One definition of research data is: "the recorded factual material commonly accepted in the scientific community as necessary to validate research findings."
(OMB Circular 110).
Note that properly managing data (and records) does not necessarily equate to sharing or publishing that data.
Image and Biomedical Data Lifecycle created by LMA Research Data Management Working Group at Harvard Medical School licensed under a CC BY-NC 4.0 DEED License.
Research Data Management is a continuum of practices. It continues throughout the course of a research project. You will likely jump around and move between phases in the lifecycle, but you should always start at the Plan & Design phase. In this phase you will plan processes from onboarding, to project closure and data resources.
During the Plan & Design phase, you will ask:
During the Plan & Design phase, you will need to know:
Use checklists to help plan and design your work:
Before launching a research project, design a model for capturing, storing, and organizing your data.
During the Collect & Create phase, you will ask:
Consider project
Design how you will store your data:
Processing and analyzing data should be collaborative and documented.
During the Analyze & Collaborate phase, you will ask:
Data analysis is a process of inspecting, cleansing, transforming and modeling data with the goal of discovering useful information, informing conclusions and supporting decision-making.
The choices you make while analyzing your data can also contribute to effectively managing your research data:
Document your steps: Consider the software you use for analysis, and whether those applications automatically generate information about your data files and process steps. Keeping track of your steps can save you time when you want to recreate your work, or share your methodology with others! Use Electronic Lab Notebooks, Collaborative Tools & Software, and Image Management platforms.
Keep your data safe: Describe your data as you capture it, organize your files, and make smart choices about where you store your data. Since some software programs produce files that are proprietary and can only be opened in their applications, consider saving data in formats that can be opened by different software programs. Ensure you are working with Analysis Ready Datasets.
Identify essential research records and evaluate for retention.
During the Evaluate & Archive phase, you will ask:
A small percentage of data and related records might be identified for permanent storage as a part of the historical record of a discipline or institution, or as intellectual property.
Records eligible for permanent retention maybe those that:
Follow required retention and preservation requirements as established by your institution or funding agency.
The Data Curation Network has developed extensive guidance on working with and keeping research data:
In the last decade, it has become increasingly common for researchers to make their data available to others when they complete a study. This is usually referred to as data sharing or data publishing. Data sharing is growing mostly due to recent data policies from journals and funders.
During the Share & Disseminate phase, you will ask:
Find a repository for sharing and publishing:
Data publishing repositories should follow FAIR principles https://www.go-fair.org/fair-principles/
Promote sharing and use of your data by making it available under appropriate licenses to ensure proper use and attribution. There are many licenses available that represent the range of rights for the create and licensee of the data.
During the Access & Reuse phase, you will ask:
In general, raw data are considered facts and cannot be copyrighted. Community norms for data attribution and scholarly communication are often more successful in documenting origins of data than licensing restrictions when possible.
Data license considerations include the following:
Please send any questions to Research and Information Literacy Services Librarian, Christina Hilburger at christina.hilburger@fredonia.edu.
This guide was heavily adapted from the SUNY Office of Library and Information Services Research Data Management Guide, the LMA Research Data Management Working Group at Harvard Medical School, and the Defining Research Data page by NC State University Libraries.
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