Development strategies as catalysts for provision of the RDM services in the South African higher education institutions

A strategy in this paper was viewed as a plan of action for achieving the mission and vision of an organisation. This paper presents preliminary findings of the larger study which aimed to determine the strategies for research data management (RDM) at selected universities in KwaZulu-Natal. The current study used the community capability maturity model framework (CCMF) and the digital curation centre (DCC) lifecycle model as theoretical support to determine the strategies for RDM service provision with specific reference to the University of Zululand. The interpretive paradigm, following the qualitative research approach through a single case study, was used. Primary data was gathered through online interviews using Zoom and Teams with Librarians, Technicians, HODs, and DVC Research due to the Covid-19 pandemic and availability of technologies. The findings of the study revealed the University of Zululand does not have an RDM policy;however, research activities are practiced. The University lacks the infrastructure and investment to support RDM services and activities. The study is significant for providing the background for developing RDM in the public university through RDM strategy and policy. The findings also sought to inform the university's RDM agenda.

Applying the FAIR principles to data in a hospital: challenges and opportunities in a pandemic.

BACKGROUND: The COVID-19 pandemic has challenged healthcare systems and research worldwide. Data is collected all over the world and needs to be integrated and made available to other researchers quickly. However, the various heterogeneous information systems that are used in hospitals can result in fragmentation of health data over multiple data 'silos' that are not interoperable for analysis. Consequently, clinical observations in hospitalised patients are not prepared to be reused efficiently and timely. There is a need to adapt the research data management in hospitals to make COVID-19 observational patient data machine actionable, i.e. more Findable, Accessible, Interoperable and Reusable (FAIR) for humans and machines. We therefore applied the FAIR principles in the hospital to make patient data more FAIR. RESULTS: In this paper, we present our FAIR approach to transform COVID-19 observational patient data collected in the hospital into machine actionable digital objects to answer medical doctors' research questions. With this objective, we conducted a coordinated FAIRification among stakeholders based on ontological models for data and metadata, and a FAIR based architecture that complements the existing data management. We applied FAIR Data Points for metadata exposure, turning investigational parameters into a FAIR dataset. We demonstrated that this dataset is machine actionable by means of three different computational activities: federated query of patient data along open existing knowledge sources across the world through the Semantic Web, implementing Web APIs for data query interoperability, and building applications on top of these FAIR patient data for FAIR data analytics in the hospital. CONCLUSIONS: Our work demonstrates that a FAIR research data management plan based on ontological models for data and metadata, open Science, Semantic Web technologies, and FAIR Data Points is providing data infrastructure in the hospital for machine actionable FAIR Digital Objects. This FAIR data is prepared to be reused for federated analysis, linkable to other FAIR data such as Linked Open Data, and reusable to develop software applications on top of them for hypothesis generation and knowledge discovery.

To protect and to serve: developing a road map for research data management services

Research Data Management (RDM) has become a major issue for universities over the last decade. This case study outlines the review of RDM services carried out at the University of Oxford in partnership with external consultants between November 2019 and November 2020. It aims to describe and discuss the processes in undertaking a university-wide review of services supporting RDM and developing a future road map for them, with a strong emphasis on the design processes, methodological approaches and infographics used. The future road map developed is a live document, which the consulting team handed over to the University at the end of the consultation process. It provides a suggested RDM action plan for the University that will continue to evolve and be iterated in the light of additional internal costings, available resources and reprioritization in the budget cycle for each academic year. It is hoped that the contents of this case study will be useful to other research-intensive universities with an interest in developing and planning RDM services to support their researchers.

Book Alert

The book focuses on the immediate practicalities of service provision under COVID-19;considers longer-term strategic responses to emerging challenges;identifies key concerns and problems for librarians and library leaders;analyses approaches to COVID-19 planning;presents and examines exemplars of best practice from around the world and offers practical models and a useful framework for the future. The book provides guidance on organizing, storing, preserving and sharing research data using RDM;contextualizes RDM within the global shift to data-intensive research;helps researchers and information professionals understand and optimize data-intensive ways of working;considers RDM in relation to varying needs of researchers across the sciences and humanities;and presents key issues surrounding RDM, including data literacy, citations, metadata and data repositories. Boosting the knowledge economy: key contributions from information services in educational, cultural, and corporate environments has a particular interest in learning services, exploring principles and strategies for their implementation - from marketing strategy to analytics - and covers implications for the LIS profession. Presents an overview and analysis of cutting-edge practices in information services, with a particular focus on learning services and their particular contribution to LAMs (libraries, archives, and museums) brand awareness and to social capital building.