/pdf/citizen-science-a-study-of-people-expertise-and-sustainable-3po1jwi9qc.pdf

Citizen Science: A Study of People, Expertise and Sustainable Development

Open Science is an umbrella term encompassing a multitude of assumptions about the future of knowledge creation and dissemination. Based on a literature review, this chapter aims at structuring the overall discourse by proposing five Open Science schools of thought: The infrastructure school (which is concerned with the technological architecture), the public school (which is concerned with the accessibility of knowledge creation), the measurement school (which is concerned with alternative impact measurement), the democratic school (which is concerned with access to knowledge) and the pragmatic school (which is concerned with collaborative research).

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Open Science: One Term, Five Schools of Thought

Citizen science provides researchers means to gather or analyse large datasets. At the same time, citizen science projects offer an opportunity for non-scientists to be part of and learn from the s...

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Citizen science on a smartphone: Participants' motivations and learning.

Citizen science has proliferated in the last decade, becoming a critical form of public engagement in science and an increasingly important research tool for the study of large-scale patterns in nature. Although citizen science is already interdisciplinary, it has untapped potential to build capacity for transformative research on coupled human and natural systems. New tools have begun to collect paired ecological and social data from the same individual; this allows for detailed examination of feedbacks at the level of individuals and potentially provides much-needed data for agent-based modeling. With the ongoing professionalization of citizen science, the field can benefit from integrating a coupled systems perspective, including a broadening of the social science perspectives considered. This can lead to new schema and platforms to increase support for large-scale research on coupled natural and human systems.

https://www.annualreviews.org/doi/pdf/10.1146/annurev-environ-030713-154609

Citizen Science: A Tool for Integrating Studies of Human and Natural Systems

Conservation prioritization at large scales is complex, combining biological, environmental, and social factors. While conservation scientists now more often aim to incorporate human-related factors, a critical yet unquantified challenge remains: to identify which areas people use for recreation outside urban centers. To address this gap in applied ecology and conservation, we developed a novel approach for quantifying human presence beyond populated areas by combining social media "big data" and remote sensing tools. We used data from the Flickr photo-sharing website as a surrogate for identifying spatial variation in visitation globally, and complemented this estimate with spatially explicit information on stable night lights between 2004 and 2012, used as a proxy for identifying urban and industrial centers. Natural and seminatural areas attracting visitors were defined as areas both highly photographed and non-lit. The number of Flickr photographers within protected areas was found to be a reliable surrogate for estimating visitor numbers as confirmed by local authority censuses (r = 0.8). Half of all visitors' photos taken in protected areas originated from under 1% of all protected areas on Earth (250 of -27 000). The most photographed protected areas globally included Yosemite and Yellowstone National Parks (USA), and the Lake and Peak Districts (UK). Factors explaining the spatial variation in protected areas Flickr photo coverage included their type (e.g., UNESCO World Heritage sites have higher visitation) and accessibility to roads and trails. Using this approach, we identified photography hotspots, which draw many visitors and are also unlit (i.e., are located outside urban centers), but currently remain largely unprotected, such as Brazil's Pantanal and Bolivia's Salar de Uyuni. The integrated big data approach developed here demonstrates the benefits of combining remote sensing sources and novel geo-tagged and crowd-sourced information from social media in future efforts to identify spatial conservation gaps and pressures in real time, and their spatial and temporal variation globally.

/pdf/where-have-all-the-people-gone-enhancing-global-conservation-2ppm90agnv.pdf

Where have all the people gone? Enhancing global conservation using night lights and social media

Within conservation and ecology, volunteer participation has always been an important component of research. Within the past two decades, this use of volunteers in research has proliferated and evolved into “citizen science.” Technologies are evolving rapidly. Mobile phone technologies and the emergence and uptake of high-speed Web-capable smart phones with GPS and data upload capabilities can allow instant collection and transmission of data. This is frequently used within everyday life particularly on social networking sites. Embedded sensors allow researchers to validate GPS and image data and are now affordable and regularly used by citizens. With the “perfect storm” of technology, data upload, and social networks, citizen science represents a powerful tool. This paper establishes the current state of citizen science within scientific literature, examines underlying themes, explores further possibilities for utilising citizen science within ecology, biodiversity, and biology, and identifies possible directions for further research. The paper highlights (1) lack of trust in the scientific community about the reliability of citizen science data, (2) the move from standardised data collection methods to data mining available datasets, and (3) the blurring of the line between citizen science and citizen sensors and the need to further explore online social networks for data collection.

/pdf/the-citizen-science-landscape-from-volunteers-to-citizen-1ilw8l53yz.pdf

Christina L. Catlin-Groves

Papers

The Citizen Science Landscape: From Volunteers to Citizen Sensors and Beyond