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Citizen science projects have the potential to advance science by increasing the volume and variety of data, as well as innovation. Yet this potential has not been fully realized, in part because citizen science data are typically not widely shared and reused. To address this and related challenges, we built CitSci.org (see www.citsci.org), a customizable platform that allows users to collect and generate diverse datasets. We hope that CitSci.org will ultimately increase discoverability and confidence in citizen science observations, encouraging scientists to use such data in their own scientific research.
This article was published in the following journal.
Name: PLoS biology
Biodiversity is being lost at an unprecedented rate, and monitoring is crucial for understanding the causal drivers and assessing solutions. Most biodiversity monitoring data are collected by voluntee...
Citizen science is a process by which volunteer members of the public, who commonly lack advanced training in science, engage in scientific activities (e.g., data collection) that might otherwise be b...
The "noisy labeler problem" in crowdsourced data has attracted great attention in recent years, with important ramifications in citizen science, where non-experts must produce high-quality data. Parti...
Coral reefs are threatened by numerous global and local stressors. In the face of predicted large-scale coral degradation over the coming decades, the importance of long-term monitoring of stress-indu...
Despite the fact that citizen engagement in research is widely practised and regarded as one of the keys to maximizing the impact of research and innovation, empirical evidence on the value, potential...
The purpose of this study is to advance upper limb RMTR for patients recovering from stroke by empowering them through active science participation. By varying the tasks' features and affo...
While low-income midlife and older adults are disproportionately affected by chronic diseases that can be alleviated by regular physical activity, few physical activity programs have been ...
The need for leading people, managing work, and governing organizations never changed over the civilization paths of society. However, people in every pole of the globe observe: over-led a...
In recent years, Mahidol Oxford Tropical Medicine Research Unit (MORU) has coordinated some of the largest international studies involving many sites in low-income and hard-to-reach settin...
This pilot study will assess feasibility and to obtain initial estimates of efficacy of Sleep Activity and Task Effectiveness (SAFTE) model, which can accurately estimate the impact of sch...
Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.
The science and art of collecting, summarizing, and analyzing data that are subject to random variation. The term is also applied to the data themselves and to the summarization of the data.
Works consisting of an announcement or statement of recent or current events of new data and matters of interest in the field of medicine or science. In some publications, such as "Nature" or "Science," the news reports are substantively written and herald medical and scientific data of vital or controversial importance.
Functions constructed from a statistical model and a set of observed data which give the probability of that data for various values of the unknown model parameters. Those parameter values that maximize the probability are the maximum likelihood estimates of the parameters.
A framework for development and promotion of common data formats and exchange protocols linked in a way that can be read directly by computers. Semantic Web is a platform for sharing and reusing data across application, enterprise, and community boundaries, by linking concepts rather than just documents.