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Open and accessible data – a recipe for research success?

Welcome to a popular science lecture and panel discussion about open data. The discussion is held during the Nobel Calling week.

Time: Thu 2023-10-05 12.15 - 13.00

Location: Sydöstra galleriet, KTH Biblioteket & Zoom

Language: English

Participating: J. Raghothama, S. Meijer, G. Nilsonne, W. Usher, S. Höhler, R. Lönneborg

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See the recorded video from the panel discussion

Welcome to join this panel discussion via Zoom or live in the library !

Open and accessible research data has been in the spotlight in recent years, notably in connection with the Covid-19 pandemic, where a vaccine could be developed at record speed thanks to it. But what does it mean for research to be open and accessible to everyone?

In this panel discussion featuring researchers from KTH and Karolinska Institutet we may begin to uncover an answer by delving into the principles surrounding FAIR data*.

It is not uncommon for researchers to build upon each other's discoveries. A Nobel Prize is often awarded to multiple researchers, where discoveries have contributed in various ways to a collective breakthrough that holds great importance for the world. If researchers shared data even earlier in the process, what could it entail? Could it assist with the reproducibility crisis? Might it lead to more novel research and Nobel laureates with diverse backgrounds?

In connection with the Nobel Calling week, we would like to add a little extra sparkle by treating the first 40 people to vegan wraps and non-alcoholic beverages!

No registration necessary, just show up in the library or enter Zoom at the appointed time. 

Participants in the panel discussion:

* FAIR is an acronym for Findable, Accessible, Interoperable, and Reusable. The FAIR data principles state that it should be possible to find research data, there should be information about how to gain access to them, they should be compatible with other data, and possible to reuse. The FAIR data principles are an integral part of the work within open science, and describe some of the most central guidelines for good data management and open access to research data.

Read more about FAIR and research data