Topic outline

  • Data Management: Context
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  • Topic 1: Key Concepts

    This topic is essentially a reference guide to terminology used throughout the course. We explain what we mean when we use terms like "research data" and "metadata". Other parts of the course may reference this topic. 

  • Topic 2: The Research Data Lifecycle

    This topic discusses the research data lifecyle, a framework for discussing data issues at different points throughout a typical research project. We reference this lifecycle in other parts of the course, particularly in the more practical modules where it is important to know how methods and practices fit into the wider scope of your research. 

  • Topic 3: Sharing Data & The Research Community

    An important thing to remember in your work is that you are not alone! The value and impact of your work (hopefully) goes far beyond just you and your team, and you are influenced by others' work in many ways. 

    This topic explores the growing understanding of these relationships amongst the wider research community, and discusses issues like sharing data, making data FAIR and understanding the key beneficiaries in your work. 

  • Topic 4: Reproducibility of research data and outputs

    Reproducibility is an important trait of good research. When you come across existing research, knowing that it has been successfully reproduced gives a good indication that the conclusions drawn from the research are valid and reliable. Similarly, others may want to verify your research by reproducing your results. 

    This topic explores what this means in practice, and how you as a researcher can increase the chance that others will be able to successfully reproduce your work.

  • Topic 5: The Policy Environment

    At some point, you will have to consider a whole host of different policies regarding data management and sharing. Your funder(s) will have one; your institution(s) will probably have one; publishers and journals you work with will have one. 

    This topic will help you navigate and understand these policies - why they exist, where they exist and how they affect your research work. 

  • Topic 6: Data Ethics

    You have a responsibility to ensure your research activities are ethically sound. This is particularly relevant when you have human subjects, or are handling personal or private data in your work, but it's important for everyone to at least consider the ethical implications of their research. 

    Fortunately, there are places you can get help. This short topic discusses some of the key ethical issues to consider, and the guidelines that exist to support you in making informed decisions.

    The last resource in this topic is a set of links to videos, texts and wider reading on this topic. Many of the links relate directly to ethics within the environmental sciences - we recommend you download this list and explore some of the links that look interesting or relevant to you.

  • Topic 7: Coding for Data Management

    This bonus topic highlights the importance of programming skills for researchers. It signposts to resources for users who require training to develop these skills, and provides advice and information on how the concepts mentioned in Module 1 apply to coding and software development.

    This is an optional topic, and is not required to attain the end of module certificate. However, if you write any sort of code as part of your work, we highly recommend hearing what Jane Lewis has to say in these videos!