This category contains Open Science Courses

Introduction to Open Science and Open Access Publishing

At a glance

Welcome to the EELISA e-learning course on Open Science!

This introductory e-learning course covers the core components of Open Science, open access, open research, repositories, and creative commons licenses, highlighting its role in enhancing collaboration, transparency, and inclusivity in scientific processes. Participants will learn about the principles, practices, and impacts of Open Science on both the scientific community and society.

Course description

Open Science represents a transformative approach designed to revolutionize the accessibility, availability, and reusability of scientific knowledge. This course offers an in-depth exploration of the core components of Open Science, emphasizing its role in promoting collaboration, transparency, and inclusivity within the scientific process.

Structured into seven comprehensive units and a final assessment, this course will guide participants through the foundational principles of Open Science, the practices that support scientific sharing, and the profound impact these practices have on both the scientific community and society as a whole.


Reproducible Research and Data Analysis

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


Open Research Data and Materials

Research data are defined as factual records (numbers, texts, images and sounds), which are used as principal sources for scientific research and which are often recognized by the scientific community as being necessary to validate research results ( Organization for Economic Cooperation and Development). Putting your code and data online can be very revealing and intimidating, and it is part of the human condition to be nervous of being judged by others. Although there is no law governing the communication of reproducible research – unless you commit explicit fraud in your work – sharing errors that you find in your work is heavily disincentivised. 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.