Data Curation

What is data curation?

Data Curation is the documentation, management, and preservation of research data to produce datasets that are FAIR: Findable, Accessible, Interoperable, and Reusable. By curating research data we add value by enhancing data sets for current use, as well as future discovery and reuse. 

Source: https://libguides.uvic.ca/researchdata/researchdata/share/curationguides

What is research data?

Research data are items of recorded information "necessary to validate or reproduce your research findings, or to gain a richer understanding of them." (University of Edinburgh - Information Services). Research data encompasses a broad set of categories, from physical specimens to sensor output to the software developed to support analysis of data. Some examples of research data include: 

• Documents (plain-text, rich-text, PDF, spreadsheets)
• Laboratory notebooks, field notebooks, diaries
• Questionnaires, transcripts, survey responses
• Audio and video recordings
• Images such as film, photographs, digital scans, or medical scans such as computed tomography
• Protein or genetic sequences
• Spectra
• Slides, artifacts, specimens, samples
• Collection of digital objects acquired and generated during the process of research
• Database contents (video, audio, text, images)
• Software including code and documentation, models, algorithms and scripts
• Methodologies and workflows
• Standard operating procedures and protocols

Why curate and share your data?

• To fulfill funder requirements. NIH, NSF, NEH, and many other research funding sources expect researchers to publish and preserve access to their data.
• Some journals and societies require data publishing and preservation, i.e., PLOS, Nature, Dryad partner journals, to name a few.
• To increase the impact of your research. Sharing detailed research data is associated with increased citation rate (PLoS ONE).
• To address questions about reproducibility
• To speed the rate of discoveries in your discipline.
• To establish priority and a public record.

           Source: https://www.lib.uiowa.edu/data/share/

How can this guide help me?

This guide will assist researchers at any stage of a project in the preparation of their project's data and metadata in order to ensure it is compliant with FAIR principles: Findable, Accessible, Inter-operable, and Re-usable. The included tutorial will guide you, step by step, through the data curation process.