My final set of notes from the summit on 18 February are below. They only cover the morning talks as I spent the afternoon in discussions with other attendees. Apologies for typos or bad formatting – typing on an iPad leads to weird autocorrects or missing spaces, and Posterous – well, don’t get me started. I hope I have time to migrate out of it sometime soon.Enjoy! —– Open Knowledge Foundation Supporting reuse and remixing of data and content, permission is a major impediment to innovation. Artificially intelligent chemical software to extract data from software but can’t use it due to publisher licensing, technology is stalled due to antiquated IP. OKF is a call for people to gather around the meaning of openness and how to make knowledge open. Not a campaigning group but looking at how to create tools and infrastructure to get information out to as many people as possible. Example of malarial research, frustration that no one can read the literature for free. Many people don’t read the literature because they can’t afford to. This is relevant to medical, climate, and development contexts. Trying to change the culture so that it becomes the norm that people have the right to access to the scientific literature. Working on this through scientific tools, one tool is Open Bibliography, makes reference collections completely open – just the list of references. Making reference lists available is a valuable resource in itself. Emphasis on high quality research creation and software for infrastructure across disciplines. OKCon2012, datahub.org —– Cabell – Online Collaboration and Legal Concerns Legal overview: global collaboration is confusing; local not global laws which means some are regional and others are enforceable in different areas. Default rules that exist around ownership and control of distribution of work, have to actively change these settings, usually in writing, they are inconsistent rules with limited interoperability, generally law provides ability to exclude but not engage, and prior rights may limit use of your own work. IP basics – patents, very expensive, cost about $12K, has to be new, useful, and not obvious, which is a lower bar than it sounds like. What is protected is method or process. Newness leads to embargoes on publication, have to file before publishing or you lose rights, so this holds up dissemination of research. Rights are to make, use, sell unless blocked by existing patents. Patent ownership is to actual inventor; if you invent on the job, it’s subject to shop rights. Lasts for 20 years. Trademark is about identifying source of goods or services, usually a registration process but not in US, have to show public recognition of brand and limited to class of goods and services. Term is as long as people recognize brand. Trade secret – lasts as long as it is secret. No legal definition, NDA keeps secrets, no right to use information, but for preventing exposure. Copyright protects original expression, not idea, not statements of bare fact. Eligibility criteria is low, but different – intellectual effort vs sweat of the brow. Annual contest, Buller-Litton, for worst possible writing you can produce, example of expression versus fact. Facts are free to use without attribution, therefore not copyrightable, but data aren’t necessarily limited to facts so beware of underlying rights which may bewildlydifferent depending on the type of work involved – e.g., a Db of photos has different rights than Db of numbers or CDs and songs. Not (always) true that data aren’t copyrightable. Collections of facts are not copyrightable, but collections of Xrays are. Rights are prevention of copying, distribution, derivatives, translations, display, public performance, related rights like moral rights including integrity (intact w/o change). Rights differ based on type of work, e.g., artistic versus literary which includes software, Dbs, texts. Dbs can be copyrighted as a compilation, collection s of elements which are not individually copyrightable. Copyright is automatic the moment the creator fixes it into tangible format. Contributing thought not the same as expression, so coauthors who write nothing have no right to copyright (watch out, PhD advisors!) Works for hire automatically belongs to employer if created as part of job duty. Universities have different policies in this regard, e.g., as to theses. Funding sources can impose ownership and publication restrictions, e.g., funders requiring deposit of data or outputs. Specially commissioned works, e.g., from freelance and consultants – wedding photographers own copyright, do not belong to commissioner unless agreement in writing. Government works – federal work is in PD in US, so no one owns it, Crown copyright in UK. Types of joint ownership – unless group of collaborators think of work as a single work, then they are not really joint authors; if they do, each author has right to sell the work. If only some authors consent to combined use, then it’s a compilation or collective work, only the combination or part that is newly created is owned by the compiler. Duration of copyright is very complicated! SGDR – parallel to copyright, subject to abuse. Other issues to consider: privacy tightly restricted in UK but hardly protected in US. Limited piecemeal protection in Us. Discrete bits of info may not reveal an individual but a combination of sources can, which runs a risk when combining databases. Main question is where you operate, if you operate in US but take data from UK, you are subject to UK law. Other related random acts: human subjects research, public sector info, species and environmental info acts, import/export acts e.g., software is an armament, child protection laws, national security, institutional and professional ethics. Implications for citizen science: usually no legal entity for voluntary collaboration, so that means no centralized management or ownership can take control of IP, only a person or business can own something. Default settings may be inconsistent with community’s intended uses of works, individual contributors can make decisions without consulting whole, piecemeal and distributed rights. In addition, law treats collaborators as joint offenders, individuals not protected from liability or harm done bothers in collaboration, e.g., copyright infringement. So one member can beheld legally responsible for harm done by others in the collective. Best legal practices: know own rights; document each contribution as well as possible like with version tracking that helps ID author, location and date; where possible, formalize collaborative organization to simplify legal application; carefully specify collaboration rights. Open sharing has lots of standard public licenses like OKF and GPL and CC. OKF has reference list that shows how open licenses are and what they apply to. Linked Open Data efforts being used to facilitate sharing. CC applicable in 75 jurisdictions. Recommend CC0 (public domain) for data, attribution becomes too difficult. Natural history observations are considered statements of fact and not copyrightable, but comments about them would be copyrightable. —– Plantin – radiation mapping in age of bad data Post-Fukushima: initially no data, but then bad data. Worries about sensitivity and then mishandling, data produced by entities whose motivations could be questioned. Several radiation mapping mashups. Mapping radiation was a 4-step process: 1. scrape it directly from websites, but initially unstructured, read through source code. 2. Measure it, many people tried to do this, could be done by many different groups or organizations. 3. Aggregate it, e.g., with Pachube, which is platform for online aggregation and redistribution through API calls. 4. Map it. Examples of only official or only alternative data, but more interesting is them mashup using both sources. Also useful for verification. Focus on monitoring group, SafeCast, ad hoc group of engineers in Tokyo, hard to ow if it is science, not planning to intervene, only trying to provide data and trigger reflexivity. Not activists. Hackers but not hackers, tinkering in DIY way, but close to community, so crossing the dynamics of science, activism, hacking, community. —– Ishigaki – Radiationwatch.org Making radiation data available to public. Created device that is housed in a candy box “Frisk”. Used it because they had no time or money for plastic injection molding. Hooks into smartphone, 4 color variations! (much laughter) Much better than 40-lb Geiger counter. Free iPhone app, Pocket Geiger, takes 5-10 minutes to analyze your data. Factory right outside of tsunami disaster area, but income went down, so their nonprofit organization creating many jobs for disaster recovery. Socially inclusive, 3 core members, 5 professionals (pedologist, Dutch DoD, Dutch NIST, NASA, Japanese CERN), 12 hackers, 10K+ users. User reports on FB group, radiation levels high in children’s park, drainpipes, very high inflight. Have millions of data points but now running into privacy problems. Cities creating monitoring posts for radiation, specialists going to create high accuracy devices, but need to know radiation levels in own homes as well. Hates this governmental model where citizens have no access to data. Issues about inconsistent measurement by contributors, need metadata or it’s not usable. Not even units or measurements, but also environment in which measurements were made. —– Maisonneuve – Public analysis of satellite images 300K damaged buildings to assess (from earthquake?), difficult to do by professionals due to scale. Organizational issues, how to organize non-trained volunteers to enforce quality and analyze a large area, either remotely or in the physical world. Parallel model, n volunteers monitoring the same area for inter-rater