Participatory Mapping in Congo-Brazzaville (Part 1)POSTED BY MICHALIS VITOS ⋅ JUNE 18, 2013 ⋅ 2 COMMENTSFILED UNDER CONGO-BRAZZAVILLE, DATA COLLECTION SOLUTIONS, EXCITES, MOBILE DATA COLLECTION, PARTICIPATORY MAPPINGExCiteS - Field Trip MapExCiteS – Field Trip MapOver six weeks from the end of March to the start of May 2013, five ExCiteS members – Julia Altenbuchner, Gill Conquest, Jerome Lewis, Matthias Stevens & MichalisVitos – travelled to the Republic of the Congo, a.k.a. Congo-Brazzaville. We spent the majority of this time in or near the rainforest of the Sangha and Likouala regions, in the North of the country. We visited very remote settlements deep in the forest, only reachable by backbreaking 4×4 journeys over tiny dirt roads or the occasional boat ride.This expedition is part of one of the ExCiteS projects, the goal of which is to develop a system of participatory monitoring for forest management – specifically the social impact of logging. Concretely, we want to enable local people to give direct feedback on the behaviour of the logging companies who control the areas in which they live through the IM-FLEG approach (Independent Monitoring – Forest Law Enforcement and Governance). Until now, these communities have seen little benefit from the logging that takes place in their localities (despite the timber industry being the second most important source of income for Congo after oil), have had little say in how the logging concessions are managed, and have no recourse if loggers destroy resources on which they depend.ExCiteS - Logging in the Congo-BrazzavillePlanks of wood at local sawmillWithin this project we, the UCL ExCiteS group, in collaboration with the local watchdog, sought to capitalise on the introduction of the new EU FLEGT (Forest Law Enforcement, Governance and Trade) law in the Congo. The Congolese FLEGT Voluntary Partnership Agreement accords a number of new rights to local communities, and places obligations on logging companies to respect the local population and the resources they use. However, unless it is accompanied by a strong system of enforcement on the ground, the legal framework itself is unlikely to make a big difference to local people’s lives. To address this concern, ExCiteS was contracted by the international NGO Forests Monitor and their local watchdog to develop an application that members of local farmer and hunter-gatherer communities could use to map the locations of their important resources, make observations concerning any evidence of illegal logging activity, and then communicate this information to IM-FLEG. By allowing locals to make these observations themselves, this system will not only benefit from their extensive knowledge of the forest environment, but will also serve as a means of empowering them in their relationships with other forest stakeholders.OI-FLEG - Decision TreeOI-FLEG – Decision TreeOur activities during this trip touch upon all aspects of the overall ExCiteS mission – developing methodologies, tools and platforms to support communities anywhere to participate in scientifically valid data collection and analysis.With regards to tools and platforms, an important goal of this trip was to do a thorough field test of our newly developed data collection and transmission platform for Android smartphones. Like the app discussed here, the user interface of the data collection side of this platform is built on the concept of pictorial decision trees – to deal with literacy issues and bridge language divides. However, unlike the earlier app our new platform has been developed entirely in-house and does not rely on a third party system like Open Data Kit or EpiCollect. During this trip we wanted to identify any technical issues with the software itself, as well evaluate its usability.As most of the forest people we visited had no experience with this kind of technology, the methodology to introduce the smartphones and the software was very important. The approach we used was adapted from similar projects conducted previously in the Congo Basin (Lewis, 2012) and we had plenty of opportunity to refine it further in response to local conditions.ExCiteS - Introduction by laminated flashcardsJerome Lewis introducing the pictorial iconsUpon arrival in a community we always began with a thorough introduction of ourselves and the project, first to the local chief or elders, and after having received their consent, also to a wider assembly of community members. Rather than moving straight to showing people the phones themselves, which may have been too abstract as a starting point, we would introduce them to the decision tree icons using a pack of large laminated flashcards. To ensure that each image was clearly understood (since some hunter-gatherer groups have no culture of drawing), we would ask the assembled crowd to guess what each image represented – this also had the effect of making the exercise more fun. If there were any images that were unclear, or situations that were missing, we would make note of suggested alterations or additions.Next, we would introduce the phones and demonstrate how to navigate the decision tree. Once people seemed comfortable with the way to “tap” the images and move between screens, we would ask them to find specific icons in order to familiarise them with the different options available. From prior experience we knew it would be important to contextualise these activities to make sure people understood what they were doing and why. So once we had trained a couple of people to use the phones we would ask small teams of men and women to take us for a walk in the surrounding forest so they could use the app to do some actual mapping. Throughout this process we kept listening and asking for suggestions for possible improvements.ExCiteS - Users Using the Data CollectorParticipants using the mobile data collectorUpon returning from community visits many suggestions were immediately incorporated in new versions of the decision tree, which were then used in subsequent visits. This is part of our effort to evaluate and improve usability aspects of the the data collection tool, both on the level of the content, namely the decision tree and images it consists of, and the level of the app itself (e.g. control flow). This participatory, iterative design process is an integral part of our methodology.
