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Open Science training
Phase 1 - Planning research
This introductory course will help you to understand what open science is and why it is something you should care about. It includes interactive sections to help you put Open Science into practice.
This introductory course will help you to understand what open science is and why it is something you should care about. You'll get to grips with the expectations of research funders and will learn how practising aspects of open science can benefit your career progression. Upon completing this course, you will:
- understand what Open Science means and why you should care about it
- be aware of some of the different ways to go about making your own research more open over the research lifecycle
- understand why funding bodies are in support of Open Science and what their basic requirements are
- be aware of the potential benefits of practicing open science
It is important to remember that Open Science is not different to traditional science. It just means that you carry out your research in a more transparent and collaborative way. Open Science applies to all research disciplines. While Open Science is the most commonly used term, you may also hear people talking about Open Scholarship or Open Research in the Arts and Humanities.
Language: English
Level: Master's, PhD, early-stage researcher
Format/length: An interactive mix of text, video and quiz
Course period: Ongoing
Although its emphasis is on the trainer, this handbook will help instructors and students alike to adopt and use Open Science practices in their research.
Bringing together methods, techniques, and practices, the handbook aims at supporting educators of Open Science. The result is intended as a helpful guide on how to forward knowledge on Open Science principles to our networks, institutions, colleagues, and students. It will instruct and inspire trainers how to create high quality and engaging trainings. Addressing challenges and giving solutions, it will strengthen the community of Open Science trainers who are educating, informing, and inspiring themselves. The handbook is managed in this GitHub repository.
Language: English, Italian, Spanish, Portuguese
Level: Master's, PhD, early-stage researcher
Format/length: PDF e-book
Course period: Ongoing
A basic introduction to Open Science originally recorded for the UCL Library Skills training summer programme.
Language: English
Level: Master’s, PhD, early-stage researcher
Format/length: Video (09:33mins)
Course period: Ongoing
An interactive introductory course to help you understand the concepts and key principles of Open Science and Responsible Research & Innovation (RRI), how to corporate these into your own research, as well as the associated benefits.
This introductory course will help you to know the concepts of Open Science and RRI, key principles and the implications for practicing research.
Upon completion of this course, you will be able to:
- know the key concepts and benefits of Open Science
- know the pillars and dimensions of RRI
- be aware of the implications for practicing research
Language: English
Level: Master’s, PhD, early-stage researcher
Format/length: An interactive mix of text and quiz.
Course period: Ongoing
A mix of videos and interactive sections to help understand what Open Science is and how this can be applied to the research workflow. This also includes a final assessment.
The following course is a general introduction to the various components and philosophies of Open Science, that can directly enrich each step of the scholarly lifecycle (Open Notebook Science, OpenData, Open Research Software, Open Access). The overall objective of the course is to provide an introduction to why Open Science is essential to rigorous, reproducible and transparent research, as well as to future research evaluation criteria focused on societal impact.
Open Science is the practice of science in such a way that others can collaborate and contribute, where research data, lab notes and other research processes are freely available, under terms that enable reuse, redistribution and reproduction of the research and its underlying data and methods.
The learning outcomes of this course are:
- understand the relevance of OS in relation to research integrity, reproducibility and impact;
- identify suitable tools to help you embrace OS at each stage of the research lifecycle;
- understand the potential of OS in supporting innovation and economic growth
Estimated time for completing this course is 3.5 hours.
Greater insight on how to implement Open Data and Research Data Management, Open Access, copyright and e-infrastructures into the scholarly lifecycle and grant proposal preparation, can be found in the rest of the FOSTER courses.
Language: English
Level: Master’s, PhD, early-stage researcher
Format/length: An interactive mix of text, video and quiz. Estimated completion time for this course is 3.5 hours.
Course period: Ongoing
This introductory course offers some practical steps on how to open your research practices in order to meet funder, peer and publisher requirements and expectations of open scholarship.
