A monthly series of infographics on research data

Published by the Library's Research Data Services (RDS) department, the Data Literacy Series (DLS) are visually-compelling one-page handouts that break down complex and important data-related topics. DLS complement the RDS's instructional efforts and mission to promote data education and research data management practices. The handouts are distributed under a CC BY-NC-SA 4.0 license. If you’d like to suggest a topic for an upcoming issue, please submit your feedback to rds@library.ucsb.edu.

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DLS-202406-QualCoding.pdf

Cracking the Coding for Qualitative Data

Qualitative coding is the systematic process of categorizing and segmenting textual or visual content into meaningful analytical units to identify patterns and themes within the data. This handout compares deductive and inductive approaches to qualitative coding and highlights campus-licensed and supported tools to aid in this process.

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TAGS: Data Analysis, Data Tools, Qualitative Data
DATE: 06-2024


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Sensitive-Textual-Data_navy.pdf

Sanitizing Sensitive Information from Textual Data

De-identifying text with human participant data is challenging due to its unstructured and sensitive nature, requiring careful measures for safe and ethical sharing. Here are eight essential steps to minimize re-identification risks while preserving reusability.

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TAGS: Data Ethics, De-Identification, Qualitative Data, Sensitive Data
DATE: 05-2024


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DLS-202404-ConsentDataSharing&Reuse-navy.pdf

Securing Consent for Data Sharing & Reuse

The informed consent process is a central component of the ethical conduct of research with human subjects overseen by an Institutional Review Board (IRB). Crafting compliant consent forms with permissive language broadens the shareability and usability of research data. Incorporating considerations for data sharing and potential reuse into the informed consent process is crucial to preempt future complications and adverse outcomes, all while meeting funders' and publishers' increasing data sharing requirements.

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TAGS: Consent Forms, Data Ethics, Data Sharing, Data Reuse, Human Subject Research, Informed Consent
DATE: 04-2024


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DLS-202403-ManagingHS-QualData-navy.pdf

The Intricacies of Managing Qualitative Data from Human Subject Research

Qualitative data is inherently nuanced and deeply contextual. While it offers rich interpretive possibilities, its analysis and presentation often demand considerable resources. Moreover, due to its sensitivity, managing qualitative research data obtained from human subjects—such as interviews and observations— poses distinct ethical challenges. This handout delineates key considerations, practical tips, and available resources for effectively handling this data type across its lifecycle.

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TAGS: Data Management, Data Sharing, Data Ethics, Qualitative Data, Human Subjects, Sensitive Data
DATE: 03-2024


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DLS-202402-DataAvailability_navy.pdf

Crafting Effective Data Availability Statements

Many scientific journals require authors to provide a data availability statement (DAS) to adhere to openness and transparency principles. The DAS specifies how and where the underlying data used in a study can be accessed and the terms under which they can be obtained. We cover best practicves for writing such statements in compliance with policy requirements.

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TAGS: Data Sharing, Data Reuse, Data Access, Data Licensing, Open Data, Restricted Data
DATE: 02-2024


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DLS-202401-Binder-navy.pdf

Bundle your Project and Computing Environment with Binder

Binder is an open-source and free service for researchers to create a shareable project version that can be viewed and interacted with within a reproducible computational environment that runs in the cloud via a web browser.

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TAGS: Code Documentation, Dependency Management, Reproducibility
DATE: 01-2024


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DLS-202312-Venv.pdf

Virtual Environments in Python with Venv

Venv operates independently, ensuring alterations to installed dependencies within one environment remain isolated from others and system-wide libraries. This isolation allows the creation of multiple virtual environments, each hosting its own Python versions and varying sets of libraries.

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TAGS: Code Documentation, Dependency Management, Reproducibility, Python programming
DATE: 12-2023


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dls-202311-renv-navy_0.pdf

Reproducible Environments with RENV

Is your project R-based? The renv package helps you set up R projects and manage dependencies to keep your environment consistent and reproducible.

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TAGS: Reproducibility, Dependency Management, Code Documentation, R Programming
DATE: 11-2023


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dls-202310-dependencies.pdf

Taming the Dependency Hell

Everybody has a "dependency hell" horror story to tell. In the spookiest month of the year, we describe the leading causes of this problem and how it impacts scientific reproducibility.

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TAGS: Reproducibility, Dependency Management, Code Documentation
DATE: 10-2023


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dls-202309-apis-navy.pdf

The ABCs of Web APIs

APIs or Application Programming Interfaces have become increasingly popular in academic research. They simplify data access, streamline data collection and analysis processes, enable real-time updates, support collaboration, provide access to specialized tools, and more.

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TAGS: API, Data Access
DATE: 09-2023