reliability. Another model is iterative, annotation and progressive improvement like Wikipedia. Experimented with these approaches in 3 maps. Types of errors, false negative and false positive. Parallel model is eduction of false detection rates, redundancy useless if at the individual level p=1, p=0.5, want only consensual results, doesn’t solve problems of omission, agreement on obvious buildings but not difficult ones. Sensitive to aggregation parameters. In iterative model, somewhat reversed, less omission of buildings so better area completeness. Sensitive to destruction of knowledge in a basic implementation (last=best), very sensitive to initial conditions, so first player is very important – maybe need experts on this part. Skill is an issue, how many volunteers needed to reach a certain level of quality? At some point, you get to a point where you can add more people but there are problems of scale,quality canbe replaced by uantity. Issue of complementarity, aggregating results of the test contributors, individually not all that great but together you get much more value. Second question about training volunteers, ongoing effort. Difficulty of task can be assessed according to agreement, easy tasks have high agreement but difficult ones have more spread. Last point is that crowd learning can happen through learning through others mistakes, can identify most common errors and use this density of errors to use information to educate people according to errors of previous contributor errors. —– Foster – Project Seahorse: advancing marine conservation Based out of UBC, committed to sustainable marine ecosystems. Know what is wrong, but have to figure out how to fix it. Why seahorses? They are really cool fish! Most people don’t know that they are fish, have a bunch of cool evolutionary features (horse heads, marsupial pouches, prehensile tails) only species where the male gets pregnant. Seahorses are like a panda, no one cares about mudflats or mangroves until you tell them that seahorses live there. So saving seahorses means saving their habitats. Threats include overfishing and target catching by small scale fishers, majority are caught as bycatch by shrimp trawlers, discard thousands of tons a year. Like using bulldozer in a forest to catch a deer. Threats to seahorses are threats to oceans and other marine life. Captured seahorses are traded internationally, especially for Chinese traditional medicine, curios, aquarium trade. They retain shape when dried, so they are interesting curios like seahorses with fish fins guard to them like wings clutching mini tequila bottles. Trade is large and global, 10M sesahorses around world in 80 countries, so it is one of biggest species trade problems. CITES regulates international species trade, all 46+ species are listed in Appendix 2 which means international trade is permitted but regulated, so have to prove sustainability. Seahorses are one of most important fishes on CITES, first fish listed, previously not considered a species for international regulation, immediately after they were listed several other fishes were added that are traded internationally. Problem is lack of location-specific information about seahorses to help groups meet mandates for demonstrating sustainability, IUCN red list shows most of the species (28) are DD – data deficient – all 8 species are EN or VU, basically very threatened or endangered, chances are good this is true for other species. Can’t spend her life diving to find seahorses around world for lots of reasons, most important is lack of time because we need to act now. Fortunately people are diving the world already, and sending them info about seahorses. Being done for other taxa already, but new for the ocean, few other projects focus on marine species. Best examples of citizen science are birds (eBird). Have done it so well, they have monitored conservation status of over 40K species. Challenge is addressing marine problems, wants to “give seahorses wings.” Marine environment is extreme for monitoring, can’t get GPS, most electronics don’t work underwater in part due to pressure. SCUBA surveys overcome issue of location by tethering to floats on surface. Another problem is that a seahorse is easy to identify, but telling which species they are is very difficult. Wants to start a project that will be so sexy that every diver to give them data and feel they are making a difference for ocean stewardship. Critical because they won’t be able to enter data immediately. Maybe they make notes on dive record, but have to still want to enter it back at their hotel before getting into Coronas on the beach. Made progress here already! Trying to work with EpiCollect, someone else has offered to help with branding, but also needs protocol and building a toolkit for monitoring seahorse populations, train worldwide groups to assess these trends locally as partners. Needs help with feedback tools, beyond point maps and bar charts, like overlapping seahorse info with other marine data. If they can map where threats are, this helps communicate sense of urgency and conservation needs, and prioritize monitoring locations. Needs info on lessons learned and experiences. —– Jones – iBats: using smartphones and citizen networks to globally monitor bats Many indicators of recent declines in global biodiversity. Looking into smart monitoring, bats are a good indicator, a fifth of all animals, widespread and sensitive to global change (behaviors sensitive to temperature) and important ecosystem service providers. Cool animated radar graph of bat emergence in Texas, saving a third of the crop pesticide costs by eating up bugs. Bats also interesting because they emit radiation in the form of echolocation, using ultrasound to communicate and locate objects. Can sense bats based on this radiation leaking. They created database of bat acoustic biodiversity, wants to use to to classify bat species. If acoustic monitoring could be done with these identifiers, why do this and where? Combined index map showing areas where the current potential for using the tool is highest due to call similarity, e.g., very different calls in certain areas. Have tested acoustic species classification tools, most call types can be identified at over 97% accuracy except one group of calls. So continental tools would be the ideal. Using ultrasonic microphone (very expensive, 400 GBP, trying to hack a cheaper version they think they can do for 10 GBP) plugged into smartphone headphone jack; need special microphone because high frequency sound requires high speed sampling. Have developed portals/versions in different locations and different languages. Started off in Romania (of course!) but effort has moved around the world. From there, building distribution maps, using machine learning and creating hotspot maps to inform conservation policies. Cn do trendlines, to show bat populations as a headline indicator of ecological health. Latest project is also doing this for frogs and insects like crickets. Got Zooniverse funding for Bat Detectives so they’re currently working on noir branding of their project.
Notes from 17 February talks in London – for full details about speakers, see the full program at http://cybersciencesummit.org/35-2More really exciting talks! Great diversity of projects represented, wildly variable technology sophistication, and fascinating people. Check out the #LCCS2 hashtag on Twitter to see the discussions. —– Plug for EpiCollect – easy to configure interface for setting up obile-basedmonitoring and web-based result displays, non-technical project organizers can use it easily. —- Igoe – NYU Tisch school of the arts – Keynote Citizen science is a good term but sets up a divisionary dynamic. Those people you try to engage come with their own expertise. Biggest challenge at ITP program is getting students to understand each others’ backgrounds. Lot of emphasis on making and hacking. Igoe does physical computing program, lots of students want to go beyond the computer in terms of interfaces. Trying to get them to start their thinking based on what people do physically, start with actions and not mapping to an existing controller. Lots of art projects, some projects are less functional or are just plain strange – “Circadian squirrel” – stuffed robotic squirrel that moves around and then removes its head, created by a former librarian, Jill. She also made cricket headphones, with little habitats for crickets that you wear like headphones. Another person made a radiation detector that is made of gongs, something of a Trojan horse that would get attention from people who otherwise wouldn’t notice. Biologically generated materials – electrolysis for building up calcium carbonate as a sculpting material. People interested chemistry and biology then got into the aesthetics of the sculpture. They use a system called Processing to get people up and going with programming quickly, also a lot of Arduino that lets people build good instrumentation right away. Example of balance board to help stroke victims that students were able to build in 2 hours, programmed the visualization interface in 15 minutes, and the speed of development allows easily throwing away things that don’t work – you don’t get attached to the thing because of the investment in creating it, which means you do more and innovate faster. Lasersaur – laser cutter that can be built from kit for $500. OpenOCR allows you to do DNA analysis for about $500. Gets people into doing recreational biology. Not all of the projects are functional like this, others allow people to explore their own expressiveness. Adaptive technologies that help people explore their everyday life, noticed the way that physical expression happens in wheelchair users, just as expressive as any other body language. Created a