Global technology access in biolabs -- from DIY trend to an open source transformation
Tobias Wenzel

TL;DR
This paper explores how open hardware and DIY technologies are transforming access to advanced scientific tools in biolabs, especially in resource-constrained environments, by enabling local production, knowledge sharing, and open collaboration.
Contribution
It demonstrates the widespread adoption of open hardware in biolabs, highlighting its role in increasing technological access through open sharing, digital fabrication, and detailed documentation.
Findings
DIY technologies are prevalent in countries with lower science funding.
Open hardware enables local production and knowledge transfer.
Open sharing and digital fabrication drive technology adoption in biolabs.
Abstract
This article illustrates how open hardware solutions are implemented by researchers as a strategy to access technology for cutting-edge research. Specifically, it is discussed what kind of open technologies are most enabling in scientific environments characterized by economic and infrastructural constraints. It is demonstrated that do-it-yourself (DIY) technologies are already wide spread, in particular in countries with lower science funding, which in turn is the basis for the development of open technologies. Beyond financial accessibility, open hardware can be transformational to the technology access of laboratories through advantages in local production and direct knowledge transfer. Central drivers of the adoption of appropriate technologies in biolabs globally are open sharing, digital fabrication, local production, standard parts use, and detailed documentation.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsBiomedical and Engineering Education · Scientific Computing and Data Management · Research Data Management Practices
