Dashboards for data visualisation, such as R Shiny and Tableau, allow an interactive exploration of data by means of drop-down lists and checkboxes, with no coding for the user. The apps can be useful for both the data analyst and the public.

This is a full length textbook explaining copyright for librarians. It has a particularly helpful chapter explaining international treaties and the Berne three-step test. The chapter on "creative approaches and alternatives" has a helpful introduction to the Creative Commons as well as Open Access.

It also has helpful case study examples to demonstrate the concepts in an applied manner which really will help students to better understand the content of the textbook.

The Digital Dexterity framework for library professionals originated at a workshop facilitated by Helen Beetham in Sydney in January 2019 (attended by over 70 library professionals from across Australia and New Zealand). The workshop outcomes were subsequently refined by a group of library professionals “Digital Dexterity champions” – as such this is a framework developed by library professionals for library professionals.

This Library Carpentry lesson introduces archivists to working with data. At the conclusion of the lesson you will: be able to explain terms, phrases, and concepts in code or software development; identify and use best practice in data structures; use regular expressions in searches.

Original data has become more accessible thanks to cultural and technological advances. On the internet, we can find innumerable data sets from sources such as scientific journals and repositories, local and national governments, and non-governmental organisations. Often, these data may be presented in novel ways, by creating new tables or plots, or by integrating additional data. Free, open-source software has become a great companion for open data. This open scholarship project offers free workshops and coding meet-ups (hackathons) to learn and practise data presentation, across the UK. It is made possible by a fellowship of the Software Sustainability Institute.

Purpose: To introduce methods and tools in organization, documentation, automation, and dissemination of research that nudge it further along the reproducibility spectrum.OutcomeParticipants feel more confident applying reproducibility methods and tools to their own research projects.ProcessParticipants practice new methods and tools with code and data during the workshop to explore what they do and how they might work in a research workflow. Participants can compare benefits of new practices and ask questions to help clarify which would provide them the most value to adopt.

Library Carpentry lesson: An introduction to Git. What We Will Try to Do Begin to understand and use Git/GitHub. You will not be an expert by the end of the class. You will probably not even feel very comfortable using Git. This is okay. We want to make a start but, as with any skill, using Git takes practice. Be Excellent to Each Other If you spot someone in the class who is struggling with something and you think you know how to help, please give them a hand. Try not to do the task for them: instead explain the steps they need to take and what these steps will achieve. Be Patient With The Instructor and Yourself This is a big group, with different levels of knowledge, different computer systems. This isn’t your instructor’s full-time job (though if someone wants to pay them to play with computers all day they’d probably accept). They will do their best to make this session useful. This is your session. If you feel we are going too fast, then please put up a pink sticky. We can decide as a group what to cover.

This Library Carpentry lesson introduces librarians and others to working with data. This Library Carpentry lesson introduces people with library- and information-related roles to working with data using regular expressions. The lesson provides background on the regular expression language and how it can be used to match and extract text and to clean data.

Library Carpentry lesson: an introduction to OpenRefine for Librarians This Library Carpentry lesson introduces people working in library- and information-related roles to working with data in OpenRefine. At the conclusion of the lesson you will understand what the OpenRefine software does and how to use the OpenRefine software to work with data files.

Library Carpentry, an introduction to SQL for Librarians This Library Carpentry lesson introduces librarians to relational database management system using SQLite. At the conclusion of the lesson you will: understand what SQLite does; use SQLite to summarise and link data.

Library Carpentry lesson to learn how to use the Shell. This Library Carpentry lesson introduces librarians to the Unix Shell. At the conclusion of the lesson you will: understand the basics of the Unix shell; understand why and how to use the command line; use shell commands to work with directories and files; use shell commands to find and manipulate data.

This is a tool to use in evaluating school library facilities. It can be used by a team of evaluators, as a precursor to renovations, to look at equity throughout a school district, or by an individual librarian or administrator.

Headlines and scholarly publications portray a crisis in biomedical and health sciences. In this webinar, you will learn what the crisis is and the vital role of librarians in addressing it. You will see how you can directly and immediately support reproducible and rigorous research using your expertise and your library services. You will explore reproducibility guidelines and recommendations and develop an action plan for engaging researchers and stakeholders at your institution. #MLAReproducibilityLearning OutcomesBy the end of this webinar, participants will be able to: describe the basic history of the “reproducibility crisis” and define reproducibility and replicability explain why librarians have a key role in addressing concerns about reproducibility, specifically in terms of the packaging of science explain 3-4 areas where librarians can immediately and directly support reproducible research through existing expertise and services start developing an action plan to engage researchers and stakeholders at their institution about how they will help address research reproducibility and rigorAudienceLibrarians who work with researchers; librarians who teach, conduct, or assist with evidence-synthesis or critical appraisal, and managers and directors who are interested in allocating resources toward supporting research rigor. No prior knowledge or skills required. Basic knowledge of scholarly research and publishing helpful.

The Music Librarianship Course working group developed this syllabus from 2019-2021, centering the principles of critical music librarianship with a particular focus on social justice and antiracist practices. This working group was funded by a Music Library Association grant. The syllabus may be used as a template for library educators or as a self-guided independent study for Master of Library and Information Science (MLIS) students attending programs without a specialization in music librarianship. Learn more about our process in our white paper on the need for online music librarianship offerings and our MLA conference poster on the course planning project are in Humanities Commons. 

The OPEN (Open Project Engagement Network) Incubator is a research development program and modular curriculum designed to advance a project from idea to proof-of-concept, infused with and aware of open scholarship principles and practices.

The open-access.net platform provides comprehensive information on the subject of Open Access (OA) and offers practical advice on its implementation. Developed collaboratively by the Freie Universität Berlin and the Universities of Goettingen, Konstanz, and Bielefeld, open-access.net first went online at the beginning of May 2007. The platform's target groups include all relevant stakeholders in the science sector, especially the scientists and scholars themselves, university and research institution managers, infrastructure service providers such as libraries and data centres, and funding agencies and policy makers. open-access.net provides easy, one-stop access to comprehensive information on OA.

Aspects covered include OA concepts, legal, organisational and technical frameworks, concrete implementation experiences, initiatives, services, service providers, and position papers. The target-group-oriented and discipline-specific presentation of the content enables users to access relevant themes quickly and efficiently. Moreover, the platform offers practical implementation advice and answers to fundamental questions regarding OA.
In collaboration with cooperation partners in Austria (the University of Vienna) and Switzerland (the University of Zurich), country-specific web pages for these two countries have been integrated into the platform - especially in the Legal Issues section.

Each year since 2007, the information platform has organised the "Open Access Days" at alternating venues in collaboration with local partners. This event is the key conference on OA and Open Science in the German-speaking area.

With funding from the Ministry of Science, Research and the Arts (MWK) of the State of Baden-Württemberg, the platform underwent a complete technical and substantive overhaul in 2015.

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.