pair of ramps for a wheelchair so a person could DJ by wheelchair movement, allows him to use his skills to do what he wants. MD sufferer who loves MLB on PS3 but can no longer play his games since the disease has reduced his capacity, created a controller that works for his abilities so he can play again. An occupational therapist who got tired of the paradigm of “give us specs, we’ll go away and build it for you” but devices were never what she wanted, so wanted to build it herself. Created a range of motion measurement tool that allows you to make music that gets better with greater range of movement. Patients improve faster because they focus on making music, not doing exercises. Interdisciplinary collaborations, students wanted more plants in their environments but were concerned that they would all die. Created plant moisture and humidity sensor that calls you when it’s sick, now they’re selling the kit which lets you DIY but you also get attached to a plant. Project Noah was a procrastination that has worked out really well. Loves monkeys, someone called him on his bluff about wanting to work with monkeys. Anthropologist who wanted to use motion technologies to track monkeys, so Igoe proposed a class on tracking monkeys, which actually was approved. So he ended up in the rainforest tracking monkeys, interesting interaction design challenge for students. Focus on what people do for their work and how to improve that, instead of teaching students about primatology, taught primatologists about technologies, but learning went both ways. Example of clunky telemetry antennas and old PDAs that they are stuck with and cannot replace. Students thought they could just move to Android, but there is no network. So one student put together a cell network using observation towers, almost up and running. Primatologists do a lot of analysis with monkey poop that they bring back to NY for analysis. Problems with broken gel cones that cost $60 each, a student was able to use a laser cutter to create some for $10 each. Sometimes send students to zoo to watch monkeys, students will watch for 3-4 hours in the cold! Students got obsessed with observation protocols, applying it to game design. They play hide and seek with radio collars and discover that it’s not so easy to find people with radio collars, technology is crude and you have to learn a lot about radio to use them. Some things you can teach in theory, others you have to experience. Competition to develop tool to measure monkeys without “taking the monkey down.” Winning device created by photographer and engineer, their job was running a fablab, so they had unlimited access to tools, tested it on stuffed animals, found that in the wild it worked so well that it was only .5 cm off. Students got bored with it and moved on, but left the plans for others to build on. Another project funded by UNICEF, dealing with clean water issues. Water detection tools are expensive, hacked a mass spectrometer from Arduino. Not that expensive, students formed a company to market their tool and release it openly so others can make it as well. ITP promotes a lot of OSS and OSH. Students work to make things for nonprofits and researchers, it’s working out really well. Lion collar that warns farmers when lions are nearby so they can move their cows. Key thoughts they transmit to students: art, science, engineering and design are all deeply personal, idea doesn’t matter until it’s used in real life. It’s worth being promiscuous, best ideas are those that grow, those that are hidden do not amount to much. The things we make are less important than the relationships we support. Qs: are there things bridging gap between cit sci and art? Yes, more overlap than you think. Students ID most of the problems to address. What do you think the role that self-selection is? Classes are idiosyncratic, self-selection is valuable to making useful outcomes. Spend a lot of time with admissions to get people who will work well in this program. How to make it happen in other schools is being open to cross-disciplinary collaborations. Have you done any biohacking? Not yet, dying to. Have attended workshops, interesting to see what comes up. Postgrad adults in genspace workshops feel much freer about expressing themselves in class, about failing, because there’s no grade, they experiment more. Discussion about sample swabbing, aesthetics and patterns for doing bacterial cultures and what works best. What about PCR tools? Haven’t done that yet but planning to, people are finding results not the same using these tools. How do you get people to realize they have an interest? Answer is counterintuitive – it’s listening, finding out what people want and need before they create anything or even agree to try to do it, making sure it will work. Have a diverse group of people, how well received are you by academics? Reason he is here is works with Francois Grey, overall reaction has been good – people know what they are and what they’re not, they come to them looking for new ways of looking at things, not precision. They are in a performing arts school, and are hard core in that context. It’s about knowing what they are and are not and being clear about that. Recently started a summer camp, people want a starter course or alumni want to retool their skills after a few years out of school with all the technologies changing. Important because hackerspaces are replacing what they do, so role in university is less relevant when community is doing what they do, they can either fight it or work with it. So they work with it. How much do you expect on admissions? Just a bachelors degree with some exceptions, train them in all the basic skills they need. Try to admit a diverse group, not too many performance artists or engineers, make multiple passes on balancing the composition of the group. Tigoe.net —– Dosemagan – Public Laboratory for Open Technology and Science: open source development of tools for grassroots science Publiclaboratory.org Low cost DIY environmental and health tools – science is too expensive, too much science is academic-oriented, lack of on the ground experience among researchers, lag in knowledge exchange, people on the ground don’t own the data, don’t understand the problems. They call it civic science (problematic due to other baggage.) BP oil spill – mapping using cameras in 2L bottles on balloons and kits, mapped oil spill over time. The point of grassroots mapping is offering an alternative, let communities address their own problems and issues like a media blackout and inability to engage in the spill despite local impacts. All work they do requires open source licensing, they maintain a public domain archive, have agreement with Google to show their maps on Google Earth with their data. Beyond archive, needed to take results to different formats to disseminate information. Printed the grassroots map and dropped off at marinas, seafood restaurants, gas stations, so people can pick up maps and do ground truthing. Initial project spread quite a lot, second project is use at Gowanus Canal Superfund site in Brooklyn and in other countries all over the world. In Brooklyn are able to see inflows and other problems at site, then can do ground truthing. Able to start developing new applications and techniques. Another is near infrared camera, based on NASA sensing, using to look at vegetative health in wetlands and other sites. Approach helps them reduce barriers to new efforts, they call these intensive hacking events barnraisings. Had camera hacking event in NC bringing together a broad team, now are able to use infrared imaging for their aerial monitoring. Able to show photosynthesis in urban and wetland areas. Unexpected impacts – aerial mapping of protests in S America. Locals not only made a device but also instructions on how to build and how to get materials in Chile as well as costs. Doing livestreams with iPhones, showed that area of activity was much bigger than officials were saying. Has been adopted much more broadly, subverts corporatized view of space and place, it’s about a moment in time, not just a place. First used in US for Occupy events. Low cost approaches to environmental health and toxics. Tracks are healthy homes, community science, sustainable futures. Healthy homes – Roomba-based indoor air quality mapping, taking long exposure films to see paths and activate test strips. Now working with formaldehyde sensors. Moving away from Roombas because they move too fast, so they now use hamster balls with $4 robots inside. Thermal imaging – flashlight that uses long exposure film and customized flashlight to find heat loss areas so people can take action, immediately analyzable and usable. Same idea with formaldehyde, identify brands of carpet that release more of this chemical that is linked to asthma. Community science – hydrogen sulfide sensing, neurotoxic gas that is developed by bacteria in gas well. Setting up bucket brigades for air sampling, normal cost is $500 for analysis and sample has to be returned to lab in 24 hours, hard to do in rural areas. Hydrogen sulfide tarnishes silver, so creating silver halide screens using photographic paper to sense the gases. Working closely with academics to lab standardize the test so it can speak to validity of the science. Other projects looking at environmental estrogens, interested in developing DIY tests to examine water sources and aggregate information on environmental health threats. DIY spectrometer to ID broad range of chemicals, kit you can buy online. Also interested in supporting alternative agriculture and environmental remediation, infrared camera and low cost image analysis with “clashifier” to support remediation projects. Focus is on community oriented, developed, and owned science to address local