Published September 13, 2023 | Version v1
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Open Science Principles and Research Data

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This is a presentation I gave at the University of Maribor Open Science Summer School 2023.

The lecture was meant for a very diverse class of students (from Bachelor to PhD degrees), and is a broad introduction to open science principles and open and FAIR research data. The lecture is structured in 4 parts:

  1. A common understanding of open science: this section tries to highlight the need for open research practices, sketching out a brief history of open science. It presents the five schools of thought, and then proceeds to demonstrate that, while it is key to achieve a common understanding of open science, it's also crucial to respect diversity of research disciplines, traditions of communities, languages.

  2. Restoring the ethos of science: this section wants to show the students that while open research practices have been designed to allow a more transparent and efficient research process, there is to them much more than what meets the eye. I talk about the normative structure described by Merton in 1942, and how a completely different set of values have polluted research with a lot of 'bad things': the serial crisis, the reproducibility crisis, the rhetoric of excellence, the cherry-picking of results (to please some commercial publishers...). Open science can help us find back those values highlighted by Merton, while developing new norms that align with these values.

  3. Open Access practices: the last two sections briefly touch upon open access and open and FAIR data. Starting from the Budapest Open Access Initiative, this section describes the need to open up scientific literature, and then proceeds to describe the different forms of Open Access: green, gold, hybrid, bronze.

  4. Open & FAIR research data: the very last bit of this lecture introduces the concepts of reproducibility, data as research objects, data discovery and re-use, and the FAIR principles. It also stresses the difference between OPEN and FAIR, and explains the 5 star open data model.

The HMTL document of this lecture is published on the web at the following link.


Open science principles and research data.pdf

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