Bringing Open Source to the Global Lab Bench - recording of seminar by Julieta Arancio

Hi All

Open Bioeconomy Lab hosted @jarancio in Cambridge recently and she gave a great seminar on “Bringing Open Source to the Global Lab Bench” - check it out!

Bringing Open Source to the Global Lab Bench - Dr Julieta Arancio

Recording from a talk at the University of Cambridge on 20 July 2022 by Dr Julieta Arancio from the Center for Science, Technology & Society, Drexel University / University of Bath.

Abstract
Experimental science demands instruments that can be quickly adapted to ever-changing research scenarios. But what happens when you find yourself in front of a black box you cannot even learn about? Can we trust data without trusting its source? Could open science provide an alternative? In this talk I will present findings from my research with the Gathering for Open Science Hardware (GOSH) community. We will discuss the implications that closed-source instruments have for knowledge production, how they affect researchers worldwide differently, and what people are doing towards a different future for science.

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really interesting,

loved the challenges slide.
did not realise OH was in the unesco recommendation…

question: in the talk @jarancio says OH is “quite new” and therefore not so easy to include in Open science policies. I am not that sure, I think open hardware is as old as open data(?), but it is much more difficult to define, it is much more complex to reuse, and ask much more time to document. The benefit over cost ratio for the researcher is not that good. It also does not touch all disciplines.

For my own experience as a researcher, I found normal to share my code and data, but tried to avoid at a maximum any engineering work and sharing of any description of that work. The building of my hardware has never been something I considered part of the research, I was also never trained to do it…

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Hey @Juliencolomb thanks for the comments :slight_smile:

question: in the talk @jarancio says OH is “quite new” and therefore not so easy to include in Open science policies.

This is really interesting, because I think it is about labels, agreements and building a movement. If you think of the practice of sharing the designs of science instruments then yes! It’s really old. Even in this community most people were doing open hardware before it was even named as “open science hardware”, calling it open labware, open science instruments and other names.

So the practice has been there for a long time but the concept the community generated consensus around is quite recent (even the OSHWA definition is from 2010 but GOSH one is from 2016). And that work does make a huge difference in terms of changing the system/policies. What I see from my own research is that the organising, mobilisation of resources and narratives created around “open science hardware” wouldn’t have been this successful (e.g. make it into the UNESCO recommendation in less than 5 years) without the earlier wins of the open data and access movements. And when you look at the policy discussion, which is led by open access to data and publications, effectively most people don’t understand why open hardware is there.

I am not that sure, I think open hardware is as old as open data(?), but it is much more difficult to define, it is much more complex to reuse, and ask much more time to document. The benefit over cost ratio for the researcher is not that good. It also does not touch all disciplines.

Agree with these challenges but I don’t think the mechanics of implementing open science hardware are the only reason why it’s difficult for it to get into policy. I think there are other more fundamental misalignments. One being that hardware forces you to consider the outside world/context for real (such as supply chains) and that’s hard for policies that often consider science as monolithic. Another misalignment is that open hardware forces you to consider instruments are also science. And this is far from science policy today, for which hardware is not even a variable. Some hints of this can be found in the way universities treat e.g. lab technicians (as an example of people working with instruments), or how in some fields working with instruments is less sexy in terms of career than theoretical research.

Anyway I wrote too much but happy to keep discussing!

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