interests. —– Zoological Society of London – Instant Wild – Hardware vs Hyenas App that transmits photos from the wild to phones for instant analysis. Focus is promoting and achieving worldwide conservation for animals and habitats. Have used camera traps, requires manual retrieval and troubleshooting. New technology making that wireless, currently have app on iPhone, lets members of public identify animals in photos and lets them see new species during your commute. Branding based on an app. Only have 6-7 cameras out there, issues with hyenas. Sri Lanka sites, don’t release specific locations to prevent poaching and trapping. App allows people to debate IDs, have had 80K downloads in 3 months, over 320K IDs. 7K regular users. Species in Kenya – porcupines and elephants. Sri Lanka – porcupines and deer. Surprises – fishing cats, African leopards, owls. Mountain mouse deer, only first photographed 3 years ago, so they are finding and recording rare species live. Next steps are increasing camera numbers, continue to develop next gen cameras and network, and protect cameras from damage: hyenas eat cameras! Even when in security cases, hyena teeth go through LCD screens. How does it work? Cameras with LED flash, GSM antenna, PIR sensor, lens, and security lock. Saves to SD card, target audience is commuters on the way to work, bored people who can spend time looking at data. Question is how to transmit data from wild to central London? Tools include Arduino, Raspberry Pi, Digi. Current cameras involve ScoutGuard, UWay MMS, Reconyx – best trail camera ever made. Limitations are SIM card based cameras, limited by GSM coverage, not scalable and not enough control. Problem of saving to SD card, need to send photos without stopping camera operation. Looking at making SD multiplexers. New projects include canopy measurement, air sensing, sound sensing like gunshots in forest or logging trucks where they don’t belong. Forest Hotspots for getting data out from tablets in the field. Using Zigbee, Xbee, Raspberry Pi, other technologies for transmitting via 2G, 3G, satellite. Usual approach is using a satellite dish which requires truck and power generator, they do data transmission at night when there is enough bandwidth. Also doing skychat between Wales and Africa sharing traditional dances from each culture. Way more talk about technical components and tools that I don’t know anything about! New technologies are cheap, need ruggedized cameras so buying those, but can DIY the rest. Will be doing more releases with Instant Wild as their new technologies are put in place. —– Loreto – EveryAware Consortium with lots of EU members. Trying to address problem of organizing. Combining objective and subjective measurements while enhancing individual awareness that they hope will trigger change in individual behaviors and generate policy pressure. Themes including social computing, participatory sensing, geo location and other aspects. Turning users into sensors, main difference is collecting the subjective as well as objective and linking the measured quantities with opinions, perceptions, impressions, personal experience. Question is whether access to these data change our understanding. Trying to understand how opinions emerge, shift, change in a population – complex systems plus opinion dynamics. They call it technosocial systems. New opportunities are understanding and controlling information dynamics, using web as a laboratory for social sciences, and raising awareness and participation. EveryAware platform – sensor box with GPS, accelerometers, temperature, humidity, noise, air quality, Geiger. Subjective part is tags, annotation, votes, comments. Uses smartphone to send stuff back and forth to servers for instant feedback. Different sensor boxes and smartphones for different focus. Also interested in web-only experiments with online games, etc. Case studies around Europe. Game Theory based experiments. XTribe web platform for social computing and experiments, xtribe.eu. Goals include standardized laboratory for social sciences and basin of attraction for recruitment, wide range of potential research areas. Games like blindate, Guess Where – How do you perceive maps?, City Race about strategies for mobility given limited information, compare with Google routing. Nexicon, word association and coordination. —– Ellie D’Hondt – Participatory Mapping City air pollution issues, affects a lot of people, good for learning laboratories. Responsible for 70% of greenhouse gas emissions. High potential for volunteer sensing of environmental parameters, people already carry mobile phones with potential for application to sensing. Goal is implementing citizen observatories focusing on noise, microclimate and air pollution. Main focus so far is noise, big problem in cities all over the world. Recent report from WHO that Europe loses 1M life years due to noise pollution, and it really gets under people’s skin. The problem is actual, representative, and possible. NoiseTube project with GPS smartphones, Internet connectivity, map server. App seems very similar to WideNoise, but samples every second and auto uploads if you have data plan, when you get home the tracks with noise measurements are ready to view, manual upload if no data plan. Use is mostly in Europe but being used worldwide by uncoordinated individual users. Projects starting up without their knowledge, using the platform for primary education in Lyons. Another application is coordinated grassroots campaigns. Coordinated is when people want good data, community organizing groups, e.g., in Antwerp where port leads to lots of noise. Rigor is important if policy is goal, you need something realistic that will convince authorities. Codesigned citizen science experiment to address concerns. Lots of noise mapping going on, but it isn’t sufficient. Worldwide issue, lots of European efforts. Large cities required to generate noise maps every 5 years. Put the info into propagation models to fill in gaps, e.g., with building canyons that retain/echo noise between buildings. Health norms say 50db during day under 40db at night, levels well in excess, and WHO norms just can’t be achieved. —– Cavalier – Being a Citizen Scientist Goals are raising interest and understanding of science, grow the ranks of citizen scientists, and encourage citizen involvement in research projects and policy discussions. Learned about citizen science at UPenn and focused on those goals in capstone project. Loss of Office of Technology Assessment problematic in terms of loss of public feedback on science policy. Too much prior sense that public is dumb and science is weary. Adult scientific literacy is very high in US, only second to Sweden, but youth science literacy is very low. Ideas around public engagement. Citizen science yields serious science. Initially it focused mostly on birders, also water quality monitors. Measurement calibration not the big issue, it’s recruitment. Not easy for would-be contributors to find a project. Started SciStarter to connect people to citizen science, considered one of Philly’s top 10 tech startups. Simple site, easy to use, focuses on what people want to do. What can I do at the beach or on a hike? They don’t create projects, they aggregate info, and they do heavy editing and approval to ensure quality. They then market the projects. Seems to be working! Mastodon Matrix Project saw doubling participation and that can be traced to SciStarter. SnowTweets saw 3x participation during the month when they were promoted. National media partnerships help, NBC News, Discover Magazine, riding coattails. New animated widget, Mission Impossible theming for project of the week on Discover Magazine which has 2M online readers. Recruitment services are free, also geographically-centric. Motivations to act – advancing research – you’re asking someone to give up something to do your project. What would make you stop what you’re doing and give up family time to participate? Examples of Firefly tracking, Belly Button Biology, BioCurious, mapping AEDs will provide information for emergency responders. Other motivations – civic concerns, money. Cheerleaders – NFL and NBA cheerleaders, using pop culture icons to promote science. All are professional scientists, they only get paid $35 game, so telling little girls that they need another career plan. Wide variety of project resources, part of the goal of SciStarter is evening out the playing field by showing everything in the same format. Important not to put out too little or too much information. Reinventing the wheel – happening too much. Rick Bonney a trailblazer in nature-based projects but also more broadly especially with respect to design and evaluation of citizen science. She is trying to advocate more policy involvement, e.g., office of technology assessment, often has participatory aspects. What came from her writing on that is a new network that is pilot testing technology assessment focused on biodiversity. Trying to establish what an OTA might look like – ECAST, museums, academics, and others in partnership. Policy issues is part of why OTA shut down. When there is direct deliberation and conversation, there is more similarity between political parties than people think. Metrics of interest? Haven’t gotten as far as it could – spikes with national media partners cover a project, so that is why partnerships with media are so important. —– Riverfly Partnership UK-based project drawing on bottom-up enthusiasm. Water quality monitoring for rivers, network of anglers, conservationists, entomologists, scientists, water course managers, relevant statutory bodies. Launched in 2007, concerned with protects river water quality. Using volunteer network as a trigger for statutory intervention, which rigorously monitors 3K sites every 3 