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"Research data management"
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Principles of data management and presentation
\"The world is saturated with data. We are regularly presented with data in words, tables, and graphics. Students from many academic fields are now expected to be educated about data in one form or another. Yet the typical sequence of courses--introductory statistics and research methods--does not provide sufficient information about data, learning to work with data sets, or how to present data to various audiences. This book is designed for these purposes. It discusses how data are used in research projects, where to get data, how to manage them with software, and how to present them so that one's message comes through clearly. With few expectations beyond some familiarity with basic statistics and research methods, this book provides a comprehensive set of principles for understanding and using data as part of a research project\"-- Provided by publisher.
Book
Reusing Data Technical and Ethical Challenges
Research centres, universities and public organisations create datasets that can be reused in research. Reusing data makes it possible to reproduce studies, generate new research questions and new knowledge, but it also gives rise to technical and ethical challenges. Part of these issues are repositories interoperability to accomplish FAIR principles or issues related to data privacy or anonymity. At the same time, funding institutions require that data management plans be submitted for grants, and research tends to be increasingly interdisciplinary. Interdisciplinarity may entail barriers for researchers to reuse data, such as a lack of skills to manipulate data, given that each discipline generates different types of data in different technical formats, often non-standardized. Additionally, the use of standards to validate data reuse and better metadata to find appropriate datasets seem necessary. This paper offers a review of the literature that addresses data reuse in terms of technical, ethical-related issues.
Journal Article
Exploration and Analysis of University Scientific Research Data Management Strategies under Big Data Environment
From the perspective of the current big data environment, briefly describe the urgency of university scientific research data management, and use this as a basis to discuss the university scientific research data management strategy under the big data environment, and propose to conduct sufficient research on scientific research data management and pay attention to scientific research data Strategies such as dynamic management, strengthening the storage and security management of scientific research data, and enhancing the value of scientific research data results through publication and citation.
Journal Article
A systematic literature review on research data management practices and services
Purpose>Research data management (RDM) has been called a “ground-breaking” area for research libraries and it is among the top future trends for academic libraries. Hence, this study aims to systematically review RDM practices and services primarily focusing on the challenges, services and skills along with motivational factors associated with it.Design/methodology/approach>A systematic literature review method was used focusing on literature produced between 2016–2020 to understand the latest trends. An extensive research strategy was framed and 15,206 results appeared. Finally, 19 studies have fulfilled the criteria to be included in the study following preferred reporting items for systematic reviews and meta-analysis.Findings>RDM is gradually gaining importance among researchers and academic libraries; however, it is still poorly practiced by researchers and academic libraries. Albeit, it is better observed in developed countries over developing countries, however, there are lots of challenges associated with RDM practices by researchers and services by libraries. These challenges demand certain sets of skills to be developed for better practices and services. An active collaboration is required among stakeholders and university services departments to figure out the challenges and issues.Research limitations/implications>The implications of policy and practical point-of-view present how research data can be better managed in the future by researchers and library professionals. The expected/desired role of key stockholders in this regard is also highlighted.Originality/value>RDM is an important and emerging area. Researchers and Library and Information Science professionals are not comprehensively managing research data as it involves complex cooperation among various stakeholders. A combination of measures is required to better manage research data that would ultimately move forward for open access publishing.
Journal Article
Managing and sharing research data : a guide to good practice
Written by experts from the UK Data Archive with over thirty years of experience in working with and teaching people to work with data, this book is the globally-reaching guide for any postgraduate student or researcher looking to build their data management skills.
Book
Data information literacy
The book lays out the history of diversity in the veterinary profession, in the context of historical changes and actions within US society. An overview of selected strategies from dental, pharmacy, and (human) medical schools is then offered. The impact of social constructs on career interest development is explored using the examples of race, gender, sexual orientation, and gender identity. Practical strategies for attracting preschool through undergraduate students to careers in the veterinary profession are presented, as well as metrics and tools to assess the impact of diversity and inclusiveness strategies. A systems approach to diversity and inclusiveness in the veterinary profession is called for in a manner that frames barriers as opportunities for improvement and progress. There is much that needs to happen to achieve professional inclusiveness and cultural competency, but the path to achieving this is clear. System-wide commitment, planning, execution, and continuous assessment will position the profession to better suit the population of the nation and the world that will be served. This book is a call to action for consistent championship and cohesive approaches, and it provides a road map to building a sustainably inclusive future.
eBook
Cybersecurity investments : decision support under economic aspects
This book offers readers essential orientation on cybersecurity safeguards, and first and foremost helps them find the right balance between financial expenditures and risk mitigation. This is achieved by pursuing a multi-disciplinary approach that combines well-founded methods from economics and the computer sciences. Established decision making techniques are embedded into a walk-through for the complete lifecycle of cybersecurity investments. Insights into the economic aspect of the costs and benefits of cybersecurity are supplemented by established and innovative economic indicators. Readers will find practical tools and techniques to support reasonable decision making in cybersecurity investments. Further, they will be equipped to encourage a common understanding using economic aspects, and to provide cost transparency for the senior management.
Book
Enhance Data Security Governance Capability: Interpretation of Data Security Law of the People's Republic of China (Draft)
[Purpose/Significance] Data security is an important cornerstone of national security. The promulgation of the data security law of the People's Republic of China (Draft) points out the development direction for the establishment and improvement of data security governance system in China. [Methods/Process] Through text analysis, the paper analyzes the content of the data security law of the People's Republic of China, mainly to interpret the legislative spirit and principles, content and characteristics of the law and its deficiencies. [Results/Conclusions] The draft not only pays attention to the confidentiality of data itself, but also takes into account the availability of data. It provides legal protection for safeguarding national data sovereignty and legitimate rights and interests of data stakeholders. In addition, relevant supporting measures should be formulated as soon as possible.
Journal Article