Research Data Management and Sharing

Go to Course: https://www.coursera.org/learn/data-management

Introduction

### Course Review: Research Data Management and Sharing In today’s data-driven world, the ability to manage, share, and archive research data is of paramount importance across various academic and professional fields. The course titled **Research Data Management and Sharing**, offered on Coursera, provides an invaluable resource for researchers, data managers, and anyone interested in understanding the intricacies of handling research data. Here’s an in-depth review of the course content, structure, and my recommendations. #### Overview of the Course The **Research Data Management and Sharing** course is designed to equip learners with a comprehensive understanding of the diverse types of research data, their management needs, and best practices throughout the research data lifecycle. Upon completion, participants will have the skills to craft effective data management plans, adopt best practices in data organization, documentation, and security, and appreciate the significance of data sharing within the scientific community. #### Syllabus Breakdown The course is structured into five main modules, each addressing critical facets of research data management: 1. **Understanding Research Data** This introductory week lays the groundwork by exploring different types of research data and fundamental data management concepts like metadata and the research data lifecycle. It also delineates the roles of various stakeholders in data management, setting a solid foundation for understanding the complexities involved in handling research data. 2. **Data Management Planning** Learners will delve into Data Management Plans (DMPs), crucial for successful research projects. This module highlights the essential components of effective DMPs and discusses guidelines from various funding agencies, providing tools for crafting well-structured plans. 3. **Working with Data** Hosted by experts from EDINA and the University of Edinburgh, this week focuses on practical strategies for organizing data, including version control and file naming. Important topics such as data documentation and the significance of data citation will also be covered, ensuring that participants understand how to maintain the integrity and efficiency of their data processes. 4. **Sharing Data** This module underscores both the benefits and potential challenges of data sharing. It addresses crucial aspects like confidentiality and the implications of data ownership while providing insights into implementing access restrictions and permissions for shared data, as well as suggesting standard licensing methods. 5. **Archiving Data** The final week's content revolves around the preservation of research data. It introduces concepts like authenticity and integrity and discusses the critical roles of metadata and trustworthy repositories. By the end of this module, learners will be equipped with key archival standards and practices necessary for ensuring that data remains accessible and usable in the long term. #### Key Strengths - **Comprehensive Curriculum**: The course is thorough, covering all essential aspects of research data management, from planning to storage and sharing. - **Expert Instructors**: Contributions from renowned institutions like the University of Edinburgh and experienced data curation professionals enhance the learning experience, providing real-world insights into best practices. - **Practical Focus**: With a strong emphasis on applying concepts through actionable strategies and tools, learners can immediately implement what they learn. #### Recommendations I highly recommend the **Research Data Management and Sharing** course for anyone involved in research, including graduate students, early-career researchers, and data managers. The skills gained from this course are not only applicable in academic settings but also invaluable in industry roles that require managing large datasets. Whether you are looking to improve your data management practices, enhance your knowledge on data sharing policies, or understand the importance of archiving, this course will serve as a fundamental building block in your data management journey. In conclusion, this course stands out as an essential resource that empowers learners to navigate the complexities of research data management competently. Don't miss the opportunity to deepen your understanding and make a positive impact in the field of research!

Syllabus

Understanding Research Data

This week introduces multiple types of research data in an array of contexts as well as important data management concepts including metadata and the research data lifecycle. We will also define the concept of data management, identify the roles and responsibilities of key stakeholders, and examine various data management tasks throughout the research data lifecycle.

This week provides an overview of Data Management Plans (DMPs) including the components of good DMPs, the DMP policies of several funding agencies, and information on data management planning tools.

This week is brought to you by EDINA and the Data Library at the University of Edinburgh and is presented by Sarah Jones from the Digital Curation Centre. Sarah will introduce strategies for organizing research data including versioning and file naming conventions as well as data file formatting and transformations. She will also discuss why documenting data and data citation are important. Finally, she will present issues involved in storing, securing, and backing up research data.

This week examines the benefits and challenges of sharing research data. We will also discuss how to protect confidentiality and how data ownership can affect data sharing. Finally, we will examine different types of access restrictions that may be placed on data as well as how to enable data sharing through the application of a standard license.

During the final week of the course, we will examine the preservation needs of research data, introduce the concepts of authenticity and integrity, and identify the different types of metadata and their role in data discovery and reuse. We will also discuss the role of trustworthy repositories as well as how repositories demonstrate their trustworthiness through audit and certification. Finally, we will present key archival standards and best practices for ensuring data remains accessible and understandable for the long-term.