TUTORIAL

This tutorial provides a tour of five main topics:

• data life cycle
• data management planning
• finding dat sets if your team itself won't be collecting or producing data
• data citation
• "open data" and reproducibility of research.

The first set of boxes below this box link out to resources related to the topics above.

OTHER RESOURCES ON THIS PAGE

• There  are lots of other boxes that relate to various aspects of data management. You may have covered many of these topics in other workshops, but you may find some items that help summarize or further elucidate things that you learned.
• See File Storage Locations for links that direct you to charts listing the various computer file storage systems of that type available to Lehigh users. Further details regarding the use and features of most systems are linked from their names on the charts.

NEED HELP?

• A subject librarian can help you identify relevant data sets for your summer work. Also, two sections of this library guide, about background information and literature searching, provide information you find those ways may help you identify data sets.
• For technical assistance with computing or software, please put in a help desk ticket.

Understanding the "data life cycle" helps you think systematically about data issues relevant to your research.

Some resources from UC San Diego:

•  "Research Lifecycle Guide"  Princeton Research Data Service
• Life Cycle Models and Principles Purdue University Libraries

• Data Management Best Practices The Library UC San Diego  

How to Find Data & Statistics: Finding Data   Michigan State University

There has been a movement to support "open data" that parallels efforts to make journal articles "open access".

Making your data publicly accessible is a service to other researchers. Doing so can help others replicate your results, or enhance your research impact, or give your research greater credibility.

For discussion of the "open data" concept, see:

• https://f1000research.com/articles/5-632/v3
• https://sparcopen.org/open-data/

You may want to mention relevant open data repositories if you are submitting a data management plan for a grant application.

Here are some articles that can get you started on exploring this toic:​

• Opinion: Is science really facing a reproducibility crisis, and do we need it to?

• Challenges in irreproducible research

• Replication failures in psychology not due to differences in study populations -- Half of 28 attempted replications failed even under near-ideal conditions.

• A solution to psychology’s reproducibility problem just failed its first test

Preregistration challenge from Center for Open Science
"Preregistration adds credibility to results by documenting in advance what will be tested. If you have a project that is entering the data collection phase, preregister now.

Why Preregister?

    Makes your science better by increasing the credibility of your results
    Allows you to stake your claim to your ideas earlier
    It’s easy and you can win a $1,000 prize for publishing the results of your preregistered research."

Open Science Framework

"OSF is a free, secure web application for project management, collaboration, registration, and archiving. Stop losing files, improve collaboration, and integrate OSF projects with the tools you use (e.g., Dropbox, GitHub, Figshare, Dataverse)."

Resources for analyzing your data:

• Running Jobs on Research Computing Resources provides information about how to use Lehigh's computer resources to run analyses of your data.
• Lehigh Software provides a list of softwares that can be downloaded from Lehigh, including ones that enable data analysis.
• See also "Citrix"/LUApps.

For assistance in identifying or using software useful for analyzing your data, contact the help desk .