Journal:Haves and have nots must find a better way: The case for open scientific hardware

From LIMSWiki
Jump to navigationJump to search
Full article title Haves and have nots must find a better way: The case for open scientific hardware
Journal PLoS Biology
Author(s) Chagas, André Maia
Author affiliation(s) University of Tübingen, TReND in Africa, University of Sussex
Primary contact Email: a dor maia dash chagas at sussex dot ac dot uk
Year published 2018
Volume and issue 16(9)
Page(s) e3000014
DOI 10.1371/journal.pbio.3000014
ISSN 1545-7885
Distribution license Creative Commons Attribution 4.0 International
Download (PDF)


Many efforts are making science more open and accessible; they are mostly concentrated on issues that appear before and after experiments are performed: open access journals, open databases, and many other tools to increase reproducibility of science and access to information. However, these initiatives do not promote access to scientific equipment necessary for experiments. Mostly due to monetary constraints, equipment availability has always been uneven around the globe, affecting predominantly low-income countries and institutions. Here, a case is made for the use of free open-source hardware in research and education, including countries and institutions where funds were never the biggest problem.


In 2013, eLife senior editor Eve Marder[1] expressed concerns about the increasing costs of equipment necessary to do state-of-the-art research in the field of biology and the decreasing amount of funding available to be shared between an ever-growing number of labs and researchers. Even though the funding situation in the United States has improved since 2013, a closer look shows that the investments accumulated an inflation of 9% in the period between 2012 and 2017[2] and a budget increase of 4.5% and 6% for the National Institutes of Heath and National Science Foundation, respectively[3][4], while the Environmental Protection Agency has had a cut of 4.5% in the same period.[5] The concerns raised by this situation have been expressed for quite some time in many places of the world, where lower investment (as a proportion of gross domestic product [GDP]) in science and education makes research conditions suboptimal and access to bleeding edge technology and tools difficult. Now, in times of shrinking funding, however, this difficulty is being felt by researchers in places earlier considered safe havens of science. One of the fears Professor Marder expressed is that we might return to the “old days,” when only a privileged few men were able to do research.

A major reason for high prices in scientific equipment is related to the way innovation, technological development, and new knowledge generated inside universities and research institutes are introduced to the world: to make them commercially interesting and to allow their development outside academia, they are protected using legal mechanisms such as patents and/or copyrights, which are then licensed/sold to companies. Although this system enables universities and companies to work in collaboration and leverage each others’ strengths, it ends up locking away research results funded with public money. Not only is this morally debatable, but it also does the following:

  1. increases costs in product development, as each patent normally requires the involvement of specialized lawyers and has several fees that can easily sum up to considerable amounts (between U.S. $10,000 and $30,000 in 2018[6]);
  2. slows down innovation cycles, as sometimes companies owning patents do not invest in further developing them into commercial applications, delaying derivative innovations that would rise from its implementation.[7] Kodak for example patented[8] the idea for a charge-coupled device (CCD) digital camera (the same as today’s digital cameras) in 1978, but the first commercial versions were only released by Fuji in 1989[9];
  3. creates instruments/technologies that are “black boxes” since consumers are not allowed to open them up (for repair, maintenance, or simple curiosity), which, in the case of scientific equipment, can lead to an incomplete understanding of how complex instruments work as well as their capabilities and limitations; and
  4. results in equipment being used in suboptimal conditions or thrown away instead of being repaired, especially in countries where manufacturing companies do not offer appropriate customer support.[10]

An alternative to this production model exists, and it relies on a free distribution philosophy, in which code and design blueprints are shared freely so that anyone can study, build, modify, and improve existing projects. This philosophy is strongly present in the software industry, more known as open source, in which several companies act as service providers for their products instead of leveraging scarcity and intellectual property.[11] One example of such a company is Red Hat, which was founded in 1993 and has, as of 2015, reported over two billion dollars in revenue yearly for the last three years.[12]

