Introduction to Data Management
Introduction to Data Management
Equips learners with an understanding of the different types of data management. Provides learners with the tools and knowledge to manage data effectively, covering the strategies for organizing research data. Supports learners in sharing their data securely and effectively.
This course will help learners to:
Recognize different types of research data, describe the importance of documenting their research and evaluate why and when to use metadata
Identify the benefits of data management and the sources of support, applying the best practices for successful data management
Determine responsibilities for data management in a research team and share data applying the FAIR principles
Formulate a data management plan and engage with data management planning tools, support and guidance
Employ the options available to them to safely store their data and recognize the importance of data backups
Describe what is meant by data integrity, and explain its importance
Anonymize, encrypt, and destroy sensitive data when required for ethical reasons and describe what is meant by data integrity
Identify the perks of data sharing, both for personal growth and for advancing ideas and knowledge and protect their data once published and shared, by complying with data protection legislation
Recognize the difference between copyright, licence and open access and how to control restrictions on their data
Language: English
Time to complete: 4 hours
Level: Beginner
Instructor: Dr. Alessandra Vigilante
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Before we leap into defining what we mean by data management, it’s important to establish what it is we will be managing, by defining different types of research data. This module will also walk you through the key steps of the data life cycle, with an emphasis on the use of different data types and data documentation, so that you understand how everything fits together.
This module will give an overview of the wider advantages of good data management and the importance of creating a data management plan. It will also explore real life examples which highlight the problems that can arise from poor data management, and the application of the FAIR principles.
This module will show you some common data management planning tools that will allow you to start your project with a detailed plan that takes into consideration important issues like storage, backups and ethics. It will be discussed the importance of being organized when handling data and the relevance of data integrity as a foundation of good science.
This module will look at the different strategies you may use to back up your data safely and efficiently, and evaluate where the best place is to store your data, and how to do so ethically. It will also be discussed how to appropriately protect your data and what it means to preserve data integrity.
This module will explore the value of sharing your data from an institutional, personal and legal perspective. It will share some insights into the benefits of open access data, and provide guidance and tips on sharing your data safely.
This course is aimed at all social science students or digital humanities students dealing with volumes of data, primarily working at postgraduate level.
Equips researchers with the skills and knowledge they need to form and articulate a clear and concise research question that’s relevant, interesting and fundamentally researchable.
Gives an understanding of the elements and purpose a research proposal, strategies to avoid pitfalls when preparing your proposal and provides a step by step plan to craft a winning proposal.
This course guides learners through the planning and development of an academic project. It supports the early preparation of the project and gives direction and advice during every stage to finalise the academic project.
Practical, hands-on course that guides you through planning and developing research interviews, from selecting a suitable interview approach to preparing participants.
Gain an understanding of the emerging field of social data science as a big data-driven approach to social science research.
Guides you through the entire process of preparing a literature review, from selecting and analyzing existing literature to structuring and writing your review.
Gives an overview of types of data and ways to find and generate them online to use for research.
Equips learners with the confidence, skills and communication strategies to present their research in an impactful and meaningful way.
Equips learners with an understanding of the different types of data management, providing tools and knowledge to manage data effectively and ethically, covering the strategies for organizing research data.
Develops skills to understand and evaluate qualitative data, with the appropriate approach to coding and techniques to categorize and pull themes from data at every stage of analysis.
Provides a clear understanding of the most popular online search strategies. It will help learners to decide which is the best fit for them, as well as giving lots of practical examples for carrying out a search using the most common approaches and tools.
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 Vigilante’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 and other research institutes.