Open Labware: 3-D Printing Your Own Lab Equipment

• Abstract
• A Culture of Sharing
• Quality Control and the Evolution of Open Labware Designs
• Online Resources for Learning and Problem Solving
• Application in a Resource-Challenged Context
• In-Depth Exposure during Multiday Training Events
• Motivating More High School Graduates to Pursue a Career in Science
• Policy Recommendations
• Supporting Information
• Acknowledgments
• References
• Reader Comments (0)
• Media Coverage (0)
• Figures

Abstract
The introduction of affordable, consumer-oriented 3-D printers is a milestone in the current “maker movement,” which has been heralded as the next industrial revolution. Combined with free and open sharing of detailed design blueprints and accessible development tools, rapid prototypes of complex products can now be assembled in one’s own garage—a game-changer reminiscent of the early days of personal computing. At the same time, 3-D printing has also allowed the scientific and engineering community to build the “little things” that help a lab get up and running much faster and easier than ever before.

Figures

Citation: Baden T, Chagas AM, Gage G, Marzullo T, Prieto-Godino LL, et al. (2015) Open Labware: 3-D Printing Your Own Lab Equipment. PLoS Biol 13(3): e1002086. doi:10.1371/journal.pbio.1002086

Copyright: © 2015 Baden et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Funding: This work was supported by the Deutsche Forschungsgemeinschaft (DFG) (Werner Reichardt Centre for Integrative Neuroscience Tübingen, EXC 307 to TE and TB; BA 5283/1-1 to TB) and the U.S. National Institutes of Mental Health Small Business Innovation Research grant #R44 MH093334 to GG and TM. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: Authors GG and TM are founders of Backyard Brains (www.backyardbrains.com), a company specializing in the design and distribution of Open Labware.

Abbreviations:: ABS, Acrylnitrile butadiene styrene; CNC, computer numerical control; DIY, Do It Yourself; EMG, Electromyogram; ERG, Electroretinogram; FOSSFA, Free Software and Open Source Foundation for Africa; GNU, “GNU is not Unix” (recursive acronym); GPIO, general-purpose input-output; IT, information technology; LED, Light Emitting Diode; NIH, National Institutes of Health; PCB, Printed Circuit Board; PLA, Polylactic acid; TReND, Teaching and Research in Natural Sciences for Development (in Africa); UV, Ultraviolet

Applications of 3-D printing technologies (Fig. 1A, Box 1) have become as diverse as the types of materials that can be used for printing. Replacement parts at the International Space Station may be printed in orbit from durable plastics or metals, while back on Earth the food industry is starting to explore the same basic technology to fold strings of chocolate into custom-shaped confectionary. Also, consumer-oriented laser-cutting technology makes it very easy to cut raw materials such as sheets of plywood, acrylic, or aluminum into complex shapes within seconds. The range of possibilities comes to light when those mechanical parts are combined with off-the-shelf electronics, low-cost microcontrollers like Arduino boards [1], and single-board computers such as a Beagleboard [2] or a Raspberry Pi [3]. After an initial investment of typically less than a thousand dollars (e.g., to set-up a 3-D printer), the only other materials needed to build virtually anything include a few hundred grams of plastic (approximately US$30/kg), cables, and basic electronic components [4,5].

Fig 1. Examples of open 3-D printed laboratory tools. A1, Components for laboratory tools, such as the base for a micromanipulator [18] shown here, can be rapidly prototyped using 3-D printing.
A2, The printed parts can be easily combined with an off-the-shelf continuous rotation servo-motor (bottom) to motorize the main axis. 
B1, A 3-D printable micropipette [8], designed in OpenSCAD [19], shown in full (left) and cross-section (right). 
B2, The pipette consists of the printed parts (blue), two biro fillings with the spring, an off-the-shelf piece of tubing to fit the tip, and one screw used as a spacer. 
B3, Assembly is complete with a laboratory glove or balloon spanned between the two main printed parts and sealed with tape to create an airtight bottom chamber continuous with the pipette tip. Accuracy is ±2–10 μl depending on printer precision, and total capacity of the system is easily adjusted using two variables listed in the source code, or accessed via the “Customizer” plugin on the thingiverse link [8]. See also the first table.

Box 1. Glossary

Open source
A collective license that defines terms of free availability and redistribution of published source material. Terms include free and unrestricted distribution, as well as full access to source code/blueprints/circuit board designs and derived works. For details, see http://opensource.org.

