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Organizing & Documenting Data

Best Practices in Organizing and Documenting Your Data

ReadMe Files

Download the Boise State University Study-Level Documentation README.TXT Template

What is study-level documentation?

  • “Study-level documentation for a data collection or dataset provides high-level information on the research context and design, the data collection methods used, any data preparations and manipulations and summaries of findings based on the data.” – Managing and Sharing Research Data: A Guide to Good Practice (Corti, et al., 2014)

Why is study-level documentation valuable?

  • Study-level documentation serves as a sort of roadmap. It provides a general overview of your research project and resulting data. For anyone wishing to review or use your data, which may include yourself if it’s been awhile since you worked with your files, this sort of orienting information is critical to understanding and using your research. What seems obvious when creating and working with your data, may quickly be forgotten or become indecipherable as your files proliferate over the life of the study.
  • Additionally, including information about file formats, specific software or tools used, and descriptions of the methodology used are essential for public sharing and long-term accessibility of your data. Since it’s impossible to know how computer systems will change over time, giving future researchers a starting place will help them open and retrieve the information contained in your files.

What does study-level documentation typically include?

  • Good study-level documentation typically includes:
    • General overview information: title, creator, summary, date
    • Content description: names of specific files, file formats, and software used
    • Data attributes: specific information that will help someone understand the content of the data and how it was collected or generated
    • Identifier and rights information: related DOIs, funder statements, rights statements.

Why a “README.TXT” file?

  • Accessibility! A .txt file may be an oldie, but it definitely still a goodie. Typically displayed in Notepad (a default program in the Microsoft Windows Operating System), these simple files can be opened and viewed by most document readers. Since these files do not include any special formatting or display information, the content can be accessed by a variety of systems and software without difficulty. When considering long-term accessibility, .txt files are one of the most effective ways to keep basic information about your study and research data still usable. For example, if the software you used to create a data set is discontinued and a future researcher is unable to open your files or even figure out what program you used, the information contained in your readme.txt file should give them the basic information they need to find a solution and get access to your data.

What other type of documentation should I consider creating for my research?

  • In addition to study-level documentation, researchers are strongly encouraged to create data-level documentation. Documentation at this level becomes more specific and may record details such as names and meanings of specific variables, codes used, a complete listing of files, and structure information for elements contained in files, such as databases.
    • Data-level documentation may be contained within the data files or be an external file, such as a data dictionary. Although data-level documentation may be created in an ad hoc manner, specific to the needs of the researcher or study, many disciplines are adopting more formal data documentation systems, known as metadata schema. For help finding and using a specific metadata schema, please contact the Library at

What is the Boise State University Study-Level Documentation ReadMe.txt Template and how do I use it?

  • The Boise State University Study-Level Documentation README.TXT Template is a tool created by Albertsons Library and Research Computing to help researchers document, manage, and prepare their data for public sharing. The sections included in the file are aligned with the DataCite and ScholarWorks metadata fields and will help you prepare information typically required when publishing or depositing your data in a specific repository.
  • Also, it can be referenced in your Data Management Plan when describing the data and metadata standards you will use. If you decide to do this, here is suggested text for your plan:
    • Study-level documentation, created using the Boise State University Study-Level Documentation README.TXT Template, will include at a minimum: description of the data, the structure of data files, and information on confidentiality, access policies, or other conditions of use, and data collection methods used. When appropriate, documentation will also include quality assurance procedures carried out, changes to data collection processes made over time, and related publications or presentations.

How do I use the template?

  • We recommend you start using the template at the beginning of your research project and periodically update it as your work progresses.
  • When you start using the template file, store it, if possible, in the same folder or server area as the related research files you describe in your README.TXT file. This will make it easier to find and will be readily available to any team members working with you.
  • As you fill it in, make certain to remove the instruction text included in brackets [ ].

What if I have questions or need help filling out the template?

Reference: Corti, L., Eynden, V., Bishop, L., & Woollard, M. (2014). Managing and sharing research data: A guide to good practice. [Library Call #: H61.8 .M36 2014]

Metadata Standards

  • Metadata can be thought of as a way of reporting on your data and is beneficial in helping others find and use your data.
  • If you are looking for a possible metadata schema to use with your own project, consider this list from the Digital Curation Centre in the United Kingdom: List of Metadata Standards or this list from the Research Data Alliance: Metadata Directory