of the interviews: to improve and standardize data management planning, including awareness of the intellectual property and agreements issues affecting data processing and sharing; and to improve and standardize data documenting and describing, not only for the researcher themself but especially for data preservation, sharing, and re-using. Hence the study informs the development of RDM education for doctoral students.

Research data management practices of chemistry researchers in federal universities of technology in Nigeria

Digital Library Perspectives ◽

10.1108/dlp-06-2020-0051 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Fatimah Jibril Abduldayan ◽

Fasola Petunola Abifarin ◽

Georgina Uchey Oyedum ◽

Jibril Attahiru Alhassan

Keyword(s):

Data Management ◽

Management Practices ◽

Management Practice ◽

Research Process ◽

Management Plan ◽

Research Data ◽

Content Type ◽

Data Preservation ◽

Research Findings

Purpose The purpose of this study was to understand the research data management practices of chemistry researchers in the five specialized federal universities of technology in Nigeria. Appropriate research data management practice ensures that research data are available for reuse by secondary users, and research findings can be verified and replicated within the scientific community. A poor research data management practice can lead to irrecoverable data loss, unavailability of data to support research findings and lack of trust in the research process. Design/methodology/approach An exploratory research technique involving semi-structured, oral and face-to-face interview is used to gather data on research data management practices of chemistry researchers in Nigeria. Interview questions were divided into four major sections covering chemistry researchers’ understanding of research data, experience with data loss, data storage method and backup techniques, data protection, data preservation and availability of data management plan. Braun and Clarke thematic analysis approach was adapted, and the Provalis Qualitative Data Miner (version 5) software was used for generating themes and subthemes from the coding framework and for presenting the findings. Findings Findings revealed that chemistry researchers in Nigeria have a good understanding of the concept of research data and its importance to research findings. Chemistry researchers have had several experiences of irrecoverable loss of data because of poor choice of storage devices, back-up methods and weak data protection systems. Even though the library was agreed as the most preferred place for long-term data preservation, there is the issue of trust and fear of loss of ownership of data to unauthorized persons or party. No formal data management plan is used while conducting their scientific research. Research limitations/implications The research focused on research data management practices of chemistry researchers in the five specialized federal universities of technology in Nigeria. Although the findings of the study are similar to perceptions and practices of researchers around the world, it cannot be used as a basis for generalization across other scientific disciplines. Practical implications This study concluded that chemistry researchers need further orientation and continuous education on the importance and benefits of appropriate research data management practice. The library should also roll out research data management programs to guide researchers and improve their confidence throughout the research process. Social implications Appropriate research data management practice not only ensures that the underlying research data are true and available for reuse and re-validation, but it also encourages data sharing among researchers. Data sharing will help to ensure better collaboration among researchers and increased visibility of the datasets and data owners through the use of standard data citations and acknowledgements. Originality/value This is a qualitative and in-depth study of research data management practices and perceptions among researchers in a particular scientific field of study.

NRDC Data Visualization Web Suite

10.29007/rkqh ◽

2020 ◽

Author(s):

Andrew Muñoz ◽

Frederick Harris ◽

Sergiu Dascalu

Keyword(s):

Data Management ◽

Data Visualization ◽

Data Center ◽

Web Application ◽

Web Applications ◽

Research Data ◽

The State ◽

Environmental Data ◽

High Rate ◽

The Nevada Research Data Center (NRDC) is a research data management center that collects sensor-based data from various locations throughout the state of Nevada. The measurements collected are specifically environmental data, which are used in cross-disciplinary research across different facilities. Since data is being collected at a high rate, it is necessary to be able to visualize the data quickly and efficiently. This paper discusses in detail a web application that can be used by researchers to make visualizations that can help in data comparisons. While there exist other web applications that allows researchers to visualize the data, this project expands on that idea by allowing researchers the ability to not only visualize the data but also make comparisons and predictions.