Maker movement

Technology-oriented extension of the traditional “Do-it-Yourself (DIY)” movement, typically denoting specific pursuits in electronics, CNC (computer numerical control) tools such as mills and laser cutters, as well as 3-D printing and related technologies.

3-D printing

Technology to generate three-dimensional objects from raw materials based on computer models. Most consumer-oriented 3-D printers print in plastic by locally melting a strand of raw material at the tip (“hot-end”) and “drawing” a 3-D object in layers. Plastic materials include Acrylnitrile butadiene styrene (ABS) and Polylactic acid (PLA). Many variations of 3-D printers exist, including those based on laser-polymerization or fusion of resins or powdered raw materials (e.g., metal or ceramic printers).

Arduino boards

Inexpensive and consumer-oriented microcontroller boards built around simple processors. These boards offer a variety of interfaces (serial ports, I2C and CAN bus, etc.), μs-timers, and multiple general-purpose input-output (GPIO) pins suitable for running simple, time-precise programs to control custom-built electronics.

Single board computers
Inexpensive single-board computers capable of running a mature operating system with graphical-user interface, such as Linux. Like microcontroller boards, they offer a variety of hardware interfaces and GPIO pins to control custom-built electronics.

It therefore comes as no surprise that these technologies are also routinely used by research scientists and, especially, educators aiming to customize existing lab equipment or even build sophisticated lab equipment from scratch for a mere fraction of what commercial alternatives cost [6]. Designs for such “Open Labware” include simple mechanical adaptors [7], micropipettes (Fig. 1B) [8], and an egg-whisk–based centrifuge [9] as well as more sophisticated equipment such as an extracellular amplifier for neurophysiological experiments [10], a thermocycler for PCR [11], or a two-photon microscope [12]. At the same time, conceptually related approaches are also being pursued in chemistry [13–15] and material sciences [16,17]. See also Table 1.

Table 1. Open Labware designs for a biology lab. doi:10.1371/journal.pbio.1002086.t001

A Culture of SharingMost makers share their designs under an open source license together with detailed assembly instructions in online repositories [20–22] such as the National Institutes of Health (NIH) 3-D print exchange [23] or in peer-reviewed journals [10,17,24–29]. As a result, anyone can freely use and modify them. This open culture, which has transformed the world of software engineering over the past decades, offers several advantages over traditional product design. First, designs are not only free, but are directly shaped by people who will actually use the final product. Second, building your own experimental equipment yields a much deeper understanding of the principles underlying its design and a better awareness of its limits. Third, manufacturing is immediate and local—thus empowering laboratories and schools located in difficult-to-reach places. Fourth, the open source movement is a global phenomenon, connecting people worldwide, often to recruit talented builders and coders from outside the traditional scientific establishment. Still, there are drawbacks. For example, a commercial solution may be preferred if the time and cost of in-house development exceeds the benefits of control and instrument knowledge. Nevertheless, and perhaps counter-intuitively, some open designs are published by commercial companies that offer the parts as well as the assembled product with technical support for a fee, while maintaining the source material online under an open source license. Consumers can more freely balance cost against time to build, while companies gain in customer relations and product feedback.

Quality Control and the Evolution of Open Labware Designs
The flagship of the open source movement, the operation system GNU/Linux [30], is perhaps the best example for the potential of open designs. First available in the 1990s, today it is one of the most widely used system on supercomputers, servers, and mobile phones (Android) and increases its share of home users every year. Critically, Linux is fully open source—anyone can freely access its entire source code, change it, and distribute modifications. Its success flows from the idea that “given enough eyeballs all bugs are shallow” [31]. In other words, a distributed network of collaborators helps to identify and rectify bugs in the system as they arise. Open Labware works the same way: release of a design sparks feedback and refinements from the community. Although Open Labware’s contributor base is still relatively small, feedback can nonetheless markedly improve product design and expand potential applications over time. For example, free online sharing of the designs for a manually controlled 3-D printed micromanipulator (Fig. 2A) [18] provided the starting point for a high-precision motorized version (Fig. 2B) [32]. Subsequently, and in combination with open designs for smartphone lens-adapters offering portable options for field-microscopy [33], both designs led to the “Raspberry Pi-scope” [34]—a self-standing histology microscope based on a Raspberry Pi, equipped with a high-resolution camera module, a low-cost acrylic lens, and the manipulator body to accurately position the sample (Fig. 2C). One next step in this evolution may be to add low-cost fluorescence capability through the addition of a ultraviolet light-emitting diode (UV-LED) and the appropriate filters, perhaps inspired by materials used in the less than US$1 fluorescence-capable Foldscope [24]. Without free-and-open sharing of the complete source materials at all stages of development, this evolution would not have been possible. With educators and researchers increasingly integrating Open Labware approaches into their projects, designs are expected to continuously improve and diversify.

