This course aims to teach the following topics:
- What is Open Science?
- Open Science Taxonomy
- Open Access vs Open Research
- Creative Commons License
- Repositories and Self-archiving
- Open access publishing
- Types of Open Access
Available courses
This course aims to teach the following topics:
- Privacy and Data Protection;
- Data Governance and Management
- Fairness, Accountability, and Transparency of Algorithmic Systems
This course aims to teach the following topics:
- Semantic technologies and principles
- RDF & Ontologies
- Linked Open Data
- RDF Triple stores & SPARQ
- Versioning RDF datasets
Open Innovation is about involving far researchers, entrepreneurs, users, governments and civil society.
Open Science means promoting the highest standards of research integrity. more actors in the innovation process, from open access to scientific data and publications
Being open to the World means enabling Europe to be relevant and competitive by engaging more in scientific diplomacy and global scientific collaboration. “Europe is a global leader in science, and this should translate into a leading voice in global debates.”
This course aims to teach the follwing topics:
- Benefits and challenges of sharing research data
- How to protect the confidentiality
- How data ownership can affect data sharing
- Different types of access restrictions
- How to enable data sharing through the application of a standard license
This course aims to teach the following topics:
- Strategies for organizing research data such as versioning, file naming conventions and data file formatting and transformations
- Why documenting data and data citation are important.
- Issues involved in storing, securing, and backing up research data
This course aims to teach the following concepts:
- Components of good DMP
- DMP policies of several funding agencies
- Information on data management planning tools.
The course aims to teach the following topics:
- Research data in an array of contexts
- Data management concepts: 1.metadata; 2.research data lifecycle.
- Concept of data management: 1. identify the roles and responsibilities of key stakeholders; 2. examine various data management tasks throughout the research data lifecycle.
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