As a consequence, researchers can now use freely available software for most of their work-related tasks (e.g., office suites, statistics, or data analysis packages), which in turn helps reduce research costs and frees resources for other expenses (as well as improves research quality and scientific outputs[13]—a more detailed description of the benefits of using freely available initiatives can be found in the following paragraphs). For Eve Marder’s main concern—the lack of funds to buy expensive equipment—a solution was still lacking. While this is worrisome, the increasing affordability of electronic systems to the general public should provide relief to the problem, as they can be used to assemble tools in an open source way in which everyone is free to use and improve designs based on their specific needs. The smartphone, for example, carries a powerful central processing unit (CPU), camera, microphone, and an array of sensors, which makes the ever-present device an excellent tool for recording, analyzing, and visualizing data.[14] One popular application is smartphone-based microscopes, in which a glass bead or other inexpensive plastic lens (normally found inside a laser pointer) can be placed in front of the smartphone camera for very large magnifications (see Table 1 for examples). A brief online search for “phone microscope” will guide the reader to a wealth of similar projects. The quality of such simple microscopes allows users, among other things, to image blood samples for diagnostics[15], with costs in the range of U.S. $5 to $20 (assuming users already have a smartphone with a camera).

Tab1 Chagas PLOSBio2018 16-9.png

Table 1.

In contrast to this, the initial cost for a “scientific-grade” optical microscope is in the range of thousands of dollars, with prices rising steeply for more complex designs, severely constraining access to such a fundamental tool. As such devices are core to scientific investigations, there have been several open-source models beyond just the “basic smartphone hack”; some examples can be found in Table 1. They have different capabilities and different levels of complexity, but all of these freely distributed models have two key features in common: (i) they are produced with “off-the-shelf” components, which are mostly cheap and easy to get, and (ii) their designs and bill of materials are available online, allowing anyone to build as well as customize/improve them, depending on specific needs and material availability.[16] These features are nothing more than the translation of the open-source software philosophy to the world of hardware (a more rigorous definition can be found on the Open Source Hardware Association page[17]). Like in software, the adoption of this philosophy in research and education has deeper implications, which have been debated in reference to specific fields (analytical chemistry[18], engineering[19], life sciences[20], and nanotechnology[21]), as well as concerning research in general.[22][23] The common implications of adopting free open-source hardware (FOSH) are summarized below:

  1. It allows more people to participate in the scientific endeavor, in turn enabling research to be done outside academia, enabling people to exercise their curiosity and better understand the world around them. Public Lab[24] and Safecast[25] are two good examples of nonprofit organizations that use FOSH to empower global communities to gather data about environmental variables and to understand the impact of human activity on the environment, health, and quality of life.
  2. It allows for a better understanding of the tools themselves because the available blueprints can be studied, leading to more informed decisions by users concerning the feasibility of experiments and the results they can expect. This, in turn, can also lead to better reproducibility, as researchers can calibrate their devices according to the blueprints more often and make sure they are performing consistently at high standards, avoiding discrepancies in experimental outcomes.
  3. In long-term projects lasting years or even decades, laboratories are less vulnerable to supply problems. If a company producing a certain device decides to discontinue its production or if the company goes out of business, researchers are left orphaned without means to repair or replace said device in the case of malfunction. If all the build plans are open, scientists can reproduce/repair it themselves or find other companies to produce them on demand. A concrete example[26] of this issue is provided by the European Organization for Nuclear Research (CERN) in which a specific hardware license[27] and several businesses protocols were created to ensure that hardware developed and sold to the project would have to comply with this license. This has enabled close collaborations in tool development between CERN and the hardware industry (as CERN employees could freely apply their expertise, both as end users and as engineers) and made the project robust to fluctuations in the market, since the necessary tools could be sourced from many suppliers.
  4. In a FOSH-rich environment, information about material costs are easy to obtain and building plans are publicly available. Therefore, consumers are better equipped to decide whether the price being charged for a certain equipment is reasonable and to decide which route to take; they can invest time and effort in building, calibrating, and repairing their own tools (therefore saving money), or they can invest money to hire a company to do it for them (saving time and effort). In this new setting, saving potentials are quite large[28], without excluding companies from operating and offering valuable services for research and education.
  5. The lower price tag on FOSH enables scientists in regions that are normally constrained by lack of funds to address scientific problems previously outside their reach. It fosters the discovery of untapped talent and paves the way for inside–out development, rather than relying on external aid and humanitarian assistance, a model that has had little success.[29] TReND in Africa[30], a volunteer-run nongovernmental organization, is leveraging this idea to train researchers in Africa on basic electronics and 3D printing as tools to develop labware and to involve academics in the global “maker movement.”[31]
  6. FOSH is also an excellent tool for education. As curious people learn how to build their own equipment, they are “forced” to learn about physics, electronics, and biology (see Table 1 for examples), creating new teaching possibilities for both schools and universities. Content can be taught in a “hands-on approach” by which students are challenged with a scientific question and try to solve it by thinking about what kind of experiments will be needed, building the instruments, gathering data, and drawing conclusions from them.