years, less rigorous monitoring protocol but good enough to identify critical issues. Issues with local groups hoarding data, need to consolidate what they’re doing, but there is a local difference – 3 localized court cases where volunteers identified breaches in policy where businesses were depleting river resources. Strong and effective policy link, very bottom-up origination. Need a lot of help with technologies, central online facility, smartphone app, online validation, auto analysis and reporting, etc. Huge needs but little resources, major gap in technical expertise, but they know what they need from a functional requirements perspective. —– Wilson & Cundy – CERN@school, Langton Star Centre Focus is ionizing radiation, public has poor understanding of this and don’t understand the science, see it as more dangerous than it is. Langton Ultimate Cosmic ray Intensity Detector – LUCID – made for LHC and other particle accelerators, but can they be used for other purposes? They produce images, not just beeps like Geiger counters. Competition for space project to detect cosmic radiation, school kids used Timepix sensors to create winning project that will be sent up on satellite. Now applying for other purposes to visualize radiation. Medipix chips family of hybrid pixel detectors developed by CERN, see what particles you’re looking at from visualization, helps students understand what radiation is much better than beeps. Data from LUCID and CERN@school will be uploaded to GridPP (particle physics) to be made available for students to analyze. Cool collaborative product lets them learn about not only physics but also the computer science required to support this research. Architecture and requirements for design. —– Dumitriu – Normal Flora Project: Bacteria and Bioart Artist who works in unusual media, in between science and community. Long term project focused on unseen, unnoticed, ubiquitous bacteria, yeasts, and mold around us. Fascinated by bacteria, more bacterial cells in our bodies than body cells, more bacteria on your fingertips than people in the world. Focus is “how sublime is your ecosystem” not “how clean is your house” – these organisms are integral to our lives, we’d die without them. Crochet installation replicating bedroom bacteria, made collaboratively. Needlepointed onto a chair. Shows these images at hospitals as outreach and education, working with craft techniques makes topic approachable to little old ladies. Bacillus mycoides has a beautiful structure, looks like lace, found the bacterium cultured from different locations have different colors. Also does performance intervention art, microbiological, at Brighton Fringe Festival. Implanted agar into ground, which pulled up soil bacteria, then they had discussion around the way that bacteria communicate chemically. Kryolab collaboration with arctic bacteria center in Finland, was able to exihibit her strains of new arctic bacteria in the gallery, had to get a certification that they are not dangerous to bring them to UK for gallery installation. Had to ship arctic ice to gallery to give bacteria appropriate habitat, opened up conversation about climate change. Installations about bacteria scale free networks, cybernetic bacteria, infective textiles. Open lab at a lighthouse with homemade agar and culturing own bacteria, works with safe protocol for doing this, worked with microbiologist to develop that. Stains them and used them to make dress decorations. Embedded images of bacteria communicating in garments, because some bacteria change colors when it communicates. Staining period pieces to reflect on gentleman scientists. MRSA quilt experiments, based on idea of bacterium from her nose but wasn’t carrying MRSA. Textile pieces were inoculated with MRSA bacteria and then cultured them to grow the blue bacterium on the textiles, using turmeric as an antibiotic to prevent culturing in some parts of the textiles. Project to let people make own MRSA quilt pieces, then culture them. Working on a BSL 2 lab that is gallery-safe to cultivate pathogens to use in art, funded by Wellcome Trust and working with microbiologists. Was allowed into a secret lab and got to handle category 3 organisms, comfortable working with level 2. Has been recommended to become a registered microbiologist so she can do the work independently. —– Paulos – Hybrid assemblages, environments, and happenings For participatory culture Starts from Operation Moonwatch in 1956, thinking about technologies and human experience related to science. Star 2008ha, found by 14yo astronomy enthusiast – had access to more equipment than average person. But most of us have phones that are really little supercomputers with sensors, etc. Who participates in making visionary science happen? New challenges at this scale – environment, famine, healthcare, literacy, economy? Different strategies for addressing each of these through participatory projects. Concept of microvolunteerism, we know our neighborhoods best – quote from Elinor Ostrom about citizens having the right information more than bureaucrats do. Connections to DIY community, manifesto of open disruption and participation. Value of helping people be curious about our world and explore it in new ways. Innovation companies don’t care about SATs and skills, they want to know if you can brainstorm all the possible uses of bubble wrap. Need to rethink education, bridge laboratory and field site views to support health of cities. Interesting trend in the rise of the expert amateurs, not just citizen science, moving from proprietary innovation to populist innovation. Scientists must abandon their white lab coats, including the invisible ones they wear in their heads. Living environments lab, variety of projects. Citizen science is not just valuable for science, but also kindling curiosity and sense of wonder. Value for literacy, data, grassroots participation, awareness. Using mobile technologies for measuring air quality and water quality, found that people returning monitoring devices said that they changed their behavior based on their awareness of air quality, seeing data changed the way they saw things around them. Once you expose people to new info, they change behavior. Opening the landscape beyond personal sensing – mobile infrastructure, indoor fixed air quality, placing them in public to see what people did. Sensors on street sweepers, cover whole city very rapidly, good for data over time. Gave sensors to community, people had different strategies for installing them, also got calls from the police because to them anything that is a technology but not a cell phone is a bomb. Also trying to drive cost down for sensors to give them to 100Ks of people, critiquing sensors themselves, other ways of interpreting data, e.g., instead of shortest route, cleanest air route. Shirt that shows data about air quality, breathe/don’t breathe sign, ticker about health value. And spectacle computing, small sensors on balloons that glow based on particles and gases, sometimes you don’t want people to miss the computing, you want them to notice and participate and spread the word. Micro volunteerism – 42 seconds at an intersection, what can I do? Developing own kinds of platforms, stuff like EpiCollect and ODK. Develop campaign-based efforts to investigate and manage projects from bottom up.
My notes from the first day of the London Citizen Cyberscience Summit (#LCCS2) are pasted below; the full program is online at http://cybersciencesummit.org/35-2. Note that these notes are just that – my own personal notes on the talks. Apologies for bad formatting; Posterous is really terrible for posting from a mobile device if you don’t do it the way that they expect you to!Ordinarily I just send these to the PhD listserv at Syracuse, but I think a much broader audience could benefit from access to these notes. It’s been a really interesting event. I am very pleased to have been able to attend because the exposure to a much broader range of participatory science projects, initiatives, and interpretations has been just great. —- Francois Grey – coordinator of Citizen Cyberscience Center @ CERN, introducing program. Citizen cyberscience relies on Internet and web to broaden participation, expands beyond prior audiences. Science is too important to be left to scientists alone. The public wants to participate actively in science, not as a passive consumer. Especially important with respect to politics, journalism, and more so in science. Summit because it’s more of a grassroots effort, but that means reinventing the wheel because people are not aware of what others are doing. Second idea is being able to bring together citizens and scientists, looking at how it can be transformative to individuals. —– Silvertown – Evolution MegaLab and iSpot Citizens pay for all our science, whether we allow them to participate or not – yet another reason to incorporate them. Lots of interest in citizen science, still getting a sense of what all the flavors are. Sharing experiences with a couple projects he’s been involved in. Thinking about what people know and how to work with what they know. 3 types of crowd knowledge: wisdom of the crowd – everyone has an opinion on and can vote, each vote has equal weight; wisdom in the crowd, opinions weighted by expertise and more diverse audiences are better; wisdom from the crowd, collective knowledge and interactions make the whole more than the sum of the parts. Corresponding types of network topologies: hierarchical, radial, interconnected. Evolution MegaLab – hands-on part of a larger series of projects. Polymorphic snails with different colors and banding patterns. Already studied by population geneticists since 1920s, hypothesis that polymorphism had changed in response to global warming. Tendency in 1970s for more light colored snails in southern parts of Europe. Climate has warmed more than 1.3 degrees C in Europe, so has this affected the snails? Temperature warms the snails inside and can kill them if it gets too high, and yellow snails are more reflective of sunlight than brown or pink ones. Gave people a variety of explanations on the website, gave them layered access to as much information as they wanted. Major advertising campaign in 14 languages, operated as franchise in each country. Took advantage of 80 years of study, digitized all the data on 8K populations and mapped them, can drill down to individual populations so you can see who collected data and when. So they can direct people to return to the same sites. Translation was quite a task. Replicated data entry sheets online, fill in data, and get immediate feedback looking for data within 5km for comparison. Verification an issue with everyone from kids to retired professors – how to know if people are IDing the right species? Online quiz for training and weighting data – original plan – what really happened is that most people didn’t take the quiz and it seemed to be a rainy-day classroom task. Found out of 2K-3K responses that they got 62% right in first try. Location-specific field guides for disambiguation. 