Skip to Main Content
     

A Guide To...Digital and Emerging Scholarship

This guide is dedicated to the advancement of digital and emerging scholarship at the College of the Holy Cross.

What is Research Data Management?

Research data refers to any information produced throughout all stages of a research project. This can include anything from experiment data pulled from daily lab notes or information on research subjects involved in a clinical study.

Research data management (or RDM) refers to the organization, storage, preservation, and sharing of research data. All stages of a research project lifecycle creates some type of data. The planning stage may include proposals or grant applications, conducting the experiment will produce many layers of data and results, and the preservation stage will be important when publishing and sharing research conclusions.

Why is managing research data so important?

There are many reasons why managing research data is so important. It is one of the most important aspects of any research project and wrangling large quantities of data is not easy. This is where Research Data Management comes in.

By creating an RDM plan from the beginning, you will ensure that your data will be organized and protected. This will make it easier to access when publishing your findings, sharing your work, or even reproducing other researcher’s experiments. It helps prevent errors and allows others to validate your findings. Many funders and publishers are now even requiring some level of access to research data. When data is easily organized and shared, valuable discoveries can be made by others outside of the original research team.

Research Data Lifecycle

According to the Data Observation Network for Earth (DataONE), “the data life cycle provides a high level overview of the stages involved in successful management and preservation of data for use and reuse” (source). Therefore, is important to plan and implement proper data management policies at all stages of a project. The DataOne Data Life Cycle is as follows:

For more information on the Data Life Cycle, visit the DataONE web page.