How to Archive and Share Data

• In Event: Open Science Basics: Training for Education Researchers

Abstract

This presentation will provide a general overview of effective practices for archiving and sharing data for scholars seeking to implement that practice in their research studies.It will be designed for scholars who have limited experience with open science, but are looking to engage in more transparent research practices. The talk will begin with defining what data sharing is, and is not, as well as the benefits of data sharing. The talk will then focus on the “how-to” of sharing data, with lots of practical advice and resources on how to get started with data sharing no matter where a project is in the research pipeline.

What is data sharing?

Process of taking any type of research data and making it available for other researchers to examine or use, usually in an established data repository. If you have shared simple statistics within your own publications, you have engaged in a basic version of data sharing.

It is also important to understand what data sharing is not. Data sharing is not a data dump. Including general information about your dataset - metadata - provides critical context and lets other researchers know what is in your dataset.

Metadata information to include:
Project title
Name of principal investigator(s)
Study design
Participant info
Variable info
Codebooks

Data sharing is not an all or nothing practice. If you are not able to share participant- or variable-level data, you can still engage in data sharing practices. For instance, sharing a variance-covariance matrix is also useful for the field and can be used by others.

Shared data should be accessible via the internet, but it does not have to be totally open without limitations. In education research, there are many reasons restrictions must be placed in shared datasets.

Benefits of data sharing
Generates new ideas
Advances the field
Increases transparency of research process
Increases collaboration
Promotes equity in research
Meets funder requirements

How can I share data?
Before your study starts address informed consents
Use proper data entry procedures such as consistent variable naming and double data entry
Keep careful documentation during your study including recruitment samples and study protocols
Carefully clean data after collection
Be ready to de-identify your data
Research data repository options

Practical advice for sharing data:
Check IRB and informed consent before sharing
Consider restricting access to data or an embargo
Consider uploading a synthetic data set (data generated based on the original data).

Author

• Sara A. Hart, Florida State University
  Presenting Author