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

Abstract

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.

Research data management competencies of researchers in selected public universities in South Africa

“…Halbert in Gunjal and Gaitanou (2017, p. 10), too, observed a lack of a sense of priority amongst researchers. Additionally, issues relating to culture are also evident in previous studies (Anduvare, 2019;Avuglah, 2016;Molloy and Snow, 2012;Morgan et al, 2017;Pinfield et al, 2014;Cox et al, 2017). Anduvare's (2019) study, for example, revealed that most universities face a cultural challenge when adopting RDM, in the sense that not every stakeholder will find it easy to migrate from one form of managing and handling data to another.…”

“…Numerous scholars and studies identify several competencies for better provision of RDM services in universities. Despite several identified RDM competencies and skills, most scholars agree that data curation skills are the most important for RDM services and practices (Molloy and Snow, 2012;Tripathi et al, 2017;Woeber, 2017;Nhendodzashe and Pasipamire, 2017;Chiware and Becker, 2018;Cox et al, 2019;Masinde et al, 2021). Data skills, sustained awareness of data creation, organisation, validation, sharing and curation are also identified as necessary RDM skills and knowledge (Molloy and Snow, 2012, p. 251).…”

“…Though skills and knowledge have been documented and emphasised as a requirement for proper handling and efficient management of research data in institutions of higher learning, it is unfortunate that most authors have highlighted skills deficits as a daunting challenge in RDM (Kahn et al, 2014;Cox and Pinfield, 2014;Cox et al, 2019;Chawinga and Zinn, 2020;Chawinga, 2019;Ng'eno, 2018;Cox et al, 2017;Avuglah and Underwood, 2019;Pinfield et al, 2014, p. 28;Chiware and Mathe, 2016;Cox et al, 2017). Also, RDM culture in terms of adoption (Anduvare, 2019;Avuglah, 2016;Molloy and Snow, 2012;Morgan et al, 2017;Pinfield et al, 2014) is a major concern. Other RDM challenges include a lack of training, a lack of resources, marketing and communication between the research community and the library, a lack of bandwidth, a lack of funding, organisational structures, professional preparation, the priority amongst researchers and institutional mandates (Hamad et al, 2021;Tang and Hu, 2019;the Council on Library and Information Resources CLIR, 2013;L€ otter, 2014;Anduvare, 2019;Chawinga, 2019;Ng'eno, 2018).…”

“…Numerous scholars and studies identify several competencies for better provision of RDM services in universities. Despite several identified RDM competencies and skills, most scholars agree that data curation skills are the most important for RDM services and practices (Molloy and Snow, 2012; Tripathi et al. , 2017; Woeber, 2017; Nhendodzashe and Pasipamire, 2017; Chiware and Becker, 2018; Cox et al ., 2019; Masinde et al.…”

Are you ready? Tasks and roles for academic libraries in supporting Research 2.0

“…DMPs represent the basic level of both RDM and RDS. Preparing DMPs has been the first and widespread activity that complies with the varied requirements of funding agencies (Molloy and Snow, 2012). There is also a model for assessing requirements for RDM support (Lyon et al, 2014), and -in general -it can be said that RDS has become a new embedded information service (Si et al, 2013).…”