More examples of scientific equipment produced under the open source paradigm can be found for PCR machines, electrophysiology systems, supercomputers, prostheses, centrifuges, optics, spectrometers, diving robots, and even electron microscopes (Table 1 and Fig. 1). The list is not exhaustive, and new tools are added to online repositories and dedicated journals almost daily (Table 1).

Fig1 Chagas PLOSBio2018 16-9.png

Fig. 1. Open-source hardware for research and education. A. Time-sorting pitfall trap and temperature logger.[32] B. “Smart” tube holder for real-time sample monitoring.[33] C. Pipetting robot for toxicological assays.[34] D. Low-cost multifluorescense system.[35]

In this modern version of the “do-it-yourself” (DIY) tradition, people are developing tools with bits, bytes, resistors, and integrated circuits. They are still learning what works and what doesn’t, becoming ever more interdisciplinary, interconnected, and increasing the complexity of their designs. Taking advantage of the internet, project repositories and information hubs are coming alive, breaking down the ivory tower, as scientists, makers, DIYers, and hobbyists interact on the same level while making suggestions on, contributing to, and improving each others’ projects in a much richer peer review system, done by many, instead of just two or three pairs of eyes, and in an iterative manner. A prime example is the community growing around the Gathering for Open Scientific Hardware[36], set to have its third meeting from October 10–13, 2018, bringing together ideas from different fields and creating collaborative, inclusive documentation, a manifesto[37], a roadmap (for an ambitious but noble destination[38]) to make open science hardware ubiquitous by 2025 and more importantly, a truly global community spirit[39], in which interdisciplinary and international events have been organized by the community members, among them the African Open Source Hardware Summit (AfricaOSH[40]), project Vuela![41], and workshops on Open Source Laboratory equipment.[42]

In 2013, Professor Marder was concerned by the number of times the phrase “the haves and the have nots” was being used in academia and the divide it represented. Even if the problem was solved by unlimited funding, it did not address the fact that, in the current system, institutions and labs that belong to the group that “has” are still in a system held hostage by their own tools. In order to solve this issue, we don’t necessarily need more money but rather need to reassess our relationship to knowledge and technology, how it determines our role in society, and how we want to spend grant money entrusted to us by the people. By making our tools and knowledge truly free, “haves and have nots” will not only erase the divide but also will actually move together in a better way.


AfricaOSH: African Open Source Hardware Summit

CCD: charge-coupled device

CERN: European Organization for Nuclear Research

CPU: central processing unit

DIY: do-it-yourself

FOSH: free open-source hardware

GDP: gross domestic product



AMC was supported by the Levelhulme Trust (Sir Philipp Leverhulme Prize 2017 for biological sciences awarded to Tom Baden). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests

I have read the journal’s policy and the author of this manuscript has the following competing interests: Editor of the Open Source Toolkit Channel for PLOS.


