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An institution cannot exist and function properly without the presence of a library because the services provided by an academic library reflect the quality of the institution. This paper attempts to present a brief overview of the concept of library, research data, Research Data Management (RDM) and its constraints as well as the roles of academic libraries. These roles has experienced new paradigm shift, unprecedented reshaping and alterations as a result of emerging waves of information communication technology (ICT) and its accompanying sustainable and disruptive technologies. Scholars are now producing, storing and disseminating digital data in much larger volumes than the text. The continued existence and access of this data is an issue, since the data is not stored in libraries. It is therefore crucial to preserve data for future generations. This paper tries to delineate the emerging role of academic libraries in Research Data Management (RDM) in tertiary institutions. [ABSTRACT FROM AUTHOR]

Research funding organizations understand the importance of infrastructure and services to organize and preserve research data. Academic research libraries have been identified as locations in which to base these research data management services. Research data management services include data management planning, digital curation (selection, preservation, maintenance, and archiving), and metadata creation and conversion. However, some libraries are beginning to provide structure for research data management services. These services are starting to record some degree of success as local data policies are being formulated. The aim of this paper, therefore, is to discuss the importance of research data management in the academic libraries in Nigeria. The article summarized the research data management life cycle to include: data creation; data collection and description, data storage; data archiving and preservation; data access; data discovery and analysis, and data reuse and transformation. The paper further identified research data management tools and applications, which include DMPonline, Data Asset framework, Collaborative Assessment of Research Data Infrastructure and Objectives (CARDIO), and Curation cost exchange. Specifically, the paper examines some skills requirements for research data management in academic libraries. Some of the challenges facing effective research data management services identified by this paper include technology obsolescence, technology fragility; Lack of guidelines on good practice; Inadequate financial and human resources to manage data well, and Lack of evidence about best infrastructures. [ABSTRACT FROM AUTHOR]

This paper presents the findings of a study on readiness of the University of Zambia in participating in research data management services in the COVID-19 and post Covid eras. The study adopted a qualitative research method and employed purposive sampling. In-depth interviews were conducted with key informants in the University. Findings reveal a lack of awareness and knowledge about research data management among senior officers and inadequate skills among library staff. On a positive note, the University has a robust information and communication technology (ICT) infrastructure supported by qualified information technology (IT) staff. It was further discovered that the University did not have a research data management policy. This paper provides a framework for the University to operationalize research data management services. The study recommends development of a research data management policy; conducting awareness campaigns; investing in skills training for library staff, and constituting research teams to deal with issues of research data management. [ABSTRACT FROM AUTHOR]

Purpose: To simplify working with and sharing research data, researchers want infrastructures that provide the highest level of accessibility, stability, and reliability. The Harvard Dataverse Project (HDP) (https://dataverse.org/) is compiling a growing list of such infrastructures. In this regard, the objective of this paper is to provide an overview through an analysis of the activities of the Dataverse website in managing research data. Design/ Methodology/ Approach: The study examines the statistics systems and other critical resources concerning upload and use the dataverse/ datasets/ files upto October 2022. This includes the creation of dataverse, category of dataverse, uploaded total datasets, file downloads trend, publication of dataverse or datasets, most approachable subject to share and browse data, the most recommended file type of research data and access level of research data. The basic resources include top metadata sources and data citation standards of dataverse project. Findings: It is noted that behaviours associated with structured study outcomes are more evident in developed countries as opposed to developing countries according to top author affiliation which is from the USA. The findings also show that research data in Medicine, Health, and Life Sciences is more uploaded and structured, whereas data in Social Sciences is more browsed and structured. Overall, the generation of dataverses, datasets, files, their downloads, and publication dataset is on the rise. The maximum contribution of data developers is found as Master, Daniel M. and Stager, Lawrence E whereas research project category and data and image file format are seen as highly used to organize data. On the dataverse website, good citation standards are being noticed, as well as the fact that 97 percent of data are available to reuse because contributors waive their copyright licences under CC0. Originality/ Value: This study presented an overall picture of the growing research data practices throughout the investigation on the Harvard Dataverse platform. The research proposed best practices focused on RDM operations to improve the amount of Research Data activities. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is the internetworking of physical devices which consists of an embedded system with sensors, actuators and network connectivity that enable collection and exchange of data. Each day, we are witnessing the emergence of new technologies that have the capability to embed into our environment and measure the physical, social and contextual phenomenon. The technology behind IOT is driven by various technological forces such as smart devices, wireless network, and pervasive connectivity among others. Data collection, management and accessibility are made easy with Internet of Things IOT. The Internet of Things (IoT) is aimed at formulating a complex information system with the combination of sensor data acquisition, efficient data exchange through networking, machine learning, artificial intelligence, big data, and clouds. This paper, therefore, focused on the relevance of Internet of Things (IoT) in clinical data management for health institutions. This includes the impact on how data are collected, how they were being analyzed and stored, and its impact in terms of security and privacy-related issues. [ABSTRACT FROM AUTHOR]

