scholarly journals A Conceptual Probabilistic Framework for Annotation Aggregation of Citizen Science Data

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 875
Author(s):  
Jesus Cerquides ◽  
Mehmet Oğuz Mülâyim ◽  
Jerónimo Hernández-González ◽  
Amudha Ravi Shankar ◽  
Jose Luis Fernandez-Marquez
Keyword(s):  
Data Quality ◽  
Citizen Science ◽  
Graphical Model ◽  
Real Life ◽  
Scientific Journals ◽  
Probabilistic Framework ◽  
Science Data ◽  
Label Aggregation ◽  
Evaluation Of Data ◽  
Model Formalism

Over the last decade, hundreds of thousands of volunteers have contributed to science by collecting or analyzing data. This public participation in science, also known as citizen science, has contributed to significant discoveries and led to publications in major scientific journals. However, little attention has been paid to data quality issues. In this work we argue that being able to determine the accuracy of data obtained by crowdsourcing is a fundamental question and we point out that, for many real-life scenarios, mathematical tools and processes for the evaluation of data quality are missing. We propose a probabilistic methodology for the evaluation of the accuracy of labeling data obtained by crowdsourcing in citizen science. The methodology builds on an abstract probabilistic graphical model formalism, which is shown to generalize some already existing label aggregation models. We show how to make practical use of the methodology through a comparison of data obtained from different citizen science communities analyzing the earthquake that took place in Albania in 2019.

scholarly journals The impact of data quality filtering of opportunistic citizen science data on species distribution model performance

2021 ◽  
Vol 444 ◽  
pp. 109453
Author(s):  
Camille Van Eupen ◽  
Dirk Maes ◽  
Marc Herremans ◽  
Kristijn R.R. Swinnen ◽  
Ben Somers ◽  
...  
Keyword(s):  
Data Quality ◽  
Citizen Science ◽  
Species Distribution ◽  
Species Distribution Model ◽  
Model Performance ◽  
Distribution Model ◽  
Science Data ◽  
Quality Filtering ◽  
The Impact

scholarly journals The Verification of Ecological Citizen Science Data: Current approaches and future possibilities

2021 ◽  
Vol 5 ◽  
Author(s):  
Emily Baker ◽  
Jonathan Drury ◽  
Johanna Judge ◽  
David Roy ◽  
Graham Smith ◽  
...  
Keyword(s):  
Data Quality ◽  
Citizen Science ◽  
Applied Research ◽  
Automated Verification ◽  
Ecological Data ◽  
Science Data ◽  
Spatial And Temporal Scales ◽  
The Past ◽  
Published Research ◽  
Critical Process

Citizen science schemes (projects) enable ecological data collection over very large spatial and temporal scales, producing datasets of high value for both pure and applied research. However, the accuracy of citizen science data is often questioned, owing to issues surrounding data quality and verification, the process by which records are checked after submission for correctness. Verification is a critical process for ensuring data quality and for increasing trust in such datasets, but verification approaches vary considerably among schemes. Here, we systematically review approaches to verification across ecological citizen science schemes, which feature in published research, aiming to identify the options available for verification, and to examine factors that influence the approaches used (Baker et al. 2021). We reviewed 259 schemes and were able to locate verification information for 142 of those. Expert verification was most widely used, especially among longer-running schemes. Community consensus was the second most common verification approach, used by schemes such as Snapshot Serengeti (Swanson et al. 2016) and MammalWeb (Hsing et al. 2018). It was more common among schemes with a larger number of participants and where photos or video had to be submitted with each record. Automated verification was not widely used among the schemes reviewed. Schemes that used automation, such as eBird (Kelling et al. 2011) and Project FeederWatch (Bonter and Cooper 2012) did so in conjunction with other methods such as expert verification. Expert verification has been the default approach for schemes in the past, but as the volume of data collected through citizen science schemes grows and the potential of automated approaches develops, many schemes might be able to implement approaches that verify data more efficiently. We present an idealised system for data verification, identifying schemes where this hierachical system could be applied and the requirements for implementation. We propose a hierarchical approach in which the bulk of records are verified by automation or community consensus, and any flagged records can then undergo additional levels of verification by experts.

scholarly journals Merging science education, citizen science and general population noise exposure data collection in the battle against noise pollution

2021 ◽  
Vol 263 (3) ◽  
pp. 2996-3007
Author(s):  
Luc Dekoninck ◽  
Wim Van Beggenhout ◽  
Mieke Sterken
Keyword(s):  
Quality Of Life ◽  
Citizen Science ◽  
Noise Exposure ◽  
Real Life ◽  
Noise Pollution ◽  
Population Based ◽  
Policy Support ◽  
Monitoring Data ◽  
Science Data

Science, Technology, Engineering, Mathematics in education is commonly referred to as STEM. The last decades illustrate that our society is transferring into an ever accelerating technological environment. In parallel, the general public became an important driving force in collecting citizen science data to trigger legislative pressure and impact on policy makers to accelerate the improvement of their quality of life. That practice is currently extending into the environmental impact of noise related quality of life. This publication suggests to merge those educational STEM goals, citizen science monitoring and the need for population based noise monitoring data for efficient policy support. The presented educational project can be regarded as a proof-of-concept and can be repeated in different schools and classes every year. This approach has the potential to acquire abundant noise monitoring data and provides an unbiased population sampling dataset by design. This population driven involvement allows to assess real-life and long-term noise policy impact and could become a fundamental pillar in achieving the overall societal goal of improving noise related environmental quality of life.

