FOSTER Open Science
Topic outline
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The Project
FOSTER Plus (Fostering the practical implementation of Open Science in Horizon 2020 and beyond) is a 2-year, EU-funded project, carried out by 11 partners across 6 countries. The primary aim is to contribute to a real and lasting shift in the behaviour of European researchers to ensure that Open Science (OS) becomes the norm.
Research communities, research performing institutions, and research funders have each recognised that OS skills are increasingly essential for researchers to undertake responsible research and innovation. While there is increasing agreement around the need to improve OS skills amongst all stakeholders, the adoption of OS approaches has been quite limited to date. Indeed general awareness of OS approaches has improved among EU researchers. However, there is still a lack of practical guidance and training to help researchers learn how to open up their research within a particular domain or research environment. For this reason, FOSTER Plus places specific emphasis on creating discipline-specific guidance and is partnering with expert organisations representing the scientific areas of life science, social science and humanities.
FOSTER Plus will enhance existing materials and co-produce new training content. The resources will be discipline-specific and their practical and tangible outcomes can directly be applied into researchers’ daily practices. The training activities will be addressed to all relevant stakeholders in the European Research Area, with a focus on young scientists, academic staff and policy makers. A strong train-the-trainer approach and network of open science trainers to act as ambassadors will help to reach a wide audience.
Our Objectives
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Support a culture change,whereby the practical aspects of Open Science are fully implemented and ultimately rewarded, by providing an advanced-level, outcome-oriented training programme based on courses and activities for which participants can attain digital badges.
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Consolidate and sustain a training support network comprised of Open Science ambassadors from a range of research performing organisations and research infrastructures.
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Strengthen the training capacity by addressing the current skills and content gaps, both at community/discipline and institutional levels, on the practical implementation of Open Science.
Main Activities
The objectives will be pursued through the combination of the following main activities:
- Delivery of face-to-face training events, blended and e-learning courses that will focus on providing practical, outcome-oriented lessons;
- Creation of high quality and advanced-level training resources including a multi-module Open Science toolkit and an Open Science training handbook
- Consolidation of an Open Science trainers network involving the disciplinary communities of humanities, social sciences and life sciences
Quick Facts
- Project Name: FOSTERING THE PRACTICAL IMPLEMENTATION OF OPEN SCIENCE IN HORIZON 2020 AND BEYOND
- Project Acronym: FOSTER Plus
- Project number: 741839
- Start Date: 01/05/2017
- Duration: 24 months
- Funding from the EC: 925.846,26€
- Website: www.fosteropenscience.eu
Project Partners
- Universidade do Minho – Portugal
- University of Göttingen – Germany
- The Open University – UK
- Stichting eIFL.net – Netherlands
- University of Edinburgh – DCC – UK
- University of Glasgow – DCC – UK
- Danmarks Tekniske Universitet – Denmark
- Stichting LIBER – Netherlands
- Consejo Superior de Investigaciones Científicas – Spain
- GESIS – Leibniz-Institute for the Social Sciences – Germany
- Fundacio Centre de Regulacio Genomica – Spain
- Associated partners: Digital Research Infrastructure for the Arts and Humanities (DARIAH-EU) and Leibniz Information Centre for Science and Technology (TIB)
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Data-driven research is becoming increasingly common in a wide range of academic disciplines, from Archaeology to Zoology, and spanning Arts and Science subject areas alike. To support good research, we need to ensure that researchers have access to good data. Upon completing this course, you will:
- understand which data you can make open and which need to be protected
- know how to go about writing a data management plan
- understand the FAIR principles
- be able to select which data to keep and find an appropriate repository for them
- learn tips on how to get maximum impact from your research data
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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
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Data-driven research is becoming increasingly common in a wide range of academic disciplines, from Archaeology to Zoology, and spanning Arts and Science subject areas alike. To support good research, we need to ensure that researchers have access to good data. Upon completing this course, you will:
- understand which data you can make open and which need to be protected
- know how to go about writing a data management plan
- understand the FAIR principles
- be able to select which data to keep and find an appropriate repository for them
- learn tips on how to get maximum impact from your research data
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This course introduces Open Source Software (OSS) management and workflow as an emerging but critical component of Open Science. The course explains the role of software sharing and sustainability in reproducibility, trust and longevity, and provides different perspectives around the sharing and reuse of computational code and methods, namely the software producer, the software reuser, and the non-coder with an interest either in reproducing research findings or in following experimental processes. You'll learn about useful resources and tools for sharing and exposing your code and workflows. Upon completing this course, you will:
- understand the roles that open source software and open workflows play in supporting Open Science
- know how Open Science can support reproducibility
- be aware of issues to consider at different stages of the research lifecycle
- know about useful tools and resources to help you get started with using OSS and open workflows
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This course covers data protection in particular and ethics more generally. It will help you understand the basic principles of data protection and introduces techniques for implementing data protection in your research processes. Upon completing this course, you will know:
- what personal data are and how you can protect them
- what to consider when developing consent forms
- how to store your data securely
- how to anonymise your data
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Licensing your research outputs is an important part of practicing Open Science. In this course, you will:
- know what licenses are, how they work, and how to apply them
- understand how different types of licenses can affect research output reuse
- know how to select the appropriate license for your research
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This course helps you to become skilled in Open Access (OA) publishing in the context of Open Science. By the end of the course, you will:
- understand how to publish your work openly and be aware of the advantages
- be able to find an OA publisher for your research
- know how to find a suitable repository to provide OA and archive your work
- know how to publish OA monographs
- understand funders' expectations and policies on OA
- be able to secure funding for Article Processing Charges (APCs) where applicable
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This course shows you how sharing preprints can improve your research and support Open Science. By the end of the course, you will:
- know what preprints are
- be able to find a suitable preprints platform to share your early findings
- understand the pro and cons of sharing preprints
- be aware of how sharing preprints can benefit your career progression
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This course introduces you to open peer review (OPR), an emerging practice which is gaining momentum as part of Open Science. Upon completing this course, you will:
- understand what OPR means and how it supports Open Science
- be aware of OPR workflows and which aspects of the review process can be conducted openly
- know how to write a constructive and responsible open peer review
- know about useful tools and services that can support you putting OPR into practice
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This course helps you to understand open business models and responsible research and innovation (RRI) and illustrates how these can foster innovation. By the end of the course, you will:
understand key concepts and values of open business models and responsible research and innovation
- know how to plan your innovation activities
- be able to use Creative Commons licenses in business
- understand new technology transfer policies with the ethos of Open Science
- earn how to get things to market faster
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You have likely heard people using the term 'FAIR' data a lot recently and might wonder what exactly is meant by this term. FAIR data are those that are Findable, Accessible, Interoperable and Reusable. Sounds simple enough, but what do each of these terms mean in a practical sense and how can you tell if your own research data is FAIR? This short course will:
- introduce you to the key terms and explain what they mean in a practical sense
- tell you how data management planning can help to make data FAIR from the very start of research projects
- show you how you can use freely available tools to help assess the FAIRness of data
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In higher education and research, the topics of open science and research data management have gained interest. This module stimulates the use of open research data in teaching, thus furthering the open science movement.
With the help of the teacher community, the module offers inspiring resources, such as good practices and examples of lesson plans and learning activities. It also provides practical information on how to use open data in teaching and indirectly encourages the acquisition of research data management literacy among students.
On completion of this module, as a teacher, you should be able to:
- explain the benefits of open data in teaching
- find new ideas for activities by learning from existing practices
- encourage active learning using hands-on activities
- help students become aware of open science and increase their data literacy
- help students use open resources combined with disciplinary theories and models
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