In some cases, the participants would want to volunteer in a passive way, as is the case with volunteered computing, without full understanding of the project as a way to engage and contribute to a scientific study. An example of this is the many thousands of people who volunteered to the Climateprediction.net project, where their computers were used to run global climate models. Many would like to feel that they are engaged in one of the major scientific issues of the day, but would not necessarily want to fully understand the science behind it.
LHC@home is a distributed computing project for particle physics based on the Berkeley Open Infrastructure for Network Computing (BOINC) platform. LHC@home consists of two applications: LHC@home Classic, SixTrack, which went live in September 2004 and is used to upgrade and maintain the particle accelerator Large Hadron Collider (LHC) of the European Organization for Nuclear Research (CERN), and LHC@home 2.0, Test4Theory, which went live in August 2011 and is used to simulate high-energy particle collisions to provide a reference to test the measurements performed at the LHC.The applications are run with the help of about fifteen thousand active volunteered computers processing at a combined more than 7 teraFLOPS on average as of December 2011. LHC@home uses idle computer processing resources from volunteers' computers to perform calculations on individual workunits, which are sent to a central project server upon completion. The project is cross-platform, and runs on a variety of hardware configurations. Test4Theory uses VirtualBox, an x86 virtualization software package.
The second level is ‘distributed intelligence’ in which the cognitive ability of the participants is the resource that is being used. Galaxy Zoo and many of the ‘classic’ citizen science projects are working at this level. The participants are asked to take some basic training, and then collect data or carry out a simple interpretation activity. Usually, the training activity includes a test that provides the scientists with an indication of the quality of the work that the participant can carry out. With this type of engagement, there is a need to be aware of questions that volunteers will raise while working on the project and how to support their learning beyond the initial training.“More than 2,500 volunteers sorted through nearly 14,000 supernova candidates between April and July 2010, Smith and colleagues report in a paper submitted to the Monthly Notices of the Royal Astronomical Society. Citizen scientists correctly identified 93 percent of the brightening objects, with no false positives.”AboutWelcome to Planet Four, a citizen science project designed to help planetary scientists identify and measure features on the surface of Mars . . . the likes of which don’t exist on Earth. All of the images on this site depict the southern polar region, an area of Mars that we know little about, and the majority of which have never been seen by human eyes before!Figure 1. HiRISE image is ~1 km across. Spiders and fans are visible.Figure 2What am I looking for?We need your help to find and mark ‘fans’ and ‘blotches’ on the Martian surface. Scientists believe that these features indicate wind direction and speed. By tracking ‘fans’ and ‘blotches’ over the course of several Martian years to see how they form, evolve, disappear and reform, we can help planetary scientists better understand Mars’ climate. We also hope to find out if these features form in the same spot each year and also learn how they change.So how do these ‘fans’ form?Rather than measuring days or months, the Martian year is indicated by the solar longitude, Ls. The year begins at Ls = 0, which is the first day of spring in the northern hemisphere and the first day of autumn in the southern hemisphere.Planetary scientists don’t know exactly how ‘fans’ and ‘blotches’ occur, but many believe that during the autumn a seasonal layer of carbon dioxide ice, otherwise known as dry ice, forms on the southern pole. In the winter, (beginning at Ls = 90) this layer transforms into translucent slab ice. Once spring arrives, (Ls =180) sunlight is able to penetrate and warm the ground below, causing the ice to sublimate (turn directly from ice into gas) from the bottom.This sublimation causes gas to become trapped below the ice layer under increasing pressure. When