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How to make your research reproducible: Data Best Practices

This guide presents best practices in documenting scientific research process to make the research reproducible.

Defining Data

Adopted from http://data-archive.ac.uk/create-manage/life-cycle

Data – files that were used or produced during the scientific research process. These files can be: 

  • Raw data
  • Different versions of processed data 

 

Good Practices to Manage Your Data

Documenting and managing data is important for reproducibility. There are different stages for managing research data. This guide focuses on general tips for well-documenting data and preparing the data to be shared and preserved. Here is how to well-document your data:

  • Include a README file in the directory that contains your Data. Check out steps of managing your project to learn about the directory structure.
  • Write a data management plan, which has become a requirement by funding agencies
  • Provide a detailed description of the data, data source(s), and how it will be used.
  • Provide a description to the process of capturing the data.
  • Describe all the steps of data preprocessing.
  • Provide a description and information about each new version of the data.
  • Provide details about the software/code that is used for preprocessing the data.
  • Adapt metadata standards for describing the data.

Naming files should be descriptive and consistent! 

Data Management Tools

There are many tools that allow researchers to manage their data. Data Management Tools and Services:

  1. Data management planning - DMPTool
  2. Publishing your data - DASH
  3. Sharing your data - Figshare
  4. Making your data citable - EZID
  5. Storing and Versioning your data- Box and Drive
  6. Backing up your data - Merritt repository

For more services and consultation about research data management, visit Berkeley's Research Data Management site.

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