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Research Lifecycle

Responsible Conduct of Research

Keep these three guidelines handy! 

Guidelines for Best Practices in Image Processing

Understanding Data Management

Why manage data?

  • to preserve the integrity of the research
  • to allow reuse by others
  • to reduce risk of data loss

Why make data discoverable?

  • to enable work to be reproduced
  • to establish credibility and to hold trust
  • to enable faster progress in research, within or across disciplines
  • to meet requirements of funders, journal publishers, etc.

Why reuse data?

  • to verify research claims
  • to permit new discoveries from exisitng data
  • to foster integration of data sets for new analysis
  • to reduce duplication of effort

Data Management Plan - outline

A successful Data Management Plan (DMP) answers these questions:

Creating your data

  • What types of data will be produced for your project?
  • What identifiers will you use for your data?
  • How will you document your data?
  • How much data will the project produce?
  • How often will the data change or be updated, and will versions need to be tracked?

Organizing your data

  • What file formats will be produced for your project and what kinds of data management risks do they present?
  • How will you organize your files into directories and what naming conventions will you apply to both?
  • Have you included project and data documentation?

Managing your data

  • Who is responsible for managing and controlling the data?
  • For what or whom are the data intended?
  • How long must the data be retained?
  • How secure are the data? Do you have a procedure for backing up the data?

Sharing your data

  • Does project funding require your data to be shared or publicly accessible?
  • When and where do you intend to publish or distribute your data?
  • How should your data be cited?
  • Are there issues with privacy or intellectual property?

Managing your lab notebook

Why keep a lab notebook?

  • To have a complete record of the work you have done and to maintain your rights to your findings.  Keep all your procedures, data, and comments in one place.
  • To prove that you did the work, and on what date -- especially if your work is novel, article-worthy, or potentially patentable.
  • To leave a trail for someone who may be interested in completing your work.
  • To serve multiple audiences: yourself, your colleagues, your funding sources.

Best practices:

Tools for Data Management

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