a crack or a rupture develops, the gas bursts, not unlike a geyser, out of the opening carrying along loose material eroded from the ground. When the gas and loose materials reach the surface of the ice they are often blown downwind of the vent in fan-shaped deposits, as shown in Figure 2. If there isn’t any wind the materials aren’t blown, but rather drop straight down forming a ‘blotch.’In the summer, (beginning at Ls = 270) the carbon dioxide melts and the ‘fans’ blend back into the surface material and are no longer visible. This annual process begins again in the following autumn and slowly erodes channels in the ground. These wide, shallow channels, generally less than 2 meters deep, are known as ‘spiders,’ though their technical name is araneiform.‘Spiders’ are visible in the winter when ice is draped over them, but when the terrain is ice-free in the summer, we can see that the ‘spiders’ are actually channels carved into the surface of Mars. Figure 3 shows the surface of Mars transforming from the spring at Ls = 181.1 to Ls = 325.4, which is mid-summer.Figure 3. Timelapse sequence of a spider initially covered with ~1m of ice (upper left), to ice-free (lower right).Where do the images come from?The images on this site come from the HiRISE (High Resolution Imaging Science Experiment) camera on board the Mars Reconnaissance Orbiter. HiRISE can image Mars with resolutions of 0.3 m/pixel (about 1 foot), resolving objects below a meter across.Why do you need our help?There are far too many images for a group of scientists to get through alone and computers are just no good at detecting the features we are trying to mark. The human mind is far superior at analyzing images with the complexity of the Martian surface!Your markings will be collected together with the markings made by other volunteers on that same image. Taking an average of these markings, we will produce an extremely reliable map of the ‘fan,’ and ‘blotch’ features on the surface of Mars and the first large scale measurement of wind on the planet!
Each image you will see is a tiny tumour sample from a huge dataset. Help our scientists to accelerate the analysis of this data by identifying the coloured sections of the image using our prompts, and bring forward the cures for cancers.
The more we know about how certain proteins fold, the better new proteins we can design to combat the disease-related proteins and cure the diseases. What is protein folding?Folded up Streptococcal Protein Puzzle (+) Enlarge This ImageWhat is a protein? Proteins are the workhorses in every cell of every living thing. Your body is made up of trillions of cells, of all different kinds: muscle cells, brain cells, blood cells, and more. Inside those cells, proteins are allowing your body to do what it does: break down food to power your muscles, send signals through your brain that control the body, and transport nutrients through your blood. Proteins come in thousands of different varieties, but they all have a lot in common. For instance, they're made of the same stuff: every protein consists of a long chain of joined-together amino acids.What are amino acids? Amino acids are small molecules made up of atoms of carbon, oxygen, nitrogen, sulfur, and hydrogen. To make a protein, the amino acids are joined in an unbranched chain, like a line of people holding hands. Just as the line of people has their legs and feet "hanging" off the chain, each amino acid has a small group of atoms (called a sidechain) sticking off the main chain (backbone) that connects them all together. There are 20 different kinds of amino acids, which differ from one another based on what atoms are in their sidechains. These 20 amino acids fall into different groups based on their chemical properties: acidic or alkaline, hydrophilic (water-loving) or hydrophobic (greasy).Unfolded (and unstable) Streptococcal Protein Puzzle (+) Enlarge This ImageWhat shape will a protein fold into? Even though proteins are just a long chain of amino acids, they don't like to stay stretched out in a straight line. The protein folds up to make a compact blob, but as it does, it keeps some amino acids near the center of the blob, and others outside; and it keeps some pairs of amino acids close together and others far apart. Every kind of protein folds up into a very specific shape -- the same shape every time. Most proteins do