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Overview of Data Management: Introduction

Welcome

This guide will provide general information about data management, including

  • data management plans (DMPs)
  • file naming conventions
  • documentation
  • security and backup
  • publication and preservation

Explore the tabs across the top of this page to learn more.

 

Resources

Why Manage Data?

Record amounts of data are being generated on a daily basis. With constant improvements in technology, higher precision and coverage in data creation, collection, and acquisition and a higher capacity for storage, there is an increased importance in managing, integrating, and re-using data.  As more and more publishers and funding agencies require researchers to share their data, developing good data management practices early in you career will make it easier to keep your data organized, meet funder requirements, and prepare data for sharing with others.

Data management addresses the lifecycle of your research output including its creation, organization, accessibility, archiving and distribution.  "Data" types can include:

  • Observational: data that is captured real-time such as sensor data and survey data
  • Experimental: data collected from lab equipment such as gene sequences and magnetic field readings
  • Simulation: data generated from test models such as climate models and economic models
  • Derived or Compiled: data that is aggregated or analyzed such as data mining and compiled databases
  • Reference: data that is collected, reviewed, and published such as databanks and data portals 

A Deeper Dive Into Data Management

These resources can provide you with more data management information, training, and tools.

Subject Guide

Megan Sapp Nelson's picture
Megan Sapp Nelson
Contact:
3053 WALC
By Appointment

Make an appointment at https://sappnelson.youcanbook.me
765-49-42871
Website / Blog PageSkype Contact

Subject Expert

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Scott Brandt
Contact:
Purdue University Libraries

504 W. State Street

West Lafayette, IN 47907
Website / Blog Page