Fig 2. Evolution of an Open Labware design.

A, A 3-D printable micromanipulator with a slanted Z-axis [18], here shown amidst commercial alternatives, initially served as the basis for a motorized version with “real” Z axis [32] (B). B1,2, the three axes are driven by continuous-rotation micro-servos, controlled by an Arduino fitted with a Joystick-shield and a 9V battery. B3, The motorized manipulator offers sufficient precision to target individual hairs on the head of a fruitfly (±5–20 μm during movements, depending on printer precision; <1 μm drift min-1 when stationary). Scale bar 1 mm. C1, The same manipulator build was then converted into a microscope-stage to permit accurate placement and focus of histology samples [34]. The optics are provided by an off-the-shelf, low-power acrylic lens positioned directly above a Raspberry Pi camera module [3]. C2, Image taken with the microscope, showing a slice of mouse brain (hippocampus) stained for cytochrome oxidase C. Scale bar 500 μm.

doi:10.1371/journal.pbio.1002086.g002

Online Resources for Learning and Problem Solving

Although most Open Labware designs are published with detailed assembly instructions aimed at the non-specialist, a basic understanding of concepts in physics, electronics, and computer programming is certainly helpful. Luckily, freely available online resources facilitate self-learning (Table 2). In addition, many makers hone their skills directly at the workbench, simply by attempting to recreate or modify existing designs. Expert community help can be rapidly found in online forums such as Stack Overflow [35], returning to the idea that many eyes lead to rapid problem-solving. In addition, online aggregators gather and summarize information on specific topics, serving as a hub for both information seekers and distributors. Some of them are curated in a centralized manner [36], while others follow the distributed wiki principle [37].

Table 2. Open resources for self-taught learning of programming, electronics, and basic physics. doi:10.1371/journal.pbio.1002086.t002

Application in a Resource-Challenged Context
If a commercial alternative is available, it is usually the compromise between time and money spent that determines whether to build or purchase equipment. While Open Labware designs may benefit any research or education setting [38], one obvious foothold for their possibilities lies in economically deprived schools and universities in the developing world. Here, the introduction of Open Labware may make the crucial difference between having some usable equipment to work with and having none at all. Several benefits of an open model come to light: low cost, local manufacture, and the possibility to customize according to local demands or availability of parts. In sub-Saharan Africa, only a few bases and organizations that offer training in “maker” skills or general promotion of open source principles operate. These include the Free Software and Open Source Foundation for Africa (FOSSFA [39]), Fundi bots [40], as well as a few physical spaces such as FabLabs [41] and Maker- [42] and Hackerspaces [43] scattered mostly around the major cities. In addition, companies selling easily transportable 3-D printers and supplies are rapidly establishing their foothold on the African continent, such that local sourcing of the required hardware is no longer an insurmountable obstacle. However, on the whole, Open Labware possibilities remain poorly established in this context, as attested in a survey taken by 89 biomedical researchers from 12 sub-Saharan African countries in August 2014 (Fig. 3). When asked about their software competency, most respondents indicated that while they are comfortable with “basic” IT usage (defined as using office packages or navigating the web), few were routine users of standard open analysis packages such as R [44], octave [45], or other Python [46] based packages, and programming skills were even less prevalent (Fig. 3A). Awareness and competency in the use of open hardware approaches were even less developed: over 90% of respondents (83/89) had never used 3-D printing or any form of single-board computers or microcontrollers (Fig. 3B).

Fig 3. Open Labware at universities in sub-Saharan Africa.

