Steps in the Data Life Cycle

Proposal Planning & Writing

  • Review of existing data sources, determine if project will produce new data or combine existing data

  • Investigate archiving challenges, costs, consent and confidentiality

  • Identify potential users of your data

  • Contact Archives for advice

Project Start Up

  • Create a data management plan

  • Make decisions about documentation form and content

  • Conduct pretest of collection materials and methods

Data Collection

  • Organize files, backups & storage, QA for data collection

  • Think about access control and security

Data Analysis

  • Document analysis and file manipulations

  • Manage file versions

Data Sharing

  • Determine file formats

  • Contact Archive for advice

  • Further document and clean data

End of Project

  • Deposit data in data archive (repository)

Remember: Managing data in a research project is a process that runs throughout the project. Good data management is one of the foundations for reproducible research. Good management is essential to ensure that data can be preserved and remain accessible in the long-term, so it can be re-used and understood by future researchers. Begin thinking about how you’ll manage your data before you start collecting it.

 

DataLifeCycle

Other Life Cycles

Parts on this webpage taken from: Van den Eynden, V., Corti, L., Woollard, M. & Bishop, L. (2009). Managing and Sharing Data: A Best Practice Guide for Researchers. Retrieved 02/06/2010, from http://www.data-archive.ac.uk/media/2894/managingsharing.pdf