Open Science, the movement to make scientific products and processes accessible to and reusable by all, is about culture and knowledge as much as it is about technologies and services. Convincing researchers of the benefits of changing their practices, and equipping them with the skills and knowledge needed to do so, is hence an important task.This book offers guidance and resources for Open Science instructors and trainers, as well as anyone interested in improving levels of transparency and participation in research practices. Supporting and connecting an emerging Open Science community that wishes to pass on its knowledge, the handbook suggests training activities that can be adapted to various settings and target audiences. The book equips trainers with methods, instructions, exemplary training outlines and inspiration for their own Open Science trainings. It provides Open Science advocates across the globe with practical know-how to deliver Open Science principles to researchers and support staff. What works, what doesn’t? How can you make the most of limited resources? Here you will find a wealth of resources to help you build your own training events.

Open Science is a collection of actions designed to make scientific processes more transparent and results more accessible. Its goal is to build a more replicable and robust science; it does so using new technologies, altering incentives, and changing attitudes. The current movement towards open science was spurred, in part, by a recent “series of unfortunate events” within psychology and other sciences. These events include the large number of studies that have failed to replicate and the prevalence of common research and publication procedures that could explain why. Many journals and funding agencies now encourage, require, or reward some open science practices, including pre-registration, providing full materials, posting data, distinguishing between exploratory and confirmatory analyses, and running replication studies. Individuals can practice and encourage open science in their many roles as researchers, authors, reviewers, editors, teachers, and members of hiring, tenure, promotion, and awards committees. A plethora of resources are available to help scientists, and science, achieve these goals.

An ecosystem of free open source tools for improving the rigor and reproducibility of research is thriving. Information professionals at research institutions must stay informed about what tools are available and how they compare. Ideally, information professionals can also onboard researchers to kickstart adoption of these tools. However, developing quality curriculum to train researchers on new tools requires expertise in the tool itself, which leaves many researchers without training on tools that may benefit their research.
This course will train participants to run hands-on, quality modules designed to onboard researchers to four free open source tools. Participants will experience each module, practice the exercises, and explore the training material needed to run the module themselves. An instructor guide that includes the module outline, objectives, description, frequently asked questions, pre- and post-participant surveys, target audience, and instructions for running a successful module is provided for each tool taught.

This course will train participants to run modules on unique aspects of four free open source tools for researchers:

Binder: Share your computational environment, code, and research notebooks.
Renku: Document and share your analysis pipelines.
Open Science Framework: Create a centralized, structured workspace for your research materials.
KnitR: Knit your R code with your analysis narrative in one executable research notebook and capture your dependencies.

Many participants already run short-duration training events at their institutions. This course is ideal for those participants who wish to improve the quality and variety of the training they already offer to researchers. Participants who do not currently run short-duration training events at their institutions will benefit from the course by learning an accessible and efficient way of getting started with these four modules.

Computational analyses are playing an increasingly central role in research. Journals, funders, and researchers are calling for published research to include associated data and code. However, many involved in research have not received training in best practices and tools for sharing code and data. This course aims to address this gap in training while also providing those who support researchers with curated best practices guidance and tools.This course is unique compared to other reproducibility courses due to its practical, step-by-step design. It is comprised of hands-on exercises to prepare research code and data for computationally reproducible publication. Although the course starts with some brief introductory information about computational reproducibility, the bulk of the course is guided work with data and code. Participants move through preparing research for reuse, organization, documentation, automation, and submitting their code and data to share. Tools that support reproducibility will be introduced (Code Ocean), but all lessons will be platform agnostic.Level: IntermediateIntended audience: The course is targeted at researchers and research support staff who are involved in the preparation and publication of research materials. Anyone with an interest in reproducible publication is welcome. The course is especially useful for those looking to learn practical steps for improving the computational reproducibility of their own research.

A collection of slides for virtually all presentations given by Center for Open Science staff since its founding in 2013.

Qualitative research has long suffered from a lack of free tools for analysis, leaving no options for researchers without significant funds for software licenses. This presents significant challenges for equity. This panel discussion will explore the first two free/libre open source qualitative analysis tools out there: qcoder (R package) and Taguette (desktop application). Drawing from the diverse backgrounds of the presenters (social science, library & information science, software engineering), we will discuss what openness and extensibility means for qualitative research, and how the two tools we've built facilitate equitable, open sharing.

As research across domains of study has become increasingly reliant on digital tools (librarianship included), the challenges in reproducibility have grown. Alongside this reproducibility challenge are the demands for open scholarship, such as releasing code, data, and articles under an open license.Before, researchers out in the field used to capture their environments through observation, drawings, photographs, and videos; now, researchers and the librarians who work alongside them must capture digital environments and what they contain (e.g. code and data) to achieve reproducibility. Librarians are well-positioned to help patrons open their scholarship, and it’s time to build in reproducibility as a part of our services.Librarians are already engaged with research data management, open access publishing, grant compliance, pre-registration, and it’s time we as a profession add reproducibility to that repertoire. In this webinar, organised by LIBER’s Research Data Management Working Group, speaker Vicky Steeves discusses how she’s built services around reproducibility as a dual appointment between the Libraries and the Center for Data Science at New York University.

A lighting talk at csv,conf,4 about how libraries and librarians are helping researchers with reproducibility.

SPARC is a global coalition committed to making Open the default for research and education. SPARC empowers people to solve big problems and make new discoveries through the adoption of policies and practices that advance Open Access, Open Data, and Open Education.

Welcome to School Library Learning 2.0. This tutorial is brought to you by the California School Library Association (CSLA) 2.0 Team. You will learn the tools of the new Internet: Web 2.0 tools that are bringing our kids in touch with the entire world through social networking, wikis, video, podcasting, and gaming sites. The exercises give you the background you need to understand the tools you're learning about.

Searching as Information Literacy: Unpacking the ACRL Frame of Searching as Strategic Exploration is an OER that includes a podcast, blog and associated exercise. Three University of Ottawa librarians are interviewed on search challenges they have encountered and their proposed search strategies as it relates to the ACRL framework: Searching as Strategic Exploration.

Interview 1: Thinking Outside the Box

Interview 2: Selecting Appropriate and Relevant Search Terms

Interview 3: Rethinking the Value of Google

Created by students in ISI 6372 Information Literacy at the University of Ottawa, Winter 2020.

If you can answer these TEN questions you will have built the engine of a Stage 1 Registered Report.

This article offers a short guide to the steps scientists can take to ensure that their data and associated analyses continue to be of value and to be recognized. In just the past few years, hundreds of scholarly papers and reports have been written on questions of data sharing, data provenance, research reproducibility, licensing, attribution, privacy, and more—but our goal here is not to review that literature. Instead, we present a short guide intended for researchers who want to know why it is important to “care for and feed” data, with some practical advice on how to do that. The final section at the close of this work (Links to Useful Resources) offers links to the types of services referred to throughout the text.

This lesson provides teachers with support for using text-dependent questions and Common Core literacy strategies to help students derive big ideas and key understandings while developing vocabulary using the text "Tomas and the Library Lady". With the help of the English-speaking local librarian, Spanish-speaking Tomas is encouraged to assume the role of family storyteller, finding that he cannot only be a learner but a teacher as well.

Central location housing curriculum materials and planning tools for trainers of the COS Introduction to Open and Reproducible Research workshop.