this all by themselves, although some need extra help to fold into the right shape. The unique shape of a particular protein is the most stable state it can adopt. Picture a ball at the top of a hill -- the ball will always roll down to the bottom. If you try to put the ball back on top it will still roll down to the bottom of the hill because that is where it is most stable.Why is shape important? This structure specifies the function of the protein. For example, a protein that breaks down glucose so the cell can use the energy stored in the sugar will have a shape that recognizes the glucose and binds to it (like a lock and key) and chemically reactive amino acids that will react with the glucose and break it down to release the energy.What do proteins do? Proteins are involved in almost all of the processes going on inside your body: they break down food to power your muscles, send signals through your brain that control the body, and transport nutrients through your blood. Many proteins act as enzymes, meaning they catalyze (speed up) chemical reactions that wouldn't take place otherwise. But other proteins power muscle contractions, or act as chemical messages inside the body, or hundreds of other things. Here's a small sample of what proteins do:Amylase starts the process of breaking down starch from food into forms the body can use.Alcohol dehydrogenase transforms alcohol from beer/wine/liquor into a non-toxic form that the body uses for food.Hemoglobin carries oxygen in our blood.Fibrin forms a scab to protect cuts as they heal.Collagen gives structure and support to our skin, tendons, and even bones.Actin is one of the major proteins in our muscles.Growth hormone helps regulate the growth of children into adults.Potassium channels help send signals through the brain and other nerve cells.Insulin regulates the amount of sugar in the blood and is used to treat diabetes.Proteins are present in all living things, even plants, bacteria, and viruses. Some organisms have proteins that give them their special characteristics:Photosystem I is a collection of proteins in plants that captures sunlight for photosynthesis.Luciferase catalyzes the chemical reaction that makes fireflies glow.Hemagglutinin helps the influenza virus invade our cells.You can find more information on the rules of protein folding in our FAQ.Why is this game important?What big problems is this game tackling?Protein structure prediction: As described above, knowing the structure of a protein is key to understanding how it works and to targeting it with drugs. A small protein can consist of 100 amino acids, while some human proteins can be huge (1000 amino acids). The number of different ways even a small protein can fold is astronomical because there are so many degrees of freedom. Figuring out which of the many, many possible structures is the best one is regarded as one of the hardest problems in biology today and current methods take a lot of money and time, even for computers. Foldit attempts to predict the structure of a protein by taking advantage of humans' puzzle-solving intuitions and having people play competitively to fold the best proteins.Protein design: Since proteins are part of so many diseases, they can also be part of the cure. Players can design brand new proteins that could help prevent or treat important diseases.Folder Madde's top scoring solution to the Mason pfizer monkey virus (+) Enlarge This ImageHow does my game playing contribute to curing diseases?With all the things proteins do to keep our bodies functioning and healthy, they can be involved in disease in many different ways. The more we know about how certain proteins fold, the better new proteins we can design to combat the disease-related proteins and cure the diseases. Below, we list three diseases that represent different ways that proteins can be involved in disease.HIV / AIDS: The HIV virus is made up largely of proteins, and once inside a cell it creates other proteins to help itself reproduce. HIV-1 protease and reverse transcriptase are two proteins made by the HIV virus that help it infect the body and replicate itself. HIV-1 protease cuts the "polyprotein" made by the replicating virus into the functional pieces it needs. Reverse transcriptase converts HIV's genes from RNA into a form its host understands, DNA. Both proteins are critical for the virus to