An online survey was taken by 89 biomedical researchers (MSc. to Professor) at universities in 12 different sub-Saharan African countries in August 2014. Researchers rated their own competency and awareness in aspects of software and hardware usage. A, Software competency rated on a scale of 1 (low) to 10 (high) in “basic usage such as navigating office software or the internet,” “usage of open analysis packages such as R [44], octave [45], or similar,” and “programming, e.g., using C++, python, or any other mainstream language.” B, Hardware awareness for possibilities in “3-D printing” (top) and “single board computers/microcontrollers such as Raspberry Pi, Arduino, Beagleboard, or similar” rated in four categories: (i) “I have never heard of this,” (ii) “I have heard of it but I have no access,” (iii) “I have tried using this at least once,” (iv) “I am a competent/routine user.”doi:10.1371/journal.pbio.1002086.g003

As part of ongoing efforts to promote scientific education and research in the developing world, we introduced the many possibilities of Open Labware to schools and universities in sub-Saharan Africa (TReND in Africa [47]) and Latin America (Backyard Brains [48]). Different formats were used, ranging from three-week intensive neuroscience summer schools aimed at university graduates in Uganda and Tanzania (four events), to multiday MakerSpace workshops aimed at school students and their teachers in Chile and Mexico (12 events), to outreach events and lectures held at scientific conferences, schools, and public spaces on four continents (more than 100 events). Here, we present some experiences and success stories from this work.

In-Depth Exposure during Multiday Training Events
The longer events, such as the three-week neuroscience summer schools in Africa or the multiday MakerSpace workshops in Latin America, afforded participants the opportunity to get hands-on experience using, assembling, and contributing to the development of Open Labware designs. One popular activity was to assemble existing designs (such as a spikerbox, Fig. 4A [10,49]) from off-the-shelf parts. This required participants to study the circuit diagram, note the identity and polarity of simple electronic components such as chips and capacitors and to solder them in place on the printed circuit board (PCB) (Fig. 4B). The assembled amplifiers were subsequently used to perform classic neurophysiological experiments such as recording of action potentials from the locust [50] or cricket [51,52] extensor tibiae (Fig. 4C). Although initially daunting especially for the many participants without previous contact with any form of electrical engineering, the experience tended to be very motivating across ages and cultures. In particular, it contributed to take away the fear of experimenting with simple electronic circuits or opening up and attempting to modify or repair existing electronic tools in their daily environment. The low cost of required parts also allowed participants to build their own gear, rather than that of their school or university, making them more invested in its success and maintenance. Critically, building equipment from scratch often resulted in a high level of mechanistic understanding and a curiosity to “play” with the finished product to see if it can be improved or modified to better suit a particular purpose. For example, one undergraduate student linked an electromyogram (EMG)-amplifier to an off-the-shelf “robotic limb” [53] via an Arduino microcontroller [1] to remotely control grasping movements by contracting their forearm muscles (Fig. 4D). Clearly, introduction of low-cost and open source electronics and mechanical parts has the potential to open up vast possibilities to resourceful people anywhere in the world, independent of financial means or educational background.

Fig 4. Hands-on exposure to Open Labware in the developing world.

A, Each student assembled a spikerbox [10,49], an amplifier for neurophysiological experiments, from its off-the-shelf components. 
B, Students at a workshop in Dar es Salaam, Tanzania. 
C, The assembled amplifiers were subsequently used to perform simple neurophysiological experiments [51]. 
Image credit for panels B and C: Horst Schneider. 
D, One student set up a spikerbox via an Arduino to trigger closure of a “gripper-hand,” a low-cost robotic limb, through contractions of their forearm muscles. doi:10.1371/journal.pbio.1002086.g004

During the three-week neuroscience summer schools in Uganda and Tanzania [54] we introduced participants to 3-D printed lab tools such as pipettes [8], manipulators [18,32], and microscope adapters [55] and compared the usefulness of self-built versus commercially available solutions for different types of experiments. For example, although printed pipettes [8] offer lower precision than commercially available ones (±2–10 μl, depending on printer precision) they are nonetheless adequate for many “low precision” tasks such as distributing diluted antibody solutions to different samples or applying mounting media for immunohistochemistry. Similarly, we used different versions of 3-D printed micromanipulators [18,32] to position reference electrodes during neurophysiological experiments, e.g., for Calliphora tangential cell recordings [56], but maintained the recording tungsten electrode on a more stable commercial manipulator. For some types of recordings, such as Drosophila electroretinograms (ERGs) [57], the printed manipulators were adequate to hold both electrodes, and the magnification gained by attaching a low-power acrylic lens to a webcam or smartphone easily sufficed for their accurate placement. We also provided access to pre-installed Raspberry Pi computers [3] running a range of open analysis and office software packages and provided basic training in their use. Hands-on exposure allowed students to judge for themselves which designs would be useful in their own research and teaching activities. In a subsequent survey, students rated the usefulness of every open design described above as at least nine out of ten on average (n = 33). We believe that the introduction of Open Labware possibilities to the African university system may be a highly effective measure towards fostering excellence in research and education on the continent.

