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Research Data Management: Research data lifecycle

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Research data lifecycle

Library Research Data Lifecycle

The research data lifecycle model describes and identifies the steps to be taken at the different stages of the research cycle to ensure successful data curation and preservation. There are several stages in the research data lifecycle, e.g. data creation, data processing, data analysis, etc.

There are a few models that one can make use to plan the data management activities, for example, DCC Curation Lifecycle Model (see also journal article about "The DCC Curation Lifecycle Model" by Sarah Higgins).

Pennock (2007) highlighted in Digital Curation: A Life-Cycle Approach to Managing and Preserving Usable Digital Information that the lifecycle approach is necessary because: 

  • Digital materials are fragile and susceptible to change from technological advances throughout their lifecycle, i.e. from creation onwards;
  • Activities (or lack of) at each stage in the lifecycle directly influence our ability to manage and preserve digital materials in subsequent stages;
  • Reliable re-use of digital materials is only possible if materials are curated in such a way that their authenticity and integrity are retained.

 

Stages in A Research Data Lifecycle

Each stage of a research data lifecycle may comprise many small activities. For example, data creation may involve new data collection, reuse of existing data, capturing and creating metadata.  

When you are considering the use of relevant existing research data, it would be useful to know which research data repositories to look.

More on Searching for existing third-party data

 

Further readings:

Video

Data Lifecycle & Searching for Data 

This 6 miniutes video introduces data lifecycle and searching for data. It is part of the video tutorial on practical data management, created by University of California Santa Cruz Library.

 

 

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Credit Note

A portion of the content is collaboratively developed with NUS and SMU Libraries.