Data Management & Retention Best Practices: Data Courses, Guides, and Tutorials

To find data, first define your topic.  What are you interested in learning about?

Then ask, What information do I need in order to know more about the topic.  Be specific, but flexible.

1) Who or what do you want to study?

• People
• Communities and Organizations
• Things

2) What time period are you interested in?

• Today
• The last decade
• A historic period

Each time period will have different sources of the data.  Sometimes the more recent (but not current) data is the easiest to obtain.

3) What type of time period?

• A single point in time, a snapshot
• A period of time with data averaged together
• A period of time with changing values

4) Where is the place of your interest?

• Geographic location or area
  • Political boundary (cities, states, countries)
  • Census boundary (U.S. census blocks, metropolitan statistical areas)
  • Natural boundary (continents, planets, oceans)

As you begin to explore the data, you can develop and refine a research question.

This question should be something interesting that isn't directly answered by the data.  But, it needs to be able to be answered by looking at data.

Sometimes the data to support a question is not available.  Be prepared to modify your question to something that can be answered by the available data. 

A canvas-based set of modules for use as an add-on to data-oriented courses. Instructors can try out the modules by contacting Roger Justus (justusra@miamioh.edu), Ginny Boehme (boehmemv@miamioh.edu), or Kristen Adams (adamsk3@miamioh.edu).

We have some preview versions of the classes that you can use to see if they may be right for you or your class.  

Planning for Data Reuse Checklist (Mozilla Science Lab)

Social Science and Humanities Data

• Guide to Social Science Data Preparation and Archiving (ICPSR)
• Qualitative Data Repository (Syracuse) guidance for managing and processing qualitative research data.
  • Managing Qualitative Social Science Data: An Interactive Online Course (QDR & SSRC)
• Sharing Study Data: A Guide for Education Researchers (US Department of Education)
• UK Data Services Managing & Sharing Data
  • ​Managing & Sharing Research Data: A Guide to Good Practice (Fenwick Library, H61.8 .C67 2014)

Scientific Data

• Data Management Short Course for Scientists (ESIP) 
• DataOne data management education modules and best practices.
• Oak Ridge National Laboratory: Data Provider Information

Digital Humanities and Scholarship are another powerful way to use data and technology to tell a story in a new and different way.  Here at Miami University, we have several excellent research guides to help you if you want more information on these areas.

The Infobase Learning Cloud (formerly known as Hoonuit) has tutorials for a number of data products.  Other sites with tutorials can be found below:

• Research Data Management Librarian Academy (RDMLA) - is geared toward librarians but useful for anyone dealing with research data. A Canvas-based set of modules that culminates in an RDMLA certificate.
• Data One Data Management Skillbuilding Hub - Many data management topics are covered in this compendium of guides and courses.
• Data Carpentry Lessons - A growing number of discipline-specific tutorials for managing research data. The Carpentries' in-person classes are popular for good reason; these online guides are the next best thing.
• University of Illinois Library Introduction to Data Management - a concise but thorough introduction to best practices. Aimed at undergraduates.
• Berkeley Advanced Media Institute Guide to Data Cleaning - tutorial for cleaning data with spreadsheet tools.
• Data Analysis and Visualization Videos - A series of instructional videos on common visualization techniques.