Motivating More High School Graduates to Pursue a Career in Science

One pervasive issue in building a sustainable research infrastructure and scientific culture in resource-challenged countries is a perceived limit on career choices afforded by higher education. Traditionally, three disciplines—medicine, civil engineering, or law—are considered the best choices for reliable income, with few individuals enrolling in a natural science subject and fewer still ending up in active research [58,59]. To encourage students to consider a career in science, we (TReND and Backyard Brains) have participated in more than a hundred science outreach events around (Neuro)science, engaging more than 10,000 students, parents, and teachers. In several science camps (“ChileVA! [60]”), we gave two-hour lectures to high school students about the brain and how to record from neurons and muscles. The students not only “tolerated” this unusually long-format science lecture without breaks, but swarmed the demonstration booth afterwards. Clearly, low-cost and portable equipment offers the possibility to perform science demonstrations anywhere, independent of local infrastructure.

In TReND’s African activities, student-alumni of our summer workshops have taken over local science outreach by organizing into regional teams to visit schools and universities in their respective home countries [61]. Many of these young scientists come from similar backgrounds as the students they engage, allowing them to act as powerful role models. Thus, students attending a school that cannot afford the equipment or infrastructure to perform live experiments during science classes are exposed to local scientists with a similar background, handling equipment they know how to build from affordable, local resources. The experience can be very powerful and inspire them to pursue a similar career, as well as offering local teachers ideas to use in future science classes. This approach of “teaching the teachers” also means that the impact of educating a few students at a high level has the potential to trickle-down and achieve a wide impact in the long term.

Policy Recommendations
Clearly, the use and design of Open Labware designs can be a powerful ingredient to foster scientific research, education, and public science engagement. Their evolution spans several disciplines, from computer sciences and mechanical engineering to electronics and biology—thus connecting experts and the wider public across fields and sparking creativity in people of all ages. Their low cost, adaptability and robustness renders designs suitable for a broad range of applications in both teaching and research. Below we present some suggestions for policy implementations to optimize available possibilities.
Integrate more aspects of design and use of Open Labware into traditional science curricula, ideally at an early age.
Establish more hands-on training courses in basic hardware design and programming skills for established scientists and educators.
Establish infrastructural support to afford more students and educators easy and direct access to 3-D printing and related technologies. With 3-D printers starting at a few hundred dollars and their price steadily falling, schools and university departments should not be barred from investing in their own model because of economic reasons.
Provide incentives for companies to invest in an open model of product design. This move promises to spark a new generation of open companies in more direct dialogue with the end user, towards better, individually tailored, and more affordable product design.

Supporting Information

S1_Data.zip

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Container with all files mentioned in the article that are currently hosted on thingiverse (www.thingiverse.com).

S1 Data. 

Thingiverse files.
Container with all files mentioned in the article that are currently hosted on thingiverse (www.thingiverse.com).

doi:10.1371/journal.pbio.1002086.s001

(ZIP)

Acknowledgments

We thank the students and voluntary instructors of the many lectures and workshops mentioned in the manuscript, as well as the TReND outreach team, headed by Mahmoud Bukar Maina and Yunusa Mohammed Garba, for their ongoing efforts in promoting science education in Africa. We thank all sponsors of workshops, most notably including the International Brain Research Organization (IBRO), The Company of Biologists, and the Cambridge Alborada Fund.

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ORIGINAL: PLOS
Tom Baden,
Andre Maia Chagas,
Greg Gage,
Timothy Marzullo,
Lucia L. Prieto-Godino,
Thomas Euler
March 20, 2015
DOI: 10.1371/journal.pbio.1002086

Stephen Wolfram's Introduction to the Wolfram Language

Stephen Wolfram introduces the Wolfram Language in this video that shows how the symbolic programming language enables powerful functional programming, querying of large databases, flexible interactivity, easy deployment, and much, much more.

To learn more about the Wolfram Language, visit reference.wolfram.com/language.

For the latest information, visit www.wolfram.com.

How to Make (Assemble) a Computer (in 107 Seconds)

Kano is the first computer kit for everybody.
Make, play, code, and level yourself up.
Coming to Kickstarter on November 19th. (USD119)

Sign up: http://kano.me

What's inside?