33% able to tell adult/juvenile, 84% got adult subspecies right, 95% scored banding correctly, 94% scored yellow correctly. Data cleaning showed that juvenile C. nem might be mistaken for adult C. hort. Cleaned data came out to 3K samples. Very expensive to get public to do this, not a cheap way to gather this many samples, but you get public engagement out of it as well. Results – MegaLab data different from historical data, public collect in cities where they live, whereas professionals would collect in countryside. Big gap in data from France. Statistical comparison saw no heterogeneity, but 10K population showed that % yellow didn’t really increase over time for full population, but significant increase for populations located in dunes. Behaviorally, if it’s too hot, the snails move away under vegetation, but that is less of an option in dunes so there was change where it was forced. 3 lessons from MegaLab: difficult to evaluate skill, indirect (quiz) evidence can be used in verification, creating a self-help network among users might have improved data quality. iSpot – more of a tool to help people identify species and put names to tags, key in ecology and biology. Part of OPAL, lottery funded. Goal is creating new generation of naturalists, used to be big in England but there’s a sense that this has been lost and there’s no education at any level to help people learn to ID things. Topology of network – has expert-based networks, but because it covers all species, no one is an expert of everything, so you get a synergistic network where everyone is an expert and a beginner at the same time, only as hierarchical as it needs to be. Uses reputation and badges to show expertise. Can gather albums, get points for getting names right, move to other groups and start to learn from them, and move up the learning curve. Some people joining societies and becoming specialists, very successful use of algorithms to show collective expertise for verification. Created a virtuous circle and earn reputation, people are gently moved up knowledge curve. Highly successful, had no idea how or whether it would work. 36K submissions without a name, within a half an hour 38% get a name, 54% in an hour, and it’s very scalable. Reason is the nature of the network. Now the question is what to do as it becomes global. About 100K observations at the moment, question of how you globalize expertise, but the answer is already there in the network. Someone offers an ID and qualifies it by saying that there maybe other species in a different location – experts know what they don’t know, won’t stray outside of their expertise. 3 lessons from iSpot: reputation system is key, is increasing, and the recognition of it gives scope to increase through learning; multiple roles is very important, helps it becomes learning environment; experts are aware of what they don’t know. Citizen science is as much about the sociology of science as the domain science. Qs: not many repeat observations, though some set out to see every grasshopper or tree. Major costs? At the end of the day it’s the staff time, had to handcraft everything to create things that were adequately specific. Cheaper ways of doing it now. —– Tokumine – No citizens, no science. Works for Vizzuality, specializing in data visualization and analysis. Talking about people power, member of Citizen Science Alliance. Worked on Old Weather project, using historical data for climate models, and Planet Hunters to find planets around distant stars. Old Weather: distribution of weather stations and so on leave big holes in knowledge of historical weather data. Royal Navy kept logbooks all over the planet, but in a format that is hard to liberate, script is difficult to read, lends itself to humans doing transcription. Users enter data, coordinates, weather details like wind speed, temperature, and incidental details like events that happen on board. In a year, 24K+ volunteers have transcribed over 800K logbook pages. How to motivate them? Topical and interesting, captures the imagination. Site is easy to understand, clear call to action, explanations of purpose. Gamification as well, earn badges to become “captain,” and people get quite competitive, so those elements drive some participation. Observations on forum about infectious feedback, people are really into it, huge teams of people are engaging with each other. 255 ships’ logs complete. Important to give participants immediate feedback, e.g., statistical feedback. Needs repackaging of data and feeding it back to them in a useful form. Animations of the ships traveling across the seas and showing temperature, really brings it alive to people. Visualiztion that shows tracks along with event data. These are really important to motivating people. Event analysis, shows that ships are very sad places (deaths at sea), most popular events included sports like cricket. Allowing people to contribute flexibly are important, there was more variety in ways people contribute than they expected. Showing preliminary results as feedback is really valuable for motivating. Individual transcriptions 97% accurate: out of 1K logbook entries, 3 lost because of transcription errors, 10 illegible logs, 3 are errors in logs themselves. Impressive given how hard it is to read handwriting. Planet Hunters: uses NASA Kepler data, looking at light coming from a star over time, if you’re looking for planets, blips in light curves are how you identify them. Computers are good at detecting these, except in noisy data, which humans are good at. People identify potential transits in data, over 10M classifications in 18 months. Who wouldn’t want to discover a planet? Make it really easy to start, show scientific results, give coauthorship to discoverers. Another way to get incredible results is to use traditional media, BBC Stargazing coverage really drove participation up very quickly. 3 points: interesting problems, real research, respect for contributors. CSA offering support to new projects. Qs: any chance for naming after discoverers? Touchy subject, but there is potential. Highlighted that there is an exchange, not just looking for cheap labor, this tension may be one of the big points of making it mutually beneficial. How did you explore motivations of participants? Understanding motivations can be done several ways, A/B testing presentation and messaging, also through forums which seemed too free form but valuable way to engage. How much are users involved during project design? Dictatorial approach, believe that project team are the people who can create the best product, once there is a first release, there’s an element of evolution based on user feedback. Statistical validity is important, so pipelines of data have to be incredibly clean. —– Dunn – Community-sourced structured metadata of English place names
Kings College, Digital Humanities Mass-digitization of data. Place names are complicated and dynamic, they change over time. They are attested in documentary resources, e.g., in archives, but these are diverse and difficult to get to. The are also contested, disagreement over place names and their etymology. They are documented in a variety of ways and are also researched. Project is digitizing a survey of English place names. Enormous and enormously complicated document, not just in subject matter and in ways it is structured. Each county has own editor so structure changes from volume to volume because guidelines are loose. About 80 years of data for 32 counties, 86 volumes, 6157 elements, 30517 pages, 4M individual place-name forms, uncounted bibliographic references (a lot!) Survey is aggregation of a lot of different documentary evidence. In 2010 a pilot used NLP to create XML records, great for getting volumes out there in machine-readable form, but they want to do more than that, harmonize and enrich it. Current work is to markup the hierarchies of place names that occur, linking and exposing the data. Will be published as RDF-enabled gazetteer, point-based historic geographic reference with authority of official commissions. Points, polygons, and lines are problematic, little data on geographic association of place names, points are arbitrary dependent on scale, administrative geographies change over time, and even natural features can mislead, e.g., rivers move over time. Hope is to integrate with other data sources. Need crowdsourcing to correct errors and omissions in NLP and OCR, validate output with local knowledge, add geographic data where missing, identify