The Clumpy experiment sounds like a funny project to participate in, and you might even expect something inherently unscientific, like identifying mascara clumps. However, it is a legitimate project created by scientists including Hugo Hutt in the Bioscience and Computer Science Department at the University of Exeter. By identifying the “clumpiness”, of an image generated; citizens are able to contribute data to an experiment that observes bacterial infection of a plant.
The organizers of the experiment are scientists at the University of Exeter in the United Kingdom; a legitimate and renowned place of education. The researchers are specifically in the fields of bioscience and computer science, and have expertise in analyzing data from random strangers online. They even published a paper on evaluating crowdsourced data, explaining how they weed out spammers and the such. (link) The website is very user friendly, and cost-free to participate in, as they want a large amount of data to help them with their research. When you complete sections of tasks on their website, there is a quick survey given that asks for your gender, age, education, and basic information. However, it is optional, and for that reason, I did not complete it.
The training was helpful in the sense that it prepared you for the upcoming tasks; however, there were no answers to check if I was right or not and that caused some frustration for me. Their tutorial was a link at the top bar, so participants could always click back if they felt unsure. I personally had to complete the tutorial several times to get a grasp of the sorting. Throughout the sorting and identifying, there were sample photos at the bottom to reference, but it was still difficult because no raw data is being shown.
I found the identifying challenging at first, because it was fresh information, and my brain could not yet immediately separate the pictures into different categories. However, after awhile, it became easier to immediate identify and sort the clumps. Other than classifying (identifying if it is clumpy or not), there were also tasks such as scoring the picture’s clumpiness from 1-7, and also ordering it from least clumpy to most (as shown below).
The participation level is completely up to you, but after you finish a round of being a scorer/orderer/classifier, it rotates and you see how many you have done for each. You can contribute from 20 to 200.
As classifying was the easiest and funnest task for me, I focused on that section and annotated around 200 pictures. You are not personally acknowledged but it is nice to see how many you have completed and to think that you’ve helped an important experiment. This citizen science project is done completely online and does not require anything else than an internet browser. There are also no age restrictions, so anyone who feels comfortable identifying pictures can take a swing at it.
The citizen science project was definitely fun and eye-opening to see how ordinary people can contribute to the science community through their laptops at home. Through participating in this experiment, I have learned the behaviour of plants when infected with bacteria, such as the tendency for the chloroplasts to clump together. I have also gained skills of identifying and scoring the clumpiness of chloroplasts. Seeing the pictures of cells on a microscopic level was intriguing and left me with a lot of thoughts and interest about microbiology. Yet, I wish there was a more conclusive tutorial as I had to research some information on my own. I hope that they publish a paper in the future with the specifics of the information, and how our data contributed.