1. Kano Books, illustrated and intuitive
2. Kano OS and Levels – 8GB SD card
3. DIY Speaker
4. Raspberry Pi Model B
5. Kano Keyboard
6. Custom case
7. Card mods and stencils
8. Stickers!
9. Cables: HDMI, Mini-USB
10. Worldwide power plug
11. WiFi powerup 

Sentient code: An inside look at Stephen Wolfram’s utterly new, insanely ambitious computational paradigm

Stephen  Wolphram

In 2002 Stephen Wolfram released A New Kind of Science and immediately unleashed a firestorm of wonder, controversy, and criticism as the British-born scientist, programmer, and entrepreneur overturned conventional ideas on how to pursue knowledge. Earlier this month, he teased something with the capacity to create as much passion — and, likely, much more actual change — in the world of programming, computation, and applications.

Today, Wolfram gave me a glimpse under the hood in an hour-long conversation. And I have to say, what I saw was amazing.

Whether you think his 1,300-page tome on the future of scientific exploration is seminal or fanciful, you can’t question that the man is a genius. Born of Jewish parents who fled persecution in pre-WWII Germany (remind you of another scientist?), Wolfram wrote a dictionary on physics at age 12 and three books on particle physics by the time he was 14, publishing his first scientific papers at 15.

In 1988 he released the first version of Mathematica, a platform for technical computation, and in 2009, he released the Wolfram Alpha search engine, a computational knowledge engine. His new project, he says, is a perfect marriage.

“Mathematica is this perfect precise computation engine, and WolframAlpha is general information about the world,” Wolfram told me. “Now we can combine the two.”

The combination is just part of the picture. Included in the new project is natural language programming — not that a program can be created exclusively with natural language, but that a developer can use some natural language. Also included is a new definition of literally anything in your application — from code to images to results to inputs — as being usable and malleable as a symbolic expression. There’s a whole new level of automation and a completely divergent approach to building a programming language, away from the small, agile core with functionality pushed out to libraries and modules and toward a massive holistic thing which treats data and code as one. And there’s a whole new focus on computation that knows more about the world than the programmer ever could.

‘Insanely more ambitious’ than Google knowledge graph

But don’t compare it to Google’s knowledge graph or semantic search.

Wolfram

Components of the Wolfram language.

“The knowledge graph is a vastly less ambitious project than what we’ve been doing at Wolfram Alpha,” Wolfram says quickly when I bring it up. “It’s just Wikipedia and other data.”

Google wants to understand objects and things and their relationships so it can give answers, not just results. But Wolfram wants to make the world computable, so that our computers can answer questions like “where is the International Space Station right now.” That requires a level of machine intelligence that knows what the ISS is, that it’s in space, that it is orbiting the Earth, what its speed is, and where in its orbit it is right now.

That’s not static data; that’s a combination of computation with knowledge. WolframAlpha does that today, but that is just the beginning.

Search engines aren’t good at that, Wolfram argues, because they’re too messy. Questions in a search engine have many answers, with varying degrees of applicability and “rightness.” That’s not computable, not clean enough to program or feed into a system.

“We want to be right,” Wolfram told me. “Making the world computable is a much higher bar than being able to generate Wikipedia-style information … a very different thing. What we’ve tried to do is insanely more ambitious.”

It’s so ambitious, and so far-reaching, that it’s hard to describe. Wolfram says that of all the different things he’s done in his life, this is the most horribly complicated to explain. Remember, this is a man who has written on particle physics. It’s both intellectually deep and far-reaching, with many implications — “tentacles,” Wolfram calls them — into different areas of programming and science and knowledge and business.

There’s no good elevator pitch for the language, and even though it’s not entirely released yet, there are 11,000 pages of documentation already. In one of any number of nutshells, however, it’s a giant leap forward in building accessibility to the world’s knowledge, in making programs — and eventually things — smart.

Making the computer do the work

“In general, what we’re trying to do is so that as long as a person can describe what they want, our goal is to get that done. A human defines what the goal should be, and a computer does its best to figure out what that means, and does its best to do it,” Wolfram says.

I watched him do it, live.

Countries and flags in South America, thanks to Wolfram language. John Koetsier

In about 30 seconds, Wolfram created a small web application that drew circles on a web page and included a user interface so a visitor could make them bigger or smaller, or change their colors. That’s doable simply because the Wolfram language — with its access to a vast reservoir of knowledge — knows what a circle is and can make it, and it automatically provides web-native user controls to manipulate it. It was a trivial example, but in another 30 seconds, Wolfram built a code snippet that defined the countries in South America and displayed their flags. Then he called up a map of Europe and highlighted Germany and France in different colors computationally, in seconds.

