Citizen Science involves public participation in scientific research, where volunteers collaborate with scientists to collect and analyze data. Methods include community monitoring and wildlife observation, often facilitated by online platforms. It benefits from expanded data collection and engages the public in science. Challenges include data quality and project coordination. Examples include eBird and Foldit.
Citizen science, also known as community science or public participation in scientific research (PPSR), is a research methodology that involves the active participation of non-professional scientists or volunteers in scientific activities. These activities can range from data collection and analysis to problem-solving and collaboration with professional scientists. The primary goal of citizen science is to harness the collective knowledge, skills, and enthusiasm of a diverse group of individuals to advance scientific understanding and address real-world challenges.
Citizen science projects span a wide range of scientific disciplines, including astronomy, ecology, environmental science, biology, chemistry, social sciences, and more. They often leverage technology and online platforms to facilitate data collection, collaboration, and communication among participants.
Key Principles of Citizen Science
To better understand the principles that underpin citizen science, consider the following key ideas:
Inclusivity: Citizen science is open to people of all backgrounds, ages, and levels of expertise. It encourages inclusivity and diversity, fostering a sense of belonging and ownership among participants.
Collaboration: Citizen science projects typically involve collaboration between volunteers and professional scientists. This collaboration is marked by a spirit of cooperation, mutual respect, and shared goals.
Public Engagement: Citizen science goes beyond data collection; it actively engages the public in scientific processes. Participants are not passive observers but active contributors to scientific research.
Data Quality: Maintaining data quality is a top priority in citizen science. Protocols and tools are designed to ensure that the data collected by volunteers meet scientific standards and can be used for meaningful research.
Open Access: Many citizen science projects promote open access to data, findings, and tools. This transparency fosters trust and allows the broader scientific community and the public to benefit from the results.
History and Evolution of Citizen Science
The roots of citizen science can be traced back to early scientific endeavors when amateur naturalists and enthusiasts made significant contributions to the field of natural history. Pioneers like Charles Darwin and John James Audubon relied on the observations and collections of citizen scientists to advance their research.
In the 20th century, formalized citizen science initiatives began to emerge, often in the context of birdwatching clubs and environmental conservation efforts. These initiatives paved the way for the broader democratization of science.
The digital age has played a pivotal role in the evolution of citizen science. The internet and mobile technology have made it easier for volunteers to participate in projects, share data, and collaborate with researchers on a global scale. Online platforms and mobile apps have transformed citizen science from a localized practice into a worldwide movement.
Key Characteristics of Citizen Science
Citizen science projects exhibit several key characteristics that distinguish them from traditional scientific research:
Volunteer Participation: Citizen science relies on the voluntary efforts of individuals who may or may not have formal scientific training. This inclusivity allows a diverse range of people to contribute.
Collective Data Collection: Projects often involve large numbers of participants collecting data simultaneously, which can lead to the gathering of vast datasets in a relatively short time.
Community Building: Citizen science fosters a sense of community among participants, who share a common interest in scientific inquiry and discovery.
Scientific Impact: Many citizen science projects have produced valuable scientific insights and contributed to peer-reviewed research. Volunteers are acknowledged as co-authors or contributors in scientific publications.
Educational Opportunities: Citizen science provides opportunities for informal science education and engagement. Participants can learn about scientific methods, data analysis, and the natural world while contributing to research.
Benefits of Citizen Science
Citizen science offers a multitude of benefits to individuals, communities, and the scientific community:
Scientific Discovery: Citizen science projects have led to important scientific discoveries and advancements across various fields, including astronomy, ecology, ornithology, and environmental science.
Public Engagement: It engages the public in scientific activities, promoting science literacy, and fostering a deeper appreciation for the scientific process.
Data Collection: Citizen science enables the collection of vast datasets that would be challenging for individual researchers or small teams to acquire.
Cost-Effective Research: By harnessing the power of volunteers, citizen science projects can conduct research cost-effectively, stretching research budgets further.