  1. Marder, E. (2013). "The haves and the have nots". eLife 2: e01515. doi:10.7554/eLife.01515. PMC PMC3832882. PMID 24252880. 
  2. "CPI Inflation Calculator". Databases, Tables & Calculators by Subject. U.S. Bureau of Labor Statistics. Retrieved 07 September 2018. 
  3. "Budget". About NIMH. National Institutes of Health. Retrieved 07 September 2018. 
  4. "Budget and Performance". About NSF. National Science Foundation. Retrieved 07 September 2018. 
  5. "EPA's Budget and Spending". Planning Budget Results. Environmental Protection Agency. Retrieved 07 September 2018. 
  6. "USPTO Fee Schedule". Learning and Resources. United States Patent and Trademark Office. Retrieved 22 August 2018. 
  7. Baker, D.; Jayadev, A.; Stiglitz, J. (July 2017). "Innovation, Intellectual Property, and Development: A Better Set of Approaches for the 21st Century". Center for Economic and Policy Research. Retrieved 17 August 2018. 
  8. Lloyd, G.A.; Sasson, S.J. (26 December 1978). "United States Patent: 4131919—Electronic still camera". Patent Full Text Databases. United States Patent and Trademark Office. 
  9. "Innovation History". FUJIFILM Corporation. Retrieved 22 August 2018. 
  10. Perry, L.; Malkin, R. (2011). "Effectiveness of medical equipment donations to improve health systems: how much medical equipment is broken in the developing world?". Medical and Biological Engineering and Computing 49 (7): 719–22. doi:10.1007/s11517-011-0786-3. PMID 21597999. 
  11. Raymond, E.S. (2000). "The Cathedral and the Bazaar". Internet Archive. Thyrsus Enterprises. 
  12. "Financial Information". Investor Relations. Red Hat, Inc. Retrieved 20 August 2018. 
  13. Goble, C. (2014). "Better Software, Better Research". IEEE Internet Computing 18 (5): 4–8. doi:10.1109/MIC.2014.88. 
  14. Malykhina, E. (5 November 2013). "8 Apps That Turn Citizens into Scientists". Scientific American. Retrieved 17 August 2018. 
  15. Switz, N.A.; D'Ambrosio, M.V.; Fletcher, D.A. (2014). "Low-cost mobile phone microscopy with a reversed mobile phone camera lens". PLoS One 9 (5): e95330. doi:10.1371/journal.pone.0095330. PMC PMC4031072. PMID 24854188. 
  16. Bonvoisin, J.; Mies, R.; Boujut, J.-F.; Stark, R. (2017). "What is the “Source” of Open Source Hardware?". Journal of Open Hardware 1 (1): 5. doi:10.5334/joh.7. 
  17. "Definition (English)". Open Source Hardware Association. 26 May 2012. Retrieved 17 August 2018. 
  18. Dryden, M.D.M.; Fobel, R.; Fobel, C. et al. (2017). "Upon the Shoulders of Giants: Open-Source Hardware and Software in Analytical Chemistry". Analytical Chemistry 89 (8): 4330–4338. doi:10.1021/acs.analchem.7b00485. PMID 28379683. 
  19. Berg, D.R.; Niemeyer, K.E. (2018). "The case for openness in engineering research". F1000Research 7: 501. doi:10.12688/f1000research.14593.2. 
  20. Baden, T.; Chagas, A.M.; Gage, G.J. et al. (2015). "Open Labware: 3-D printing your own lab equipment". PLoS Biology 13 (3): e1002086. doi:10.1371/journal.pbio.1002086. PMC PMC4368627. PMID 25794301. 
  21. Pearce, J.M. (2013). "Open-source nanotechnology: Solutions to a modern intellectual property tragedy". nanotoday 8 (4): 339–41. doi:10.1016/j.nantod.2013.04.001. 
