Open Science is increasingly referred to as the “Science for the Future” and the “Future of Science”. By making science more accessible - via Open Access publishing and proper Research Data Management - Open Science makes the scientific process more inclusive and the outputs of science more readily available and relevant for society. Consequently, more and more funding bodies, governments, research institutions and other agencies have emphasized the value and importance of open science practices and introduced policies on open access publications and data management and sharing. Open Access (OA) aims at providing free of charge and unhindered access to research and its publications without copyright restrictions. Research Data Management (RDM) is a term that describes the organization, storage, preservation, and sharing of data collected and used in a research project. It involves the everyday management of research data during the lifetime of a research project. It also involves decisions about how data will be preserved and shared once the project is completed, for example depositing the data in a repository for long-term archiving and access. Good RDM and OA are not only crucial for reproducible and robust scientific research but are key requirements for research grants and journal publications. Completing this cycle of lessons will allow you, as a PhD candidate, to learn about • The importance of RDM in the general context as well as for your own work • How to write data management plans (DMP) for grant proposals as well as for your own research • Managing privacy, consent, confidentiality and IP issues with respect to to data management • RDM compliance requirements for grant proposals such as Horizon Europe • The application of Open Access principles to scholarly publishing; understanding copyright and licenses in relation to publishing agreements; using POLITO tools that support Open Access publishing; how to find suitable OA journals/platforms and how to bypass predatory journals.

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Lesson 1: Introduction to RDM (3 hrs) • Setting the context: Why RDM • Secure backup, storage using PoliTo infrastructure, • Metadata standards, how to make their research outputs (data, models, code) citable • File formats, data organisation, file naming conventions, version control and house-keeping • Digital preservations, discipline specific data repositories, licenses: Exercise to deposit data sets. Lesson 2: RDM for personal data and commercially sensitive data (3 hrs) • What does GDPR mean for Research Data: the essentials • Legal bases for using Personal data in research: Beyond just consent forms Safe storage, safe settings, safe people, safe outputs, safe projects • Data encryption and anonymisation tools for quantitative and qualitative data • Working with commercially sensitive data: Considerations • Managing IP and tech transfer while following the FAIR data road Lesson 3: Publishing research outputs (3hrs) • Principles of Open Access publishing • Basics about copyright and licenses in relation to author rights and user permissions. • Institutional repository PORTO@IRIS and supporting tools provided by the University • Things to know before publishing in an Open Access journal • What you need to know about Plan S Lesson 4: Writing Data Management Plans for Grant Proposals (3 hrs) • Introduction to how to make your data FAIR: step-by-step • Horizon Europe Open Science requirements • Data Management Plans and DMP Online • Writing a DMP for a mock research project for Horizon Europe • Increasing impact with RDM tools: e.g. Open Knowledge maps, Orcid etc. Lesson 5: Final presentation and assessment (3 hrs) • DMP peer review • Discussion and plenary: DMP • Feedback session and final quiz covering the concepts of the course

In presenza

Test a risposta multipla - Presentazione report scritto

P.D.2-2 - Marzo

The course will be taken on October