crossovers with users of other sources, enrich point data with raster and string data, learn more about what communities are interested in. Qs: thought large part of England had Scandinavian names? Most strongly felt in Northeast. Did names change with Norman conquest? Yes. —– Arazy – Citizen Science a Motivational Perspective Context of research: HCI, focuses on knowledge sharing in a variety of online settings; organizational perspective – to what extent can peer-production models be applied in organizational settings? Study approach is outside observation, participation. What’s in it for the dude? Studied Stardust@Home, classifying images of collector plates from NASA’s Stardust spacecraft, searching for interstellar dust particles. RQ: what are motivational drivers of quantity and quality of contributions made by volunteers. Quantity is easy to measure, but how does motivation affect quality? Differences from open source, goal there is solving their own problems, rational economic decision argument, not the case for citizen science. Can’t assume the motivations from open source or Wikipedia are the same a those in citizen science. Motivation framework from social movements theory: collective motives, identification with the group. These have to do with cost-benefit motives and norm-benefit motives. Relationship between quality and quantity: cost-benefit suggests tradeoff between the two but collective/identification orientation suggests both increase together. Cost-benefit analysis shows opposite of expectations – social benefit increases quantity, reputation increases quality, thought there would be negative influences of social benefit on quality and reputation would have negative effects on quantity. This depends on the project. Self-actualization increases both quality and quantity. Fundamental differences between cost-benefit and self-actualization models. Quantity and quality differ in antecedents,explains prior failure to find significant effect for collective and identification motivates in OSS and Wikipedia. Overall, self-actualization is more important. Insights and recommendations: pay special attention to collective, identification motives. Be careful with benefits model, incentivizing one outcome may cause the other to suffer. —– Munyaradzi – transcription of bushman historical text Bushman people of southern Africa – earliest inhabitants of Earth, unique worldview, most language speakers are dead. Digital Bleek and Lloyd collection contains notebooks, art, and dictionaries that preserve encoded bushman culture. Text contains complex diacritics (over 137, more still being found) with no Unicode representation. RQ is whether volunteer thinking can be used to crowd source the translation, and then how does volunteer thinking compare to machine learning techniques? Also whether cell phones can be used for this. Using Bossa framework – OSS framework for volunteer thinking projects, minimizes effort of creating and operating projects, supports variance of volunteer skill. Near completion of segmentation and transcription application for the project. Text segmentation is challenging aspect of preparing images for analysis, e.g., diacritics under a character might get cut off by lines. Transcription application shows the image, type in the representation, convert to latex and see the translation – have found ways to create these representations of the diacritics that way. Goals: generic solution for other historical applications, preservation of Bushman historical texts (important to linguists), make text searchable, reprint text into books, text-to-speech. —– Wu First and only Chinese volunteer cit sci project in mainland China, focus on volunteer computing and volunteer thinking, CAS@home. Different groups using this infrastructure, so they made a task management interface for scientists. Projects in high energy physics, clean water filtering through nanotubes, infectious respiratory diseases involving proximity contact network, protein structure prediction. Huge Chinese population, 500M Internet users, most using mobile phones, enormous potential for harnessing volunteer computing cycles. Chinese contributors are 90% male, mostly students in IT professions. Lots of swift growth, worth over $2.2 if the CPU time we were purchased from Amazon EC2. —- ForestWatchers Tropical forests provide habitat for most of the world’s terrestrial plant and animal species, deforestation is 20% of greenhouse gas emissions. Project started at last year’s CCS. Collaboration with Brazil’s space research agency as they are leader in deforestation monitoring, responsible for detection system, trains monitoring teams, supports open data policies. Building PyBossa framework demo for micro-tasking, show an image to volunteers, let them examine it over time, ask if they think it is a deforestation area and if so they mark the area, then the experts evaluate to see if it is so. Short-term goal is having a working alpha by June. Qs: relying only on experts? Will compare volunteer data to expert gold standard, evaluating their ability to do the task is a primary goal. —- Chen – Quake catcher network @ Asia ASGC is context for development – eScience collaborations, tech development, dissemination and training. Want to support/stimulate eScience collaborations, focus on earthquake sensing for disaster mitigation. Taiwan is in convergent plate boundary zone between Eurasia and Philippine Sea plates, lots of earthquakes. Earthquake simulations take a lot of computing power. Most of talk focuses on the seismic research. Want to use citizen cyberscience for educational initiatives, focused on classrooms, but mostly just volunteer computing. —– Ala-Mutka – e-Infrastructure and citizen science EC program officer, describes focus of e-Infrastructure funding projects. One goal is seamless access, use, and reuse of data. Geant 2020 is European communication commons: deepen relationship between science and society, reinforce public confidence, promote science education, make scientific knowledge more accessible, informed citizen engagement. What can e-Infrastructure do for citizen science and vice versa? Data collections infrastructure, QA mechanisms, human computing resources, computing/science resources, scientific software and innovations development. To date they support a lot of open access efforts, tools and models for citizen science (Gloria – network of practitioners?, Discover the Cosmos), enhancing awareness. Qs: ordinary guy running 2 citizen science projects – how can he get access to funding and HPC? —– Taddei – Citizens, Science, Education, and Technology: new synergies to be explored IT is developing fast, open source hardware allows hacking cell phones to create new scientific instruments. Volume of scientific publication increasing on a log scale. Reinventing Discovery – Michael Nielsen – already outdated, how do you keep updated on the evolution of science? Education is evolving slowly. Can we imagine innovative solutions? The rules are changing. Biology Letters – Blackawton bees, all the first authors are primary school participants, last author is a UCL scientist. Open source citizen science a focus – not just open source but also open wetware. 14yo developed first line earthquake detection for Chile. Games like Foldit not only advance science, but also methodologies and education. Learning through research – main difference between prior and future models is how knowledge production is catalyzed. Instead of being pushed by teachers for years, people can pick an interest and move it forward much more quickly and with engagement of society. Scientific understanding progresses through feedback between experiments, analysis, and models. In many science contexts, students or citizen scientists only engage people in one part of the research – just crowdsourcing or crowd computing. Wants to develop a citizen science of citizen science. Open questions for citizen science: top-down, bottom-up, or co-constructed. Who will benefit? Science, companies, contributors, society? How to maximize learning through research while contributing to CCS? How to do experiments, analyze and model CCS? Necessary and sufficient conditions for advancing as identify field? What is optimal division of labor between man and machine? Citizens and professionals? Chess of a metaphor for the future – Kasparov being beaten by computer, if your job is chess, get ready to find a new job. Game of Kasparov against the world, 15yo worked with software for collective intelligence and challenged Kasparov so much he never wanted to repeat that game. Chess is not a simple task, and collective intelligence can accomplish complex tasks, but it has to be managed well. How can citizens collectively maximize the synergies between citizen cyber science, OSS, and empowering knowledge creation environments? —– Pintea – Community based monitoring of chimpanzees and forest habitats using ODK (Jane Goodall Institute) Mission is protecting chimpanzees and their habitats. Community-centered philosophy, community manages own resources. TACARE project focuses on conservation with local communities, numerous related goals related to ownership of projects. Started from participatory mapping project in 2002, found need to incorporate indigenous knowledge in their planning around Gombe National Park. Led to village forest monitoring, valuable not only for providing input but also reporting. Trained monitors learned GPS, were assigned village government, they provide tools and small stipend. Collected 36K observations. GPS had some problems, limited data points captured, relies on GIS which also had issues. In 2009, ODK + Google tools to build systems for forest monitoring, testing on multiple devices. Villagers store data on mobile phones, upload data when they