This is only possible because the new Wolfram computational framework includes the complex and precise algorithms developed in over 20 years of Mathematica development, plus the knowledge engine built up inside WolframAlpha.

And the results are shocking.

Automation through information

Infragram: the Infrared Plant Photography Project

ORIGINAL: KickStarter
by Public Lab
 

A simple, cheap infrared camera which can measure plant health -- for geek gardeners, farmers, and open source DIY scientists.
What could farmers, gardeners, students or environmental activists do with an infrared camera that costs as little as $35?

What is Infragram?

Infragram is a simple, affordable near-infrared camera produced by the Public Laboratory community in a series of collaborative experiments over the last few years. We originally developed this technology to monitor wetlands damages in the wake of the BP oil spill, but its simplicity of use and easy-to-modify open-source hardware & software makes it a useful tool for home gardeners, hikers, makers, farmers, amateur scientists, teachers, artists, and anyone curious about the secret lives of plants.

What can you do with Infragram?

• Take pictures to examine plant health in backyard gardens, farms, parks, and nearby wetlands
• Check on the health of your crops, especially from a balloon or a kite
• Monitor your household plants
• Teach students about plant growth and photosynthesis
• Create exciting science fair projects
• Generate verifiable, open environmental data
• Check progress of environmental restoration projects
• Document unhealthy areas of your local ecology
• Pretend you have super-veg-powers

Near-infrared photography has been a key tool for planning at the industrial and governmental level: it is used on airplanes and satellites by vineyards, large farms, and even NASA for sophisticated agricultural and ecological assessment. In contrast, Infragram allows average people to monitor their environment through verifiable, quantifiable, citizen-generated data. Just as photography was instrumental to the rise of credible print journalism, inexpensive, open-source data-collection technologies democratize and improve reporting about environmental impacts.

Start exploring your world today with Infragram!

How does it work? 

Photosynthesizing plants absorb most visible light (less green than red and blue, which is why they're green to our eyes!) but reflect near-infrared. When you take a picture with the Infragram, you get two separate images -- infrared and regular light -- and a false-color composite that shows you where there are big differences. Bright spots in the composite means lots of photosynthesis! (Learn more here)

We're able to get both channels in one by filtering out the red light, and reading infrared in its place using a piece of carefully chosen "superblue" filter (read more here). The images are later processed online -- combining the blue and infrared channels into an image map of photosynthesis (as shown above).

What you get

DIY Filter Pack: This is just a piece of "superblue" filter which you can use to turn your webcam or cheap point-and-shoot into an infrared camera. The filter allows you to take an infrared photo in the "red" channel of your camera, and a visible image in the "blue" channel. You'll also receive a white balance card and instructions on how install your filter -- it's pretty easy!

Infragram Webcam: This inexpensive but flexible reward is perfect for plugging directly into your laptop or integrating into other projects. It's also ideal for your Raspberry Pi, if you want to take it outdoors, do timelapse photography, or write scripts to control your camera. It ships as a bare circuit board with a USB cable - like an Arduino.

Infragram Point & Shoot: Just want a camera? This is a straightforward, if basic, point-and-shoot: you can simply take photos as you normally would, then upload them to our free and open-source web app to quickly and easily get a variety of composite images and analyses. To accomplish this, we're simply modifying existing cameras which we'll buy in bulk, using the "superblue" filter. This isn't an SLR or even a particularly fully featured camera -- it likely won't have an LCD screen and may be "rebranded" with a Public Lab sticker -- but it's the new filter we've put inside which counts.

The final configuration will depend on the # of backers, but it will likely use AAA batteries and a micro SD card. We're promising a minimum of 2 megapixel resolution, but should be able to do much better, especially if we get a lot of backers. Basically, the more money we raise, the better these cameras will get!

How you’ll develop your images

Whether you’re using our DIY filter with your own camera, the Infragram Webcam, or the Infragram Point & Shoot, you’ll be following the same, easy process to generate composite, infrared + visible images that will reveal new details of plant health and photosynthesis -- like in the photo above, taken out the window of a commercial airline flight!

