Topic outline

  • Course Overview

    This course equips you with an understanding of different data management practices, providing you with the tools and knowledge to manage your data effectively. It covers strategies for working with and organizing research data, and supports you in sharing your data securely, effectively, and in line with FAIR principles. 

    Learning Outcomes 

    This course will help you to: 

    1. Recognize different types of research data, describe the importance of documenting your research, and evaluate why and when to use metadata 
    2. Identify the benefits of data management and the sources of support, applying the best practices for successful data management  
    3. Determine responsibilities for data management in a research team and share data applying the FAIR principles   
    4. Formulate a data management plan and engage with data management planning tools, support, and guidance  
    5. Employ the options available to you to safely store your data, and recognize the importance of data backups  
    6. Describe what is meant by data integrity, and explain its importance  
    7. Anonymize, encrypt, and destroy sensitive data when required for ethical reasons, and describe what is meant by data integrity 
    8. Identify the perks of data sharing, both for personal growth and for advancing ideas and knowledge, and protect your data once published and shared by complying with data protection legislation 
    9. Recognize the difference between copyright, license, and open access and how to control restrictions on your data 

    • Course Author: Dr. Alessandra Vigilante

      • Dr. Alessandra Vigilante

        Dr. Alessandra Vigilante is a Senior Lecturer in Bioinformatics at the Center for Stem Cells and Regenerative Medicine with a focus on genotype-phenotype interactions and data integration. Alessandra obtained her PhD in Bioinformatics in Naples (2008-2011) before moving to the UK to join the Nicholas Luscombe group first at the EMBL-European Bioinformatics Institute as a visiting student (2011-2012) and then as a postdoctoral fellow at UCL (2012-2017). Alessandra’s group has significant expertise and experience in the analysis and integration of large scale genomic, epigenomic and transcriptomic data (i.e., single-cell RNA-seq and ATAC-seq datasets, ChIP-seq etc.), and in the implementation of novel computational methods for various bespoke analyses to gain biological insights. She is actively involved in a great network of collaborations to develop multidisciplinary approaches to research efforts, working with faculty members within King’s College and other research institutes.

        View Bio
      • Module One: Understanding the Different Types of Research Data

        This module will help you to: 

        1. Recognize different types of research data   
        2. Describe the importance of documenting your research 
        3. Evaluate why and when to use metadata   
        4. Distinguish between each step of the data life cycle 
      • Module Two: Data Management Principles and Best Practice

        This module will help you to: 

        1. Identify the benefits of data management   
        2. Determine responsibilities for data management in a research team   
        3. Identify sources of support for data management   
        4. Apply the best practices for successful data management  
        5. Share data applying the FAIR principles    
        6. Formulate a data management plan   

      • Module Three: Planning a Data Management Strategy

        This module will help you to: 

        1. Engage with data management planning tools, support, and guidance   
        2. Apply data file naming, renaming, and versioning conventions   
        3. Use electronic lab notebooks to support the collaborative research process   

      • Module Four: Storing Your Data Effectively

        This module will help you to: 

        1. Employ the options available to you to safely store your data 
        2. Recognize the importance of data backups   
        3. Describe what is meant by data integrity, and explain its importance 
        4. Anonymize, encrypt, and destroy sensitive data when required for ethical reasons 

      • Module Five: The Benefits of Sharing Data

        This module will help you to: 

        1. Identify the perks of data sharing, both for personal growth and for advancing ideas and knowledge 
        2. Protect your data once published and shared, by complying with data protection legislation   
        3. Recognize the difference between copyright, license, and open access, and how to control restrictions on your data