A Jupyter Book Template for Research-Based Open Educational Resources in Data Literacy

Sep 12, 2026

A Jupyter Book–based template supports the creation of modular, interactive Open Educational Resources (OER) for data literacy. The design helps educators translate authentic research workflows into teachable modules, each combining theoretical foundations, hands-on practice, reflection tasks, and formative assessment. Data skills are embedded in discipline-specific case studies to yield reusable and accessible learning materials, while aligning software requirements with the varying competencies of OER creators through a clear instructional design and technical architecture.

LanguageEnglish

CategoryPresentations

FormatPDF

Pages6

Reading Time2 min

AccessFree to download

Introduction

Data literacy in research

Open Educational Resources and open science principles

QUADRIGA project and template overview

Audience and Benefits

Target instructors and researchers

Learning and classroom/workshop use

Cross-domain applicability

Instructional Design Integration

Case-study-centered pedagogy

Contextual training for non-STEM researchers

A Jupyter Book Template for Research-Based Open Educational Resources in Data Literacy Hannes Schnaitter 1 , Evgenia Samoilova 2 , and Lamia Islam 2 Abstract: This paper introduces a Jupyter Book–based template designed to support the creation of modular, interactive Open Educational Resources (OER) for data literacy. The template provides educators with a structured framework to convert authentic research workflows into pedagogically coherent modules, each comprising theoretical background, hands-on practice, reflective activities, and formative assessment. By embedding data skills within discipline-specific case studies, it enables the development of reusable and accessible learning materials. We describe the template’s instructional design and technical architecture, and highlight the core challenge of aligning software requirements with the diverse software competencies of OER creators. Keywords: Data literacy, Open Educational Resources, Jupyter Book, Case studies, Software competencies 1 Introduction In today’s research landscape, data literacy has emerged as a crucial competency for researchers across all disciplines. The ability to collect, manage, apply, and evaluate data in a critical manner [Ri15] is fundamental to modern scientific practice, particularly as research becomes increasingly data-intensive. Creating effective data literacy resources presents significant challenges, particularly in bridging theoretical knowledge with domain-specific research applications. Purely theoretical instruction, when detached from authentic practice, has limited impact on learners’ ability to transfer skills into their own work [AFG24] . Hence, effective data literacy training benefits from hands-on approaches using real data and authentic research scenarios [Ri15] . Open Educational Resources (OERs) contribute to addressing these educational challenges while aligning with the foundational principles of open science now embedded in contemporary scientific practice. Effective data literacy education necessitates teaching materials that themselves exemplify these principles through non-proprietary tools, accessible formats, and transparent processes [NB16] . To address this educational challenge, we developed a structured template [SSI24] within the QUADRIGA project [Bu24] for creating research-based interactive OERs centered on 1 Humboldt-Universität zu Berlin, Institut für Bibliotheks-und Informationswissenschaft, Unter den Linden 6, 10099 Berlin, Germany, [hannes.schnaitter.1@ibi.hu-berlin.de](hannes.schnaitter.1@ibi.hu-berlin.de), https://orcid.org/0000-0002-1602-6032 2 Universität Potsdam, Institut für Informatik, An der Bahn 2, 14476 Potsdam, Germany, [evgenia.samoilova@uni-potsdam.de](evgenia.samoilova@uni-potsdam.de), https://orcid.org/0000-0003-3858-901X; [lamia.islam@uni-potsdam.de](lamia.islam@uni-potsdam.de), https://orcid.org/0009-0001-1879-9880 􀀀􀀁􀀂 doi:10 . 18420/inf2025_ 111 authentic case studies. Implemented using Jupyter Book [Co20], the template transforms real research workflows from these case studies into modular learning experiences. This paper focuses on a structured Jupyter Book-based template: it details both the pedagogical framework, centered on case studies, and the technical implementation. 2 Audience and Benefits The primary objective of the developed template is to support instructors affiliated with the QUADRIGA data literacy center in designing research-based case studies that integrate pedagogically sound modular structures with the technical capabilities of the Jupyter Book framework. At the same time, the template is intentionally designed to be accessible to researchers outside the QUADRIGA project, enabling broader participation in the creation of open, reusable learning resources. By reducing technical barriers, the template invites contributors from various disciplinary backgrounds to share their data, research insights, and methodological expertise in the form

FAQs

What problem does the Jupyter Book template address for data literacy education?

It targets the gap between theoretical instruction and authentic, transferable skills by turning real research workflows into modular learning experiences for OER creators and learners.

What core components does each module in the template include?

Each module combines theoretical background, hands-on practice, reflective activities, and formative assessment.

How does the template support different types of creators and courses?

It reduces technical barriers for contributors beyond QUADRIGA and supports independent learning as well as instructor-led classroom or workshop use through selectable modules and interactive notebooks.

Sep 12, 2026

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