Research Data Management
Research data management refers to the activity of working with research data throughout the research process: data capture, data processing, metadata creation, data quality checks, data storage & backup, data archiving, data sharing at the end of the process.
Although handling research data can be challenging, managing your data effectively will not only help your research to be robust and replicable, but can help you to anticipate potential problems that can occur during the research process, and will ensure that your research meets the requirements set out by research funders and publishers.
In the context of Research Data Management (RDM), several key roles contribute to ensuring that data is properly managed, protected, and utilized throughout its lifecycle. Here are the most common roles ensuring that research data is managed efficiently, securely, and in compliance with applicable regulations: 
- The Data Steward is responsible for managing the data within an organization or project. Ensures that data is stored, organized, and accessible in accordance with institutional and project-specific guidelines. A key contributor to the creation of a DMP, especially in defining how data will be curated, organized, and made available for sharing or long-term storage.
- Chief Data Officer (CDO) oversees the overall data strategy within an organization or research institution.
- Data Protection Officer (DPO) ensures that data management practices comply with data protection laws and regulations; responsible for overseeing the handling of sensitive data, including personal data, and ensuring privacy rights.
- Researcher/Principal Investigator (PI) is the lead researcher or project leader responsible for the research project and its data management. Oversee the creation, collection, and usage of research data.
- IT Support/Systems Administrator ensure that the technical infrastructure required for data management, such as servers, cloud storage, and databases, is functional, secure, and accessible.
Proper collaboration among these roles ensures that a comprehensive and effective Data Management Plan is developed for the research project.
Data Management Plan
Data Management Plan is a formal document you create to describe how you plan to collect, document, store and share your data throughout the lifecycle of a research project. DMP requires regular review and revision over the span of a research project.
Unlike many universities, NU does not have yet a data management policy that requires researchers to write a Data Management Plan (DMP) except to the item in the IREC application form, It is still good practice to manage your data throughout its lifecycle for a number of reasons:
Use the links below to help you plan for every stage of the data lifecycle.
In the DMP you will consider and answer the following questions:
- Why? The purpose of a data management plan is not simply to fulfill grant obligations, meet research or legal requirement (although this is important). DMPs should provide meaningful guidance to the investigator's team over the life of the project.
- Who? Who is responsible for overseeing the project's data? Creating it? Analyzing, transforming, and reporting it? Who will have access? Who will keep change logs and check data integrity? Should some of these tasks be delegated, and will doing so require training supporting personnel?
- What? What kind of data is being generated? What format is it created in, and what formats will it be translated into over its lifespan? How large will the files be, individually and as a set? What intermediate products might be created during the analysis?
- Where? Where will data be created/recorded? Where will it be stored? Should backups exist in multiple physical locations? Where will it be archived for long-term preservation?
- When? When will collaborators have access to data? When will the larger research community have access? The public? How long will data be retained? Is there a "maintenance schedule" for the data and associated records?
- How? How will the plan be enacted? How will adherence be measured? How will problems that arise be addressed? (Auburn University)