1. Calibrate. In order to get the most meaningful data possible from your plant images, it’s a good idea to ‘calibrate’ your camera, taking into account the current lighting conditions (sunny vs. cloudy, indoors vs. outdoors) at the time that you’re taking your photos: this makes it much easier to compare ‘plant health’ images taken at different times, in different places, and by different cameras. To make this easy, we’ll likely be providing an additional ‘white balance card’ -- simply, a card that has a standard color -- in our kits. By recording an initial image that includes this card, you’ll be able to use our online software to “standardize” the colors in all of your images. If you don’t have a card, don’t worry -- there will also be opportunities to calibrate your imagery automagically later, using our analysis software, and the results might be just as good.

2. Take your snapshot. “Rhododendrons -- say cheese!” Using your own camera (modded with our DIY filter), the Infragram Webcam, or the Infragram Point & Shoot, you’ll record the scene of your choosing -- ideally, with some vegetation-y life forms in it. Take pictures of household plants, garden vegetables, trees -- we’ve grabbed a lot of useful agricultural imagery from cameras dangling from kites and balloons! The Public Lab website and mailing list are already full of examples and suggestions related to infrared photography, and it’s easy to start a discussion with community members about your ideas, or ask for advice.

3. Upload. After you’ve finished an image capture session, you’ll want to upload your images using the (free, open source) online software our community is developing. This will likely simply involve navigating to a particular URL and dragging-and-dropping your images onto a specified area of a webpage. Easy peasy.

4. Analyze. If you thought the prior steps were fun, this step is fun +1 . We’re planning on providing a suite of image analysis tools online, so that everyone from researchers to geek gardeners can analyze, tweak, modify, and re-analyze their imagery to their heart’s content, extracting useful information about plant health and biomass assessment along the way.

5. Share. And perhaps the most exciting aspect of all: your imagery, your work, and your insights can easily be shared with the rest of the Public Lab community via this online service, the Public Lab mailing lists, and wikis and research notes at http://publiclab.org. Develop a kite-based aerial imagery project with your friends; get advice from NDVI researchers in the community as to the best techniques for yielding useful information from your garden photos; create and collaborate on new methods and protocols around DIY infrared photography. Public Lab’s ‘share and share alike’, ‘open source’ learning community model is not only fun -- it’s a great way to make rapid progress on any project!
Prototypes

The Infragram has been in active development for over a year now; our first prototype was made over 2 years ago and was simply some custom filter material taped to a camera!

Others have used 2 aligned webcams, and many have been tested alongside custom Raspberry Pi controller code which auto-composites the imagery. Read more about the collaborative, open source development of this tool here: http://publiclab.org/tag/near-infrared-camera

The modification to the camera happens inside, out of sight, unlike in some of the above prototypes. The final version will be based on a mass-produced camera like the one below (one of our prototype mods), though we are waiting to see how many backers we get before settling on a final model. If we have enough backers, we'd love to do a fully custom enclosure as well!

Gallery

Here are some photos showing Infragram infrared composite images from various prototypes. You can find more images here.

Who are we?

Public Lab is a community of tinkerers and concerned citizens (supported by a nonprofit) which develops and applies open-source tools for environmental exploration and investigation. Our small nonprofit has run three successful Kickstarters--Grassroots Mapping the BP Oil Spill, Balloon Mapping Kits, and DIY Spectrometry.

Our community of contributors help each other problem solve and trouble shoot through online mailing lists and research notes, organized by region and topic. This allows community members to share research, and for the combined brain power of dozens of people to answer questions and innovate rather than relying on a traditional "customer service" model. Join the Public Lab infrared discussion list today to get started!

On this project, we've collaborated with a range of different groups to meet the diverse needs of gardeners, farmers, environmental activists, conservationists, and more. These include: Gulf Restoration Network, FarmHack, GreenStart, the Design Trust’s Five Borough Farm project, Belize Open Source, and others!

Public Lab Staff in Cocodrie, LA--January 2013

Risks and challenges  
Learn about accountability on Kickstarter

This is Public Lab’s fourth Kickstarter campaign; our experience with the previous three successful ones have taught us lots about everything from production to fulfillment and international shipping. We've already shipped functional prototypes for the camera (which was actually a reward in a previous campaign), and are confident that we’ll be able to turn out a great new design for larger scale production with your support.

Our main unknowns at this point are the final specs on the different cameras we'll produce -- such as maximum resolution, battery life, and housing, which we have plenty of options for, but for which we need to know final order quantities before finalizing design work and choosing a supplier. We're lucky to have a vibrant open source community behind the project at PublicLab.org -- one which you're encouraged to join to help move the project along by contributing your skills!