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Data Management

Resources to help you manage, store, and share your data.

Data Management Basics


This resource guide offers data management support for all members of the CPP community: students, staff, and faculty researchers. You'll find information about the basics of managing, storing, and sharing data. If you are off-campus, some of the resources featured here require that you login with your BroncoID and Password. Whether you've found this guide while working on an assignment or as you're trying to manage data for a special project, please reach out if you have questions or are in need of additional support.

The Basics

What is data management?

Data management is a series of actions you can take as a researcher throughout the lifecycle of your research project. These actions help to keep your data organized, usable, and sharable.


So, why manage your data?

  • Managing your data will benefit you and your collaborators.

  • It will benefit the scientific community, as well as academic research more broadly.

  • Journals and sponsors will want to share your data, some even require access.


A Data Sharing Horror Story via NYU Health Sciences Library


How does the University Library support Data Management?

The University Library can support your Data Management journey in multiple ways, through:

  • Access to resources like this Research Guide

  • One-on-one data management consultations

  • Recommendations for data repositories

  • General support through the creation of your Data Management Plan

The Data Lifecycle

To better understand how data or the management of data factors into our research, it's important to recognize the critical elements of the Data Lifecycle.


Data lifecycle graphic, created by University of Ottawa.


The data lifecycle begins with planning your research project and, often, creating a data management plan that describes how your data will be used throughout your project and where it will go when your project ends. The resources present throughout this guide can help you do just that – whether formally for a funder or informally for your own project management.


Under the Data Lifecycle model, after you PLAN your project, you CREATE or locate datasets.

You then PROCESS or clean your data, and ANALYZE your data to write up your conclusions.

You then PRESERVE your data so that it will be usable for researchers across your institution and beyond.

You then SHARE your data since sharing is a vital component of scientific inquiry and progress. Other researchers, as well as members of your own research team, can now REUSE what you've created for their own experiments and the data lifecycle begins again.