Objective The enormous growth in research data generated today has highlighted the value of data management (RDM) to make research FAIR (Findable, Accessible, Interconnected and Reusable). Appropriate data instructs researchers to use and reuse that data within appropriate citations and attribute it to the author. And Data citation refers to the process of presenting a reference to data in the same way as a bibliographic reference to printed resources is regularly provided by researchers. In this regard, the objective of this paper is to investigate the activities of the Datacite website in managing research data. Methodology The study approached the Datacite website, a non-profit organization that provides analysis with persistent identifiers (DOIs). The research examines the Statistics systems and other critical resources. Registrations by the Collective group and most involved repositories are included in the statistical approaches. The basic resources include top executives, OAI-PMH, DataCite Public Roadmap, DataCite Commons, DataCite/ORCID Auto-update and Service Providers. The outcomes were analysed by MS Excel. Results It is noted that there were 293 members of the registry from different countries. The USA was at the top of the 137 members according to registration, while at least one was located in India, Finland, Spain, etc. Germany was listed as the top member and most of the repository holding companies. Datafirst is the only server found in an Indian context. DataCite Commons found as a discovery tool which allows simple searches by works, individuals and organisations, while providing users with a detailed overview of the relationships between the entities in the research setting. Using the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH), the DataCite service exposes metadata stored in the DataCite Metadata Store (MDS). Datacite Auto-update unambiguously categorises researchers and provides tools to automate the link between researchers and their creative work. [ABSTRACT FROM AUTHOR]

This comprehensive review article delves into the current landscape of research data management (RDM) practices and challenges faced by academic libraries across various regions. Utilizing a wide range of studies and data collected from different countries, this article aims to provide a comprehensive overview of the state of RDM services, the role of librarians, and the advancements in technology within academic libraries. The review explores the importance of RDM in supporting open science, data sharing, and reproducibility, while also shedding light on areas that require further development and improvement. [ABSTRACT FROM AUTHOR]

The study applied an adapted Technology, Economic, Legal, Organisational, and Schedule (TELOS) model to explore the feasibility of Research Data Management (RDM) at the Zimbabwe School of Mines (ZSM). The study employed a qualitative approach. Data were collected through interviews that were held with purposively chosen professionals at ZSM in the form of the Information Technology (IT) manager, the Librarian, and three (3) Assistant Librarians. Findings show that ZSM does not currently meet the TELOS model feasibility test. ZSM lacks a robust technological system to support data creation, data collection and description, data storage, archiving and preservation, data access, data discovery and analysis, and data reuse and transformation. ZSM has not yet created a legal environment conducive for the introduction of RDM. It does not have policies and standards in place to handle issues such as intellectual property, copyright, data licensing, ethics, data protection, freedom of information, and confidentiality. While librarians at ZSM possess basic IT and computer skills they lack skills specific for RDM. The study informs the shaping of policies, practices, and strategies regarding the introduction of RDM services in Zimbabwean academic libraries. [ABSTRACT FROM AUTHOR]