scholarly journals Perspectives on Citizen Science Data Quality

2021 ◽  
Vol 3 ◽  
Author(s):  
Robert R. Downs ◽  
Hampapuram K. Ramapriyan ◽  
Ge Peng ◽  
Yaxing Wei
Keyword(s):  
Quality Control ◽  
Data Quality ◽  
Quality Assessment ◽  
Citizen Science ◽  
Data Reuse ◽  
Quality Information ◽  
Science Data ◽  
Conducting Research

Information about data quality helps potential data users to determine whether and how data can be used and enables the analysis and interpretation of such data. Providing data quality information improves opportunities for data reuse by increasing the trustworthiness of the data. Recognizing the need for improving the quality of citizen science data, we describe quality assessment and quality control (QA/QC) issues for these data and offer perspectives on aspects of improving or ensuring citizen science data quality and for conducting research on related issues.

scholarly journals Assessing citizen science data quality: an invasive species case study

2011 ◽  
Vol 4 (6) ◽  
pp. 433-442 ◽  
Author(s):  
Alycia W. Crall ◽  
Gregory J. Newman ◽  
Thomas J. Stohlgren ◽  
Kirstin A. Holfelder ◽  
Jim Graham ◽  
...  
Keyword(s):  
Invasive Species ◽  
Data Quality ◽  
Citizen Science ◽  
Science Data

scholarly journals Evaluating the Fitness for Use of Citizen Science Data for Wildlife Monitoring

2021 ◽  
Vol 9 ◽  
Author(s):  
Heather A. Fischer ◽  
Leah R. Gerber ◽  
Elizabeth A. Wentz
Keyword(s):  
Data Quality ◽  
Citizen Science ◽  
Ecological Monitoring ◽  
Global Scale ◽  
Third Party ◽  
Data Sets ◽  
Science Data ◽  
Spatial And Temporal Scales ◽  
Fine Grained ◽  
Assessment Approach

Contributory citizen science programs focused on ecological monitoring can produce fine-grained and expansive data sets across spatial and temporal scales. With this data collection potential, citizen scientists can significantly impact the ability to monitor ecological patterns. However, scientists still harbor skepticism about using citizen science data in their work, generally due to doubts about data quality. Numerous peer-reviewed articles have addressed data quality in citizen science. Yet, many of these methods are not useable by third-party scientists (scientists who are not directly involved in the citizen science program). In addition, these methods generally capture internal data quality rather than a dataset’s potential to be used for a specific purpose. Assessing data fitness for use represents a promising approach to evaluating data accuracy and quality for different applications and contexts. In this article, we employ a Spatial, Temporal, Aptness, and Application (STAAq) assessment approach to assess data fitness for use of citizen science datasets. We tested the STAAq assessment approach through a case study examining the distribution of caribou in Denali National Park and Preserve. Three different datasets were used in the test, Map of Life data (a global scale citizen science mobile application for recording species observations), Ride Observe and Record data (a program sponsored by the park staff where incentivized volunteers observe species in the park), and conventionally collected radio collar data. The STAAq assessment showed that the Map of Life and Ride Observe and Record program data are fit for monitoring caribou distribution in the park. This data fitness for use approach is a promising way to assess the external quality of a dataset and its fitness to address particular research or monitoring questions. This type of assessment may help citizen science skeptics see the value and potential of citizen science collected data and encourage the use of citizen science data by more scientists.

scholarly journals Using a Citizen Science Approach with German Horse Owners to Study the Locomotion Behaviour of Horses on Pasture

2020 ◽  
Vol 12 (5) ◽  
pp. 1835
Author(s):  
Anja Schmitz ◽  
Bettina Tonn ◽  
Ann-Kathrin Schöppner ◽  
Johannes Isselstein
Keyword(s):  
Land Use ◽  
Citizen Science ◽  
Agricultural Land ◽  
Agricultural Research ◽  
Real Life ◽  
Sustainable Land Use ◽  
Walking Distance ◽  
Pasture Management ◽  
Science Approach ◽  
Simple Technology

Engaging farmers as citizen scientists may be a cost-efficient way to answering applied research questions aimed at more sustainable land use. We used a citizen science approach with German horse farmers with a dual goal. Firstly, we tested the practicability of this approach for answering ‘real-life’ questions in variable agricultural land-use systems. Secondly, we were interested in the knowledge it can provide about locomotion of horses on pasture and the management factors influencing this behaviour. Out of 165 volunteers, we selected 40 participants to record locomotion of two horses on pasture and provide information on their horse husbandry and pasture management. We obtained complete records for three recording days per horse from 28 participants, resulting in a dataset on more individual horses than any other Global Positioning System study published in the last 30 years. Time spent walking was greatest for horses kept in box-stall stables, and walking distance decreased with increasing grazing time. This suggests that restrictions in pasture access may increase stress on grass swards through running and trampling, severely challenging sustainable pasture management. Our study, involving simple technology, clear instructions and rigorous quality assessment, demonstrates the potential of citizen science actively involving land managers in agricultural research.

scholarly journals The Use of Citizen Science to Achieve Multivariate Management Goals on Public Lands

Diversity ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 293
Author(s):  
Sara Souther ◽  
Vincent Randall ◽  
Nanebah Lyndon
Keyword(s):  
Citizen Science ◽  
Land Management ◽  
Ecological Integrity ◽  
Public Land ◽  
Suitable Habitat ◽  
Science Data ◽