Data management refers to the process of decision-making and documenting of how data will be collected, structured, analyzed, stored, and shared. As a research project progresses, the ways in which data files might be structured, stored, and shared may change depending on the most appropriate strategy for that phase of the research project. Often, the plan for how data will be treated during each phase of the research project will be documented in some fashion. This documentation can be valuable when plans change, colleagues enter or leave the research collaboration, or in the future when a data set is revisited years after the research project was completed.
A variety of resources are available that describe data management and the range of considerations that researchers should analyze during the planning phases of any research project. Many of these resources are freely available to members of the public. To see the list of resources available to UNLV researchers, visit the Writing a Data Management Plan tab.
In other sections of this guide we define data, why you might need or want to create a data management plan, the recommended components of a data management plan, and provide helpful tips about storing, sharing and archiving your data.
Data are (and a single datum is) a basic form of information that may be used to make meaning through activities such as calculating, summarizing, or analyzing. (See the Merriam-Webster dictionary definition). For the purposes of academic research, scholarship, and creative endeavors it is most useful to consider that data are whatever foundational bits that researchers use to create meaning.
Data can be numbers, text, or other symbols. Below are examples of research data (from NCSU Libraries' Guide)
UNLV provides unique resources and assistance to our researchers. Please do not hesitate to contact the groups below to explore how they can assist with your data management needs.
Humorous video about sharing data and why best practices are important. From the authors: "A data management horror story by Karen Hanson, Alisa Surkis and Karen Yacobucci. This is what shouldn't happen when a researcher makes a data sharing request! Topics include storage, documentation, and file formats."