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What is Data Management

Handbook of Research on Computational Science and Engineering: Theory and Practice
All disciplines related to managing data as a valuable resource, here in particular we refer to Scientific Data Management, the management of storage, access, usage, lifecycle, content and meaning for scientific data
Published in Chapter:
Integrating Data Management and Collaborative Sharing with Computational Science Research Processes
Kerstin Kleese van Dam (Pacific Northwest National Laboratory, USA), Mark James (University of California San Diego, USA), and Andrew M. Walker (University of Bristol, UK)
DOI: 10.4018/978-1-61350-116-0.ch021
Abstract
This chapter describes the key principles and components of a good data management system, provides real world examples of how these can be successfully integrated with scientific research processes and enable successful data sharing, provides an outlook on future developments, and discusses lessons learned. We conclude with a short section on how to get started for those whose interest has been piqued.
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Essential Characteristics of Health Information Systems
The practice of collecting, storing, protecting and using data effectively and efficiently.
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Making Data Right: Embedding Ethics and Data Management in Data Science Instruction
An ongoing process that involves decisions about collecting, organizing, preserving, and sharing data to make data findable and accessible throughout the research lifecycle.
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Monitoring Environmental Performance of Agricultural Supply Chains Using Internet of Things
Data Management involves a comprehensive set of activities, methodologies, and technology solutions employed to acquire, store, arrange, examine, and guarantee the integrity and usefulness of data throughout its entire lifespan.
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Evolution of the Legal Status of Oceanographic Data Management in Europe
Practices and projects to acquire, control, protect, disseminate, and increase the value of data.
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Business Applications of Big Data: Considerations for Not-for-Profits
Development and execution of policies and procedures to manage the information of a company in an effective manner.
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Towards Ethical Neuromarketing 2.0 Based on Artificial Intelligence
The planning, development, implementation, and administration of data systems in order to collect, store, secure, use and archive data.
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Executive Information Systems
A broad term that comprises all the disciplines related to the management of data as a valuable resource.
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Data and Data Management
The set of approaches used to process, store, and organize the data used in the study.
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Collective Case Study: Making Qualitative Data More Impactful
The systematic organization of data into sets to assist meaning-making and prepare for analysis.
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Social Media Bullying in the Workplace: Impacts on Motivation, Productivity, and Workplace Culture
The process of collecting and storing information needed for personal, educational, business use.
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Big Data Adoption: A Comparative Study of the Indian Manufacturing and Services Sectors
Process of ensuring accuracy, availability, accessibility, and quality of large stores of data by allocating people, policies, and technologies.
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Key Challenges to Data Management in the Fourth Industrial Revolution
Is a managerial method that involves the acquisition, storing, validating, protecting, and handling the necessary information to create accessibility, reliability, and availability of the data for its users.
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New Data-Related Roles for Librarians: Using Bibliometric Analysis and Visualization to Increase Visibility of Research Impact
The practice of describing and organizing research data to increase understanding and enable further analysis of the data. Well-managed data enables data to be discovered, accessed, and reused to replicate results or repurpose for new research.
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Cloud Database Systems: NoSQL, NewSQL, and Hybrid
This comprises all the regulations associated with managing data as a valuable resource.
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Redefining the 21st Century Labor Paradigm: Role of Contingent Workforce in the Indian Economy
Design and development of systems, policies, and procedures for effectively managing an organization’s information lifecycle needs.
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