Open Science summer school organised by Cyprus Institute.
The project NI4OS-Europe - National Initiative for Open Science in Europe, actively participates in the establishment of the European Open Science Cloud (EOSC), which seeks to ensure an easy and seamless access to electronic infrastructures, services and dat for the research community. As part of this project, which involves 22 organizations from 15 EU member states and associated countries from Southeast Europe, a catalog of digital services to be included in the EOSC portfolio has been established. Through a series of short presentations, participants will learn about selected services developed in Serbia and the partner countries.
The training is jointly organized by the University of Belgrade Computer Centre and the Institute of Physics. All presentations are in Serbian, and the training will be organized on Zoom.
NanoCrystal is a novel web-based crystallographic tool that creates nanoparticle coordinates from any material crystal structure.
- Trainer: Zoe Cournia
EOSC and FAIR essential information in multiple languages
National end-users training event in North Macedonia organized by UKIM
Freely available courses on Open Science from Open Science MOOC.
- why open science is an issue that you can't afford to ignore
- how to go about making your own research more open
- what funders expect to see about open access and data sharing when applying for new grants
- how to progress your career through practicing open science
For a citable version or to use this course offline, please refer to the print version which is available from Zenodo.This course has been imported from the FOSTER project.
Practical steps toward making research more open. 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.
- practical implications of taking a more open approach to research
- meet expectations relating to openness from funders, publishers and peers
- reap the benefits of working openly
- guiding principles to follow when building openness in to your research workflow
- useful tools and resources to help you embed Open Science into work research practices
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.
- which data can be open and which need to be protected
- how to go about writing a data management plan
- understand the FAIR principles
- select which data to keep and find an appropriate repository for them
- tips on how to get maximum impact from research data
For a citable version or to use this course offline, please refer to the print version which is available from Zenodo.The course has been imported from the FOSTER project.
Introduction to Open Source Software (OSS) management and workflow as an emerging but critical component of Open Science. The role of software sharing and sustainability in reproducibility, trust and longevity. 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. Useful resources and tools for sharing and exposing code and workflows.
- roles that open source software and open workflows play in supporting Open Science
- how Open Science can support reproducibility
- different stakeholders' needs when it comes to software and workflows
- useful tools and resources to help you get started with using OSS and open workflows
The focus is on data protection in particular and ethics more generally. Understand the basic principles of data protection and introduces techniques for implementing data protection in the research processes.
- what personal data are and how to protect them
- what to consider when developing consent forms
- how to store data securely
- how to anonymise data
Open Access (OA) publishing in the context of Open Science:
- publish work openly and be aware of the advantages
- find an OA publisher for the research
- find a suitable repository to provide OA and archive work
- publish OA monographs
- funders' expectations and policies on OA
- secure funding for Article Processing Charges (APCs) where applicable
Introduction to open peer review (OPR), an emerging practice which is gaining momentum as part of Open Science.
- what OPR means and how it supports Open Science
- OPR workflows and which aspects of the review process can be conducted openly
- how to write a constructive and responsible open peer review
- useful tools and services that can support you putting OPR into practice
For a citable version or to use this course offline, please refer to the print version which is available from Zenodo.
Understand open business models and responsible research and innovation (RRI) and how these can foster innovation.
- understand key concepts and values of open business models and 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
- learn how to get things to market faster
Licensing research outputs is an important part of practicing Open Science.
- 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
How to go about assessing the FAIRness of research data using freely accessible tools and resources.
- key terms and explain what they mean in a practical sense
- how data management planning can be used to make data FAIR from the very start of research projects
- how to use freely available tools to help assess the FAIRness of data