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Research Data Management

This guide provides information on how to better manage and share research data in any discipline.

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Data Curation Librarian

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Wasila Dahdul
Contact:
Science Library
Office 249
949-824-2185

Overview

Welcome!

This guide details ways to organize, manage, and share your research data to increase impact and ensure research reproducibility, and help meet journal and funder data sharing requirements. Research data management has become an important skill required of researchers as funding agencies and journal publishers increasingly implement data sharing policies.

The FAIR Data Principles

One of the grand challenges of data-intensive science is to facilitate knowledge discovery by assisting humans and machines in their discovery of, access to, integration and analysis of, task-appropriate scientific data and their associated algorithms and workflows. The FAIR Data Principles are a set of guiding principles to make data Findable, Accessible, Interoperable, and Re-usable.

From: FORCE11/The FAIR Data Principles 

F1. (meta)data are assigned a globally unique and eternally persistent identifier.
F2. data are described with rich metadata.
F3. (meta)data are registered or indexed in a searchable resource.
F4. metadata specify the data identifier.

A1  (meta)data are retrievable by their identifier using a standardized communications protocol.
A1.1 the protocol is open, free, and universally implementable.
A1.2 the protocol allows for an authentication and authorization procedure, where necessary.
A2 metadata are accessible, even when the data are no longer available.

I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
I2. (meta)data use vocabularies that follow FAIR principles.
I3. (meta)data include qualified references to other (meta)data.

R1. meta(data) have a plurality of accurate and relevant attributes.
R1.1. (meta)data are released with a clear and accessible data usage license.
R1.2. (meta)data are associated with their provenance.
R1.3. (meta)data meet domain-relevant community standards.

Research Data Management Lifecycle

Research Data Management Life Cycle (source: UCSC

Digital Scholarship Services

The UCI Libraries Digital Scholarship Services (DSS) fosters the use of digital content and transformative technology in scholarship and academic activities. DSS works with the campus community to publish, promote, and preserve the digital products of research in several areas. DSS can help you with all stages of data management required by funding agencies:

  • Write grant winning Data Management Plans
  • Deposit data into repositories for access and preservation
  • Capture metadata to allow re-use
  • Create permanently resolvable hyperlinks
  • Connect your data with your publications