The Rise of Citizen Science in Health and Biomedical Research.

Citizen science models of public participation in scientific research represent a growing area of opportunity for health and biomedical research, as well as new impetus for more collaborative forms of engagement in large-scale research. However, this also surfaces a variety of ethical issues that both fall outside of and build upon the standard human subjects concerns in bioethics. This article provides background on citizen science, examples of current projects in the field, and discussion of established and emerging ethical issues for citizen science in health and biomedical research.

A Science Products Inventory for Citizen-Science Planning and Evaluation.

Citizen science involves a range of practices involving public participation in scientific knowledge production, but outcomes evaluation is complicated by the diversity of the goals and forms of citizen science. Publications and citations are not adequate metrics to describe citizen-science productivity. We address this gap by contributing a science products inventory (SPI) tool, iteratively developed through an expert panel and case studies, intended to support general-purpose planning and evaluation of citizen-science projects with respect to science productivity. The SPI includes a collection of items for tracking the production of science outputs and data practices, which are described and illustrated with examples. Several opportunities for further development of the initial inventory are highlighted, as well as potential for using the inventory as a tool to guide project management, funding, and research on citizen science.

A Science Products Inventory for Citizen-Science Planning and Evaluation.

Citizen science involves a range of practices involving public participation in scientific knowledge production, but outcomes evaluation is complicated by the diversity of the goals and forms of citizen science. Publications and citations are not adequate metrics to describe citizen-science productivity. We address this gap by contributing a science products inventory (SPI) tool, iteratively developed through an expert panel and case studies, intended to support general-purpose planning and evaluation of citizen-science projects with respect to science productivity. The SPI includes a collection of items for tracking the production of science outputs and data practices, which are described and illustrated with examples. Several opportunities for further development of the initial inventory are highlighted, as well as potential for using the inventory as a tool to guide project management, funding, and research on citizen science.

Exposing the Science in Citizen Science: Fitness to Purpose and Intentional Design.

Citizen science is a growing phenomenon. With millions of people involved and billions of in-kind dollars contributed annually, this broad extent, fine grain approach to data collection should be garnering enthusiastic support in the mainstream science and higher education communities. However, many academic researchers demonstrate distinct biases against the use of citizen science as a source of rigorous information. To engage the public in scientific research, and the research community in the practice of citizen science, a mutual understanding is needed of accepted quality standards in science, and the corresponding specifics of project design and implementation when working with a broad public base. We define a science-based typology focused on the degree to which projects deliver the type(s) and quality of data/work needed to produce valid scientific outcomes directly useful in science and natural resource management. Where project intent includes direct contribution to science and the public is actively involved either virtually or hands-on, we examine the measures of quality assurance (methods to increase data quality during the design and implementation phases of a project) and quality control (post hoc methods to increase the quality of scientific outcomes). We suggest that high quality science can be produced with massive, largely one-off, participation if data collection is simple and quality control includes algorithm voting, statistical pruning, and/or computational modeling. Small to mid-scale projects engaging participants in repeated, often complex, sampling can advance quality through expert-led training and well-designed materials, and through independent verification. Both approaches-simplification at scale and complexity with care-generate more robust science outcomes.

Can Observation Skills of Citizen Scientists Be Estimated Using Species Accumulation Curves?

Volunteers are increasingly being recruited into citizen science projects to collect observations for scientific studies. An additional goal of these projects is to engage and educate these volunteers. Thus, there are few barriers to participation resulting in volunteer observers with varying ability to complete the project's tasks. To improve the quality of a citizen science project's outcomes it would be useful to account for inter-observer variation, and to assess the rarely tested presumption that participating in a citizen science projects results in volunteers becoming better observers. Here we present a method for indexing observer variability based on the data routinely submitted by observers participating in the citizen science project eBird, a broad-scale monitoring project in which observers collect and submit lists of the bird species observed while birding. Our method for indexing observer variability uses species accumulation curves, lines that describe how the total number of species reported increase with increasing time spent in collecting observations. We find that differences in species accumulation curves among observers equates to higher rates of species accumulation, particularly for harder-to-identify species, and reveals increased species accumulation rates with continued participation. We suggest that these properties of our analysis provide a measure of observer skill, and that the potential to derive post-hoc data-derived measurements of participant ability should be more widely explored by analysts of data from citizen science projects. We see the potential for inferential results from analyses of citizen science data to be improved by accounting for observer skill.