  22. Pearce, J.M. (2012). "Materials science. Building research equipment with free, open-source hardware". Science 337 (6100): 1303–4. doi:10.1126/science.1228183. PMID 22984059. 
  23. Kera, D. (2018). "Science Artisans and Open Science Hardware". Bulletin of Science, Technology & Society 37 (2): 97-111. doi:10.1177/0270467618774978. 
  24. "Public Lab". Public Laboratory for Open Technology and Science. Retrieved 20 August 2018. 
  25. "Safecast". Shuttleworth Foundation. Retrieved 20 August 2018. 
  26. "CERN launches Open Hardware initiative". European Organization for Nuclear Research. 
  27. "CERN Open Hardware License". Open Hardware Repository. Retrieved 20 August 2018. 
  28. Pearce, J.M. (2015). "Return on investment for open source scientific hardware development". Science and Public Policy 43 (2): 192–5. doi:10.1093/scipol/scv034. 
  29. Moyo, D. (2011). Dead Aid: Why aid is not working and how there is another way for Africa. Penguin. ISBN 9780241959961. 
  30. "TReND - Home". TReND in Africa. Retrieved 04 March 2016. 
  31. Quinn, A.; Paffhausen, B.; Chagas, A. (2017). "Implementation of a Novel Educational Course to Teach 3D Printing, Circuit Design, and Programming to PhD Candidates in Nigeria". SocArXiv. doi:10.31235/ 
  32. McMunn, M.S. (2017). "A time-sorting pitfall trap and temperature datalogger for the sampling of surface-active arthropods". HardwareX 1 (4): 38–45. doi:10.1016/j.ohx.2017.02.001. 
  33. Hoang, T.; Moskwa, N.; Halvorsen, K. (2018). "A 'smart' tube holder enables real-time sample monitoring in a standard lab centrifuge". PLoS One 13 (4): e0195907. doi:10.1371/journal.pone.0195907. PMC PMC5901991. PMID 29659624. 
  34. Steffens, S.; Nüßer, L.; Seiler, T.B. et al. (2017). "A versatile and low-cost open source pipetting robot for automation of toxicological and ecotoxicological bioassays". PLoS One 12 (6): e0179636. doi:10.1371/journal.pone.0179636. PMC PMC5473567. PMID 28622373. 
  35. Nuñez, I.; Matute, T.; Herrera, R. et al. (2017). "Low cost and open source multi-fluorescence imaging system for teaching and research in biology and bioengineering". PLoS One 12 (11): e0187163. doi:10.1371/journal.pone.0187163. PMC PMC5687719. PMID 29140977. 
  36. Doesemagen, S.; Liboiron, M.; Molloy, J. (2017). "Gathering for Open Science Hardware 2016". Journal of Open Hardware 1 (1): 4. doi:10.5334/joh.5. 
  37. Liboiron, M.; Austic, G.. "GOSH Manifesto". Gathering for Open Science Hardware. Retrieved 20 August 2018. 
  38. GOSH Community. "Global Open Science Hardware Roadmap". Gathering for Open Science Hardware. Retrieved 20 August 2018. 
  39. Liboiron, M.; Austic, G.. "GOSH Community Forum". Gathering for Open Science Hardware. Retrieved 20 August 2018. 
  40. "Africa Open Science and Hardware". AfricaOSH. Retrieved 20 August 2018. 
  41. Bernaldo, P.; Irujo, G.P.; Pérez, A. et al. (13 December 2017). "¡Vuela! - Open science with drones - Ciencia libre con drones". OSF. Center for Open Science. 
  42. Arancio, J. (16 April 2018). "Open science hardware across the Andes". Gathering for Open Science Hardware - Blog. Retrieved 20 August 2018. 


This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added.