Topic outline

  • Introduction to Data Tree

  • Introduction

    • The purpose of this course is to provide online training for environmental science PhD students and early career researchers in data management and in engaging with businesses, policy and the wider public.

      The course has been developed with NERC funding in order to help research students and early career researchers learn how to manage their data effectively with a view to their long-term preservation and use, and to understand how their data can provide a basis and means for engagement with the beneficiaries of their research.

      The course will be of benefit to any researcher in the early stages of their career wishing to learn about data management and engagement with the end-users of research. Many of the general principles of data management are widely applicable across research domains, but the details of the course and specific examples are drawn from the broad spectrum of environmental sciences.

      The course is delivered as eight modules, organised in three themes:

      • Data management: (modules 1-3)

      • Data variability: advanced processing and analysis (4-5)

      • End-users: engaging with business, policy, media and the public (6-8).

      The course follows a logical progression from first principles and basics to more advanced skills and practices. But its modular design allows you to select modules and topics of interest or relevance. While all modules are relevant to all researchers, some information will necessarily be more relevant at different stages on the research pathway. For example, the modules dealing with end-user engagement may be of more immediate relevance to late-stage PhD students and early career researchers.

  • Why should you take this course?

    • This course will give you a grounding in knowledge and skills that are an essential part of the modern researcher’s skills and knowledge.

      Research data are the foundation on which research is built. Effective data management is fundamental to the integrity, quality and reliability of your research. Research without good data management is research built on sand.

      Research data are also part of your intellectual capital and can have enduring value. Many career researchers use and benefit from the research data they have collected and generated over many years. And many other potential users of your data, such as other researchers, policy-makers, and businesses, will only be able to benefit from them if the data are preserved, well-curated, and made accessible. By making use of your data, others also return benefits to you, in terms of credit and reputation, and opportunities for further research.

      If you invest early and wisely in making your data fit for long-term use, you have a greater chance of realising a long-term return on the time and effort you put in.

      Lastly, research data are also a public good. If you are a researcher working in a publicly-funded university or research organisation, then any data you collect or generate will have benefited from public funding. You therefore have an obligation to manage these data accessible to and usable by others in the public interest.


  • Contents

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