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Navigating the Dataset Landscape

This resource is designed to supplement instructional sessions and serve as a reference for researchers, students, and faculty members interested in discovering and utilizing datasets in the sciences and engineering fields.

Overview of Open Data Movement and Data Sharing Practices

Open Data Movement: Advocates for making data freely available to everyone to use and republish without restrictions.

Benefits:

  • Promotes transparency and reproducibility.
  • Accelerates scientific discovery and innovation.
  • Facilitates collaboration across disciplines.

Data Sharing Practices:

  • Increasingly required by funding agencies and publishers.
  • Involves depositing data in accessible repositories.
  • Requires attention to data management planning and ethical considerations.

Findable, Accessible, Interoperable, and Reusable (FAIR) Datasets

Findable: Data should be easy to find for both humans and computers. Proper metadata and indexing are essential.

Accessible: Once found, data must be retrievable using standard protocols.

Interoperable: Data should be compatible with other datasets and tools, enabling integration and analysis.

Reusable: Data should be well-described so it can be replicated and/or combined in future research.