Conservation and Advocacy: Many citizen science projects focus on environmental conservation, providing critical data for decision-making and advocacy efforts.
Educational Opportunities: Citizen science serves as a valuable educational tool, offering hands-on learning experiences for participants of all ages.
Challenges in Citizen Science
While citizen science offers numerous advantages, it also faces certain challenges and considerations:
Data Quality Control: Ensuring the accuracy and reliability of data collected by volunteers can be challenging. Rigorous protocols and data validation processes are essential.
Project Sustainability: Maintaining the long-term sustainability of citizen science projects can be a logistical and financial challenge, especially for grassroots initiatives.
Ethical Concerns: Ethical considerations, such as data privacy, informed consent, and equitable participation, must be addressed to protect the rights and interests of volunteers.
Scientific Validity: Ensuring that citizen science research meets scientific standards and can be incorporated into peer-reviewed literature is an ongoing concern.
Data Accessibility: Making data accessible to the public while protecting sensitive information can be a delicate balance.
Examples of Citizen Science Projects
Citizen science has made significant contributions to a wide range of scientific disciplines. Here are a few examples of impactful citizen science projects:
eBird: Managed by the Cornell Lab of Ornithology, eBird is a global database of bird observations contributed by birdwatchers and enthusiasts. It has revolutionized the field of ornithology and contributed to bird conservation efforts.
Foldit: Foldit is an online puzzle video game that challenges players to solve complex protein-folding problems. Players’ solutions contribute to scientific research in biochemistry and drug design.
Zooniverse: Zooniverse is a platform that hosts a variety of citizen science projects, from classifying galaxies and transcribing historical documents to identifying wildlife in camera trap photos.
The Great Backyard Bird Count: An annual event that encourages people worldwide to count birds in their local areas and report their observations online. This project provides valuable data for studying bird populations.
NASA’s Planet Hunters: This project invites volunteers to search for exoplanets in data from the Kepler Space Telescope. Citizen scientists have discovered numerous potential exoplanets.
iNaturalist: iNaturalist is a platform for recording and sharing observations of biodiversity. It has helped scientists track the distribution of species and detect ecological changes.
Conclusion
Citizen science is a transformative and inclusive approach to scientific research that empowers individuals and communities to actively participate in the scientific process. It has the potential to advance our understanding of the natural world, address pressing environmental challenges, and promote science literacy. As citizen science continues to evolve and expand its reach, it exemplifies the collaborative and democratizing spirit of scientific inquiry, where everyone has the opportunity to contribute to our collective knowledge and make a meaningful impact on the world of science.
Case Studies
Project BudBurst: Participants observe and record the timing of leafing, flowering, and fruiting of plants, helping scientists track the impact of climate change on plant phenology.
The Globe at Night: Volunteers measure light pollution in their areas by identifying and counting visible stars in the night sky, aiding in the preservation of dark skies.
SETI@home: Users contribute their computer’s processing power to analyze radio signals from space in the search for extraterrestrial intelligence.
iNaturalist: A platform where users share observations of plants and animals, contributing to biodiversity research and species identification.
Coral Watch: Divers and snorkelers record coral bleaching observations and upload data, assisting in coral reef conservation efforts.
Old Weather: Participants transcribe historical ship logs to gather climate data and improve our understanding of past weather patterns.
EteRNA: Gamers design RNA molecules in an online puzzle game, contributing to RNA structure research.
Bat Detective: Users analyze bat calls recorded from around the world, helping researchers study bat populations and behavior.
Stall Catchers: Participants play an online game to analyze blood flow videos to accelerate Alzheimer’s disease research.
Habitat Network: Individuals map their yards and gardens to create a database of wildlife-friendly habitats, promoting urban biodiversity.
FrogWatch USA: Volunteers monitor and report frog and toad calls, contributing to amphibian conservation and research.
CrowdWater: Citizen scientists measure water levels in rivers and streams using smartphones, providing valuable hydrological data.
CitiSci.org: A platform connecting volunteers with a wide range of citizen science projects, making it easy to find opportunities to get involved.