This course introduces some practical steps toward making your research more open. We begin by exploring the practical implications of open research, and the benefits it can deliver for research integrity and public trust, as well as benefits you will accrue in your own work. After a short elaboration of some useful rules of thumb, we move quickly onto some more practical steps towards meeting contemporary best practice in open research, and introduce some useful discipline specific resources. Upon completing this course, you will:
- be able to contextualise you research environment
- be aware of the questions you should bear in mind as you progress through the key stages of your research
- know about some discipline-specific resources to help you embed Open Science into work research practices
Language: English
Level: Master’s, PhD, early-stage researcher
Format/length: An interactive mix of text, video and quiz
Course period: Ongoing
An introduction to the basics of research data management including data formats, persistent identifiers, licencing, data repositories and metadata.
S. Venkataraman (DCC) talks about the basics of Research Data Management and how to apply this when creating or reviewing a Data Management Plan (DMP). He discusses data formats and metadata standards, persistent identifiers, licensing, controlled vocabularies and data repositories.
Language: English
Level: Master’s, PhD, early-stage researcher
Format/length: Video (13:30mins)
Course period: Ongoing
A general introduction to good data management practices with an overview of how to organise, manage, document, format, store, encrypt and share data produced from research projects.
The introductory workshops on Data Management Basics are intended for researchers and anyone who wants to learn about research data management. This first workshop provides an overview of how to manage, document, store and safeguard research data well and how to plan and implement good data management in research projects, with a focus on optimising data sharing. In this free session we will discuss key essential processes: Writing a data management plan for research grants; documenting your data appropriately and effectively; formatting and organising your data; and storing your data, including data transfer, encryption, and file sharing.
Language: English
Level: Master’s, PhD, early-stage researcher
Format/length: Video recording of workshop (62:34mins)
Course period: Ongoing
Introduction to Pre-Registration from the Berkeley Initiative for Transparency in the Social Sciences (BITSS).
Language: English
Level: Master’s, PhD, early-stage researcher
Format/length: Video (09:57mins)
Course period: Ongoing
An introduction to pre-registration with discussion on the distinction between exploratory and confirmatory results. Preregistration may be useful against publication bias and help enhance the credibility of research findings.
More researchers are preregistering their studies as a way to combat publication bias and improve the credibility of research findings. Preregistration is at its core designed to distinguish between confirmatory and exploratory results. Both are important to the progress of science, but when they are conflated, problems arise. In this webinar, we discuss the What, Why, and How of preregistration and what it means for the future of science.
Language: English
Level: Master’s, PhD, early-stage researcher
Format/length: Video (56:36mins)
Course period: Ongoing
An introduction to the basics of pre-registration and registered reports, and their utility in helping the researcher to create a record of their research plan prior to data collection.
In this deep dive session, Amanda Montoya (UCLA) and Karen Rambo-Hernandez (Texas A&M University) introduce the basics of preregistration and Registered Reports: two methods for creating a permanent record of a research plan prior to conducting data collection. They discuss the conceptual similarities and practical differences between pre-registration and registered reports. They provide practical advice from their own experiences using these practices in research labs and resources available for researchers interested in using these approaches. The session concludes with questions and discussion about adopting these practices and unique considerations for implementing these practices in education research.
Language: English
Level: Master’s, PhD, early-stage researcher
Format/length: Video (65:12mins)
Course period: Ongoing
An overview of the process of pre-registration in qualitative research.
In this webinar, Tamarinde Haven provides an overview of the process of preregistration in qualitative research. We review the process of preregistration, how we partnered with a community of qualitative researchers to develop a template for qualitative research through a Delphi study, and a guide to the fields that were included in the final form.
Language: English
Level: Master’s, PhD, early-stage researcher
Format/length: Video (59:52mins)
Course period: Ongoing
An overview on the pre-registration of secondary data with an example of how the presenters developed and tested a template for the pre-registration of research that uses existing datasets.
In this webinar, Olmo van den Akker and Marjan Bakker (Tilburg University), Pam Davis-Kean (University of Michigan), and David Mellor (Center for Open Science) overview the process of preregistering secondary data analyses. See a demonstration of the Secondary Data Preregistration template on OSF, including examples and best practices for writing up preregistered work.
Language: English
Level: Master’s, PhD, early-stage researcher
Format/length: Video (60:09mins)
Course period: Ongoing
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