scholarly journals Research Data Management and the Canadian Academic Library: An Organizational Consideration of Data Management and Data Stewardship

Author(s):  
Michael Steeleworthy
Author(s):  
Charles Humphrey

Portage is the research data management initiative of the Canadian Association of Research Libraries and its story has been very much about establishing partnerships in a complex environment to advance research data management services and infrastructure in Canada. Many jurisdictions make up the space in which research data management takes place. A variety of legal, political, cultural, economic, technological, and scientific factors are at play and how they fit together depends on the connections between a number of stakeholders. The levels at which these stakeholders operate and the transient nature of research data itself made the development of partnerships a complex undertaking for Portage. This article describes the building of partnerships in a multi-jurisdictional environment, discusses challenges in operating in Canada's digital research ecosystem, and highlights the importance of working with Canada's regional academic library associations in laying the foundations for digital research infrastructure to support data management. 


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Johnson Masinde ◽  
Jing Chen ◽  
Daniel Wambiri ◽  
Angela Mumo

Abstract University libraries have archaeologically augmented scientific research by collecting, organizing, maintaining, and availing research materials for access. Researchers reckon that with the expertise acquired from conventional cataloging, classification, and indexing coupled with that attained in the development, along with the maintenance of institutional repositories, it is only rational that libraries take a dominant and central role in research data management and further their capacity as curators. Accordingly, University libraries are expected to assemble capabilities, to manage and provide research data for sharing and reusing efficiently. This study examined research librarians’ experiences of RDM activities at the UON Library to recommend measures to enhance managing, sharing and reusing research data. The study was informed by the DCC Curation lifecycle model and the Community Capability Model Framework (CCMF) that enabled the Investigator to purposively capture qualitative data from a sample of 5 research librarians at the UON Library. The data was analysed thematically to generate themes that enabled the Investigator to address the research problem. Though the UON Library had policies on research data, quality assurance and intellectual property, study findings evidenced no explicit policies to guide each stage of data curation and capabilities. There were also inadequacies in skills and training capability, technological infrastructure and collaborative partnerships. Overall, RDM faced challenges in all the examined capabilities. These challenges limited the managing, sharing, and reusing of research data. The study recommends developing an RDM unit within the UON Library to oversee the implementation of RDM activities by assembling all the needed capabilities (policy guidelines, skills and training, technological infrastructure and collaborative partnerships) to support data curation activities and enable efficient managing, sharing and reusing research data.


2016 ◽  
Vol 49 (1) ◽  
pp. 3-14 ◽  
Author(s):  
Tibor Koltay

This paper describes data literacy and emphasizes its importance. Data literacy is vital for researchers who need to become data literate science workers and also for (potential) data management professionals. Its important characteristic is a close connection and similarity to information literacy. To support this argument, a review of literature was undertaken on the importance of data, and the data-intensive paradigm of scientific research, researchers’ expected and real behaviour, the nature of research data management, the possible roles of the academic library, data quality and data citation, Besides describing the nature of data literacy and enumerating the related skills, the application of phenomenographic approaches to data literacy and its relationship to the digital humanities have been identified as subjects for further investigation.


2019 ◽  
Author(s):  
Heather Andrews ◽  
Marta Teperek ◽  
Jasper van Dijck ◽  
Kees den Heijer ◽  
Robbert Eggermont ◽  
...  

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.


2019 ◽  
Vol 15 (2) ◽  
Author(s):  
Paloma Marín-Arraiza ◽  
Silvana Vidotti

RESUMO As tarefas de gestão de dados de pesquisa ao longo do processo de pesquisa têm se tornado muito importantes devido à alta produção de dados e à exigência da sua preservação. Tanto bibliotecas quanto seções de apoio à pesquisa de diversas instituições de ensino e pesquisa têm começado a implementar serviços para a gestão de dados e a profissionalização desta gestão. Com um caráter qualitativo, e após um levantamento bibliográfico em bases de dados abertas, contextualiza-se a gestão de dados de pesquisa, analisam-se os perfis profissionais e determinam-se três fases para a implementação institucional destes serviços: elaboração de uma política, estabelecimento de uma unidade de informação e integração de profissionais da gestão de dados.Palavras-chave: Administração de Dados; Dados de Pesquisa; Gestão de Dados de Pesquisa; Política de Dados; Serviços Institucionais.   ABSTRACT The tasks of managing research data throughout the research process have become very important due to the high production of data and the requirement for its preservation. Both libraries and research support sections of various research institutions have started to implement services for data management and the professionalization of this management. With a qualitative character, and after a bibliographic search in open databases, research data management is contextualized, professional profiles are analyzed, and three phases are determined for the institutional implementation of these services: the elaboration of a policy, the establishment of an information unit and the integration of data management professionals.Keywords: Data Stewardship; Research Data; Research Data Management; Data Policy; Institutional Services.


Author(s):  
Liisi Lembinen

Even though many academic libraries are offering various types of data management services (RDM) and infrastructure, many universities struggle with convincing researchers to publish their data. Collaboration in data management services between libraries, researchers, universities and government is the only way to make research data available and accessible. The purpose of this paper is to demonstrate how initiative from researchers led to wider collaboration between researchers and an academic library and resulted in the development of data management services in the library as well as a country-wide research data management consortium in Estonia. The country-wide research data management system was a requirement of the funding agency which put the library into a new position to initiate and lead work towards research universities' consortium. The development work of RDM services has tremendously raised the library's value as a partner rather than just a service provider in the eyes of researchers.


Author(s):  
Liisi Lembinen

Even though many academic libraries are offering various types of data management services (RDM) and infrastructure, many universities struggle with convincing researchers to publish their data. Collaboration in data management services between libraries, researchers, universities and government is the only way to make research data available and accessible. The purpose of this paper is to demonstrate how initiative from researchers led to wider collaboration between researchers and an academic library and resulted in the development of data management services in the library as well as a country-wide research data management consortium in Estonia. The country-wide research data management system was a requirement of the funding agency which put the library into a new position to initiate and lead work towards research universities' consortium. The development work of RDM services has tremendously raised the library's value as a partner rather than just a service provider in the eyes of researchers.


Author(s):  
Chidi Onuoha Kalu ◽  
Esther Ihechiluru Chidi-Kalu ◽  
Titilola Abigail Mafe

Academic libraries need to store, preserve, and manage scholars' intellectual output, hence the importance of research data management in academic libraries. This chapter focuses on research data management in academic libraries, and it aims at examining the concept of research data, which is referred to as the evidence used to inform or support research conclusions, while data management, on the other hand involves planning for and creating data, organizing, structuring, and documenting data, backing up and storing data, and preparing data for analysis to share with others or to preserve for the long-term.


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