Key Highlights
Public Participation: Citizen science involves the active engagement of individuals from diverse backgrounds, including non-scientists, in scientific research and data collection.
Scientific Collaboration: Collaboration between citizen volunteers and professional scientists fosters knowledge exchange, enhancing research outcomes.
Diverse Research Areas: Citizen science spans multiple fields, from environmental monitoring and biodiversity studies to astronomy, healthcare, and more.
Technological Tools: Online platforms and mobile apps make it easier for volunteers to participate remotely and contribute data.
Expanded Data Collection: The involvement of a large number of participants significantly increases the volume of data available for research.
Public Engagement: Citizen science promotes scientific literacy, encourages curiosity, and creates a sense of ownership in research projects.
Cost-Efficiency: Leveraging the efforts of citizen volunteers can reduce the cost of data collection and analysis, making large-scale projects feasible.
Challenges: Ensuring data quality, project coordination, and addressing ethical considerations are challenges that need to be managed in citizen science initiatives.
Real-World Impact: Citizen science has made significant contributions to fields such as environmental conservation, healthcare research, and space exploration.
Community Building: Participation in citizen science often leads to the formation of communities of enthusiasts with shared interests and goals.
Accessible Science: Citizen science makes science accessible to a broader audience, breaking down barriers between researchers and the public.
Environmental Stewardship: Projects like habitat monitoring and wildlife observation empower individuals to take an active role in environmental stewardship.
Scientific Discovery: Citizen science has led to discoveries and insights that may not have been possible through traditional research methods alone.
Convergent thinking occurs when the solution to a problem can be found by applying established rules and logical reasoning. Whereas divergent thinking is an unstructured problem-solving method where participants are encouraged to develop many innovative ideas or solutions to a given problem. Where convergent thinking might work for larger, mature organizations where divergent thinking is more suited for startups and innovative companies.
The concept of cognitive biases was introduced and popularized by the work of Amos Tversky and Daniel Kahneman in 1972. Biases are seen as systematic errors and flaws that make humans deviate from the standards of rationality, thus making us inept at making good decisions under uncertainty.
Second-order thinking is a means of assessing the implications of our decisions by considering future consequences. Second-order thinking is a mental model that considers all future possibilities. It encourages individuals to think outside of the box so that they can prepare for every and eventuality. It also discourages the tendency for individuals to default to the most obvious choice.
Lateral thinking is a business strategy that involves approaching a problem from a different direction. The strategy attempts to remove traditionally formulaic and routine approaches to problem-solving by advocating creative thinking, therefore finding unconventional ways to solve a known problem. This sort of non-linear approach to problem-solving, can at times, create a big impact.
Bounded rationality is a concept attributed to Herbert Simon, an economist and political scientist interested in decision-making and how we make decisions in the real world. In fact, he believed that rather than optimizing (which was the mainstream view in the past decades) humans follow what he called satisficing.
The Dunning-Kruger effect describes a cognitive bias where people with low ability in a task overestimate their ability to perform that task well. Consumers or businesses that do not possess the requisite knowledge make bad decisions. What’s more, knowledge gaps prevent the person or business from seeing their mistakes.
Occam’s Razor states that one should not increase (beyond reason) the number of entities required to explain anything. All things being equal, the simplest solution is often the best one. The principle is attributed to 14th-century English theologian William of Ockham.
The Lindy Effect is a theory about the ageing of non-perishable things, like technology or ideas. Popularized by author Nicholas Nassim Taleb, the Lindy Effect states that non-perishable things like technology age – linearly – in reverse. Therefore, the older an idea or a technology, the same will be its life expectancy.
Antifragility was first coined as a term by author, and options trader Nassim Nicholas Taleb. Antifragility is a characteristic of systems that thrive as a result of stressors, volatility, and randomness. Therefore, Antifragile is the opposite of fragile. Where a fragile thing breaks up to volatility; a robust thing resists volatility. An antifragile thing gets stronger from volatility (provided the level of stressors and randomness doesn’t pass a certain threshold).