replicate inside the body, and both are targeted by anti-HIV drugs. This is an example of a disease producing proteins that do not occur naturally in the body to help it attack our cells.Cancer: Cancer is very different from HIV in that it's usually our own proteins to blame, instead of proteins from an outside invader. Cancer arises from the uncontrolled growth of cells in some part of our bodies, such as the lung, breast, or skin. Ordinarily, there are systems of proteins that limit cell growth, but they may be damaged by things like UV rays from the sun or chemicals from cigarette smoke. But other proteins, like p53 tumor suppressor, normally recognize the damage and stop the cell from becoming cancerous -- unless they too are damaged. In fact, damage to the gene for p53 occurs in about half of human cancers (together with damage to various other genes).Alzheimer's: In some ways, Alzheimer's is the disease most directly caused by proteins. A protein called amyloid-beta precursor protein is a normal part of healthy, functioning nerve cells in the brain. But to do its job, it gets cut into two pieces, leaving behind a little scrap from the middle -- amyloid-beta peptide. Many copies of this peptide (short protein segment) can come together to form clumps of protein in the brain. Although many things about Alzheimer's are still not understood, it is thought that these clumps of protein are a major part of the disease.This is an example of a puzzle that a human can see the obvious answer to - fix the sheet that is sticking out! (+) Enlarge This ImageWhat other good stuff am I contributing to by playing?Proteins are found in all living things, including plants. Certain types of plants are grown and converted to biofuel, but the conversion process is not as fast and efficient as it could be. A critical step in turning plants into fuel is breaking down the plant material, which is currently done by microbial enzymes (proteins) called "cellulases". Perhaps we can find new proteins to do it better.Can humans really help computers fold proteins?We’re collecting data to find out if humans' pattern-recognition and puzzle-solving abilities make them more efficient than existing computer programs at pattern-folding tasks. If this turns out to be true, we can then teach human strategies to computers and fold proteins faster than ever!You can find more information about the goals of the project in our FAQ.Foldit Scientific PublicationsPredicting protein structures with a multiplayer online game. Seth Cooper, FirasKhatib, AdrienTreuille, Janos Barbero, Jeehyung Lee, Michael Beenen, Andrew Leaver-Fay, David Baker, ZoranPopović and Foldit players. In Nature 466, 756-760 (2010).The challenge of designing scientific discovery games. Seth Cooper, AdrienTreuille, Janos Barbero, Andrew Leaver-Fay, Kathleen Tuite, FirasKhatib, Alex Cho Snyder, Michael Beenen, David Salesin, David Baker, ZoranPopović and Foldit players. In Foundations of Digital Games, 2010.Analysis of social gameplay macros in the Foldit cookbook. Seth Cooper, FirasKhatib, IlyaMakedon, Hao Lu, Janos Barbero, David Baker, James Fogarty, ZoranPopović and Foldit Players. In Foundations of Digital Games, 2011.Crystal structure of a monomeric retroviral protease solved by protein folding game players. FirasKhatib, Frank DiMaio, Foldit Contenders Group, Foldit Void Crushers Group, Seth Cooper, MaciejKazmierczyk, MiroslawGilski, SzymonKrzywda, Helena Zábranská, Iva Pichová, James Thompson, ZoranPopović, MariuszJaskolski and David Baker. In Nature Structural and Molecular Biology 18, 1175–1177 (2011).High-resolution structure of a retroviral protease folded as a monomer. MiroslawGilski, MaciejKazmierczyk, SzymonKrzywda, Helena Zábranská, Seth Cooper, ZoranPopović, FirasKhatib, Frank DiMaio, James Thompson, David Baker, Iva Pichová and MariuszJaskolskia. In ActaCrystallographica D67, 907-914 (2011).Algorithm discovery by protein folding game players. FirasKhatib, Seth Cooper, Michael D. Tyka, KefanXu, IlyaMakedon, ZoranPopović, David Baker, and Foldit Players. In Proceedings of the National Academy of Sciences (2011).Increased Diels-Alderase activity through backbone remodeling guided by Foldit players. Christopher B Eiben, Justin B Siegel, Jacob B Bale, Seth Cooper, FirasKhatib, Betty W Shen, Foldit Players, Barry L Stoddard, ZoranPopović and David Baker. In Nature Biotechnology (2012).