Introduction to FAIR Data Management for Long-term Agriculture Experiments

Good research data management for LTE data matters because

  • LTE data is costly to produce
  • LTE data is unique and cannot be reproduced
  • LTE data takes many years to generate
  • Good RDM is necessary to ensure the continuity of data over time
  • Good RDM is necessary to ensure the accessibility of data over time
  • Good RDM is necessary to ensure the usability and interpretation of data over time

Why should we share long-term experiment data

  • Open science aims to remove barriers to accessing research outputs.
  • Open data is a key building block of Open Science.
  • There are different motivations for sharing data including.
  • LTE data is inherently valuable with relevance to multiple research areas.

FAIR Principles for long-term agricultural experiments data

  • Applying FAIR Principles make it easier to find research data.
  • Following FAIR principles makes you start to follow best practices for research data management.
  • FAIR data is not open data, but open data should be FAIR data.
  • Good research data management through adopting FAIR principles has a cost.

Metadata for long-term experiments

  • Metadata provides essential context for understanding a dataset
  • To be reusable, metadata should be consistent across datasets of the same type

Organising data for long-term experiments

  • Humans and computers can interpret data in Excel differently.
  • Be aware of common problems using Excel for managing data.
  • Excel is not a database.

Making LTE data FAIR

  • Providing a well described table makes it easier for researchers to understand what data it contains.
  • Standardising table structures and using open data formats make it easier to use the data in statistical packages.
  • Semantic annotation allows different datasets to be combined on common concepts.

databases-for-lte-data

  • Use .md files for episodes when you want static content
  • Use .Rmd files for episodes when you need to generate output
  • Run sandpaper::check_lesson() to identify any issues with your lesson
  • Run sandpaper::build_lesson() to preview your lesson locally

Publishing LTE data

  • Data repositories provide features supporting FAIR data.
  • Published datasets are immutable - the data must not be altered.
  • Published datasets are versioned.