Systems thinking is a holistic means of investigating the factors and interactions that could contribute to a potential outcome. It is about thinking non-linearly, and understanding the second-order consequences of actions and input into the system.
Vertical thinking, on the other hand, is a problem-solving approach that favors a selective, analytical, structured, and sequential mindset. The focus of vertical thinking is to arrive at a reasoned, defined solution.
Maslow’s Hammer, otherwise known as the law of the instrument or the Einstellung effect, is a cognitive bias causing an over-reliance on a familiar tool. This can be expressed as the tendency to overuse a known tool (perhaps a hammer) to solve issues that might require a different tool. This problem is persistent in the business world where perhaps known tools or frameworks might be used in the wrong context (like business plans used as planning tools instead of only investors’ pitches).
The Peter Principle was first described by Canadian sociologist Lawrence J. Peter in his 1969 book The Peter Principle. The Peter Principle states that people are continually promoted within an organization until they reach their level of incompetence.
The straw man fallacy describes an argument that misrepresents an opponent’s stance to make rebuttal more convenient. The straw man fallacy is a type of informal logical fallacy, defined as a flaw in the structure of an argument that renders it invalid.
The Streisand Effect is a paradoxical phenomenon where the act of suppressing information to reduce visibility causes it to become more visible. In 2003, Streisand attempted to suppress aerial photographs of her Californian home by suing photographer Kenneth Adelman for an invasion of privacy. Adelman, who Streisand assumed was paparazzi, was instead taking photographs to document and study coastal erosion. In her quest for more privacy, Streisand’s efforts had the opposite effect.
As highlighted by German psychologist Gerd Gigerenzer in the paper “Heuristic Decision Making,” the term heuristic is of Greek origin, meaning “serving to find out or discover.” More precisely, a heuristic is a fast and accurate way to make decisions in the real world, which is driven by uncertainty.
The recognition heuristic is a psychological model of judgment and decision making. It is part of a suite of simple and economical heuristics proposed by psychologists Daniel Goldstein and Gerd Gigerenzer. The recognition heuristic argues that inferences are made about an object based on whether it is recognized or not.
The representativeness heuristic was first described by psychologists Daniel Kahneman and Amos Tversky. The representativeness heuristic judges the probability of an event according to the degree to which that event resembles a broader class. When queried, most will choose the first option because the description of John matches the stereotype we may hold for an archaeologist.
The take-the-best heuristic is a decision-making shortcut that helps an individual choose between several alternatives. The take-the-best (TTB) heuristic decides between two or more alternatives based on a single good attribute, otherwise known as a cue. In the process, less desirable attributes are ignored.
The bundling bias is a cognitive bias in e-commerce where a consumer tends not to use all of the products bought as a group, or bundle. Bundling occurs when individual products or services are sold together as a bundle. Common examples are tickets and experiences. The bundling bias dictates that consumers are less likely to use each item in the bundle. This means that the value of the bundle and indeed the value of each item in the bundle is decreased.
The Barnum Effect is a cognitive bias where individuals believe that generic information – which applies to most people – is specifically tailored for themselves.
First-principles thinking – sometimes called reasoning from first principles – is used to reverse-engineer complex problems and encourage creativity. It involves breaking down problems into basic elements and reassembling them from the ground up. Elon Musk is among the strongest proponents of this way of thinking.
The ladder of inference is a conscious or subconscious thinking process where an individual moves from a fact to a decision or action. The ladder of inference was created by academic Chris Argyris to illustrate how people form and then use mental models to make decisions.
Goodhart’s Law is named after British monetary policy theorist and economist Charles Goodhart. Speaking at a conference in Sydney in 1975, Goodhart said that “any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.” Goodhart’s Law states that when a measure becomes a target, it ceases to be a good measure.
The Six Thinking Hats model was created by psychologist Edward de Bono in 1986, who noted that personality type was a key driver of how people approached problem-solving. For example, optimists view situations differently from pessimists. Analytical individuals may generate ideas that a more emotional person would not, and vice versa.
The Mandela effect is a phenomenon where a large group of people remembers an event differently from how it occurred. The Mandela effect was first described in relation to Fiona Broome, who believed that former South African President Nelson Mandela died in prison during the 1980s. While Mandela was released from prison in 1990 and died 23 years later, Broome remembered news coverage of his death in prison and even a speech from his widow. Of course, neither event occurred in reality. But Broome was later to discover that she was not the only one with the same recollection of events.
The bandwagon effect tells us that the more a belief or idea has been adopted by more people within a group, the more the individual adoption of that idea might increase within the same group. This is the psychological effect that leads to herd mentality. What in marketing can be associated with social proof.
Moore’s law states that the number of transistors on a microchip doubles approximately every two years. This observation was made by Intel co-founder Gordon Moore in 1965 and it become a guiding principle for the semiconductor industry and has had far-reaching implications for technology as a whole.
Disruptive innovation as a term was first described by Clayton M. Christensen, an American academic and business consultant whom The Economist called “the most influential management thinker of his time.” Disruptive innovation describes the process by which a product or service takes hold at the bottom of a market and eventually displaces established competitors, products, firms, or alliances.
Value migration was first described by author Adrian Slywotzky in his 1996 book Value Migration – How to Think Several Moves Ahead of the Competition. Value migration is the transferal of value-creating forces from outdated business models to something better able to satisfy consumer demands.
The bye-now effect describes the tendency for consumers to think of the word “buy” when they read the word “bye”. In a study that tracked diners at a name-your-own-price restaurant, each diner was asked to read one of two phrases before ordering their meal. The first phrase, “so long”, resulted in diners paying an average of $32 per meal. But when diners recited the phrase “bye bye” before ordering, the average price per meal rose to $45.
Groupthink occurs when well-intentioned individuals make non-optimal or irrational decisions based on a belief that dissent is impossible or on a motivation to conform. Groupthink occurs when members of a group reach a consensus without critical reasoning or evaluation of the alternatives and their consequences.
A stereotype is a fixed and over-generalized belief about a particular group or class of people. These beliefs are based on the false assumption that certain characteristics are common to every individual residing in that group. Many stereotypes have a long and sometimes controversial history and are a direct consequence of various political, social, or economic events. Stereotyping is the process of making assumptions about a person or group of people based on various attributes, including gender, race, religion, or physical traits.
Murphy’s Law states that if anything can go wrong, it will go wrong. Murphy’s Law was named after aerospace engineer Edward A. Murphy. During his time working at Edwards Air Force Base in 1949, Murphy cursed a technician who had improperly wired an electrical component and said, “If there is any way to do it wrong, he’ll find it.”
The law of unintended consequences was first mentioned by British philosopher John Locke when writing to parliament about the unintended effects of interest rate rises. However, it was popularized in 1936 by American sociologist Robert K. Merton who looked at unexpected, unanticipated, and unintended consequences and their impact on society.
Fundamental attribution error is a bias people display when judging the behavior of others. The tendency is to over-emphasize personal characteristics and under-emphasize environmental and situational factors.
Outcome bias describes a tendency to evaluate a decision based on its outcome and not on the process by which the decision was reached. In other words, the quality of a decision is only determined once the outcome is known. Outcome bias occurs when a decision is based on the outcome of previous events without regard for how those events developed.
Hindsight bias is the tendency for people to perceive past events as more predictable than they actually were. The result of a presidential election, for example, seems more obvious when the winner is announced. The same can also be said for the avid sports fan who predicted the correct outcome of a match regardless of whether their team won or lost. Hindsight bias, therefore, is the tendency for an individual to convince themselves that they accurately predicted an event before it happened.
Gennaro is the creator of FourWeekMBA, which reached about four million business people, comprising C-level executives, investors, analysts, product managers, and aspiring digital entrepreneurs in 2022 alone | He is also Director of Sales for a high-tech scaleup in the AI Industry | In 2012, Gennaro earned an International MBA with emphasis on Corporate Finance and Business Strategy.