visit town for other errands every couple of weeks. Very difficult to train people in the field until they used ODK, this was a huge improvement to be able to get people up and running on it quickly. Google Android ODK training in Tanzania brought together villagers, leaders, and developers. Incorporating the monitoring into ongoing JGI projects using ODK, multi-million dollar projects, reporting a variety of data points, training via train-the-trainer either onsite or online. Results include detailed information around chimp habitats, not just chimp presence but other wildlife, snares and traps, threats to chimps. Suspected forest monitors knew about this before but didn’t have the tools to report the data, lets JGI ask new questions and refocus interventions. Collaborators in REDD project in Tanzania collect more scientific data, and focuses not on village land but public land. Other examples from Uganda where chimps still survive in degraded habitats. Locals can collect data for REDD credits that give them incentives help preserve the habitats. —– Parsons – Global Canopy Programme Working in Guyana; previously did phenology work with Woodland Trust and project called Nature’s Calendar, which started with digitizing a box of paper records. Slider maps of horse chestnut fruit ripening and swallows arriving, some data go back to 1700s. Oak first leafing is now happening 2 weeks later than it was 60 years ago. Phenology used in reporting for IPCC. Phenology important to daily life. Also had a project called Ancient Tree Hunt, oaks have 900-year life cycle, 300 years each of growing, then resting, then dying; dying stage is when they are considered ancient. Have had over 75K ancient trees mapped, have trained verification volunteers. Each tree has its own web page, some have multiple photos over time, so getting phenological biography of the tree, or simply indicate that you have visited this tree, so they know how many people have visited them. Shows a tree from Henry VIII’s hunting grounds on an old map, and then current location on satellite map where it’s now in the middle of a city. Now working Global Canopy Programme, MRV – monitoring, recording, and verification. Focus on community management of their resources, policy impact as partners, technology to help record data. Project in center of Guyana in the rainforest, lots of interest from policy makers. Habitats include mountains, rainforests, and savannahs. Recruited and paid 32 contributors for 10 days/month, village leader has to get involved or nothing happens, need total buy-in from local community. Capturing data on paper, on farms, food, river, wetlands, fish, hunting, building, logging, savannah, and social activity in villages. Introduced them to handheld devices, using a variety of smartphones. Trained project leaders, need rugged phones and tested them in difficult conditions. Youngsters really like it and already know Bluetooth, but older people have never seen these devices. One guy’s fingers were so dry from working in the field that the touch screen wouldn’t register his touch! But the older people really want to learn the technology. Using ODK, download forms, collect data, upload it, analyze and validate it, map it. Simple interfaces but numerous steps. They leave the phones with villagers to assess the device usability and durability. Next goal is using their data collection for ground-truthing satellite data on deforestation and forest degradation. Part of community forest monitoring working group, putting together an experience blog of organizing. Needs help setting up satellite Internet access point. Q: what do villagers do with data, or is it just for you? Collecting data that they can use for managing their own communities, this is why village leader was so enthusiastic about it. Issues of jealousy with who gets paid and gets to do the work? Monitors selected by village council through democratic system, some questions around who gets paid, but data types being collected were inspired by collaboration with the communities so very driven by community interests. Community monitors are being verified and selected locally, a lot of awareness in community that this is beneficial for managing the community so that is alleviating issues of jealousy. —– Lewis – Congo Basin Citizen Science Heartbreaking situation in Congo Basin: deforestation, bushmeat trapping, abuse of local people. Local indigenous people don’t mind sharing resources but don’t want tombs of ancestors bulldozed, destruction of freshwater sources, loss of medicinal trees, and especially the trees that support a special delicacy caterpillar require – they taste like meaty prawns, have a high commercial value. Worked with hunter gatherers to find out what trees they most want to preserve. Set up ugly Excel spreadsheet, but there are problems with analysis and accuracy. Worked with a company to set up monitoring with icons developed with the locals, who don’t speak European languages and are not literate. Have been using these on military grade devices since 2006, takes 10 minutes to learn, and only poor-sighted elders have a hard time seeing the icons, but then they get partnerships between youth and elders to do the mapping. Screens show social groups – so they can indicate who cares – then is shown the kind of resource (e.g. forest spirits) and then they choose a subtype, it beeps, and they know data are recorded. Now they have records of sacred trees, caterpillar trees, medicinal trees, and cemetery sites, and the forestry company is now able to protect the locally valued trees. The method has spread like wildfire because it’s so effective. Allows peaceful communication and meeting all interests via maps, which predates writing by a long time. After forest company accepts trees for preservation, the locals go back and physically mark the trees to make sure they are not harmed accidentally. Lumber company now uses this approach for all projects. Have also done some modifications to evaluate illegal logging elsewhere. When they visited people, they showed icons and asked what they meant, refined icons with collaborative feedback, locals also provide feedback about other features they want or need. Iterative development with localized input. Early project challenges involved consent so they spent a lot of up-front time explaining before asking for consent which is a process and not a contract. Worked to reduce issues with accessibility of information, training and support, self-definition of roles and resources, community protocol and ceremony that defined who would do what, including withdrawal of data and consent. Key challenges: time and technical support, developing long term sustainable data collection strategies, conflicts of interests among some participants, and difficulties ensuring effective advocacy due to being ignored, corruption, and inertia. Recent win: locals recognized value of these approaches, came to them and asked for software to track poachers so law enforcement can address issues more effectively. Initial gadgets robust but very expensive, need to find cheaper hardware options. Hackfest challenge is to design portable device that can meet specific requirements, e.g., accurate geo-ref under rainforest canopy, withstand heat and humidity, disguise its purpose, be able tolerate a week without charge and before upload, ability to update software quickly when needed, etc. Another challenge has to do with climate change and mining concessions, hacking industrial sensors so they can live in landscapes and record changes for long-term monitoring of changes, develop analytic tools for visualizing and analyzing results themselves, and building lobbying partnerships to build for action. Third challenge is developing intelligent maps: new analytic and visualization tools, experimenting with tablets for recording and visualizing. Data collection devices now reality, but marginalized and poor remain sidelined. Analysis dominated by scientists, need to develop accessible analytic tools if citizen science is to reach potential. Methods for motivating and ensuring effective participation resolved for some user groups, but those most indeed of support still largely excluded, rural, semi/non-literate, women, urban poor. —– Haklay – Kickoff of ExCiteS Began with noise monitoring, used for environmental justice. Concern over air quality, looked at ozone sampling using litmus-like sheets, dust sampling, and Leicester University collected leaves because you know where you got them and how long they were out, so you can find out how much copper is in the air because it’s magnetic. Also put up diffusion tubes for mapping the air quality. What makes it extreme citizen science? Who can participate – everyone can participate, not just educated people with domain knowledge. Moving locations from populated rich parts of planet to everywhere. Moving people from just data collection and entry to shaping the problem and analyzing data. Levels of participation, from basic crowd sourcing (citizens as sensors), to citizens as interpreters, to participation in problem definition, to participation in entire process. Goals of ExCiteS include development of theoretical and methodological frameworks, developing core technology platforms, usability of GIS and related technologies particularly for non experts, etc. Coming projects include adaptable suburbs to learn about how suburbs are changing; intelligent maps like those in the Congo, spatial mobile games for citizen science; Google Earth Tours and communicating geographical concepts; OSM and user-generated GIS data; EveryAware to enhance awareness through social information technologies using mobile technologies to collect, analyze, and visualize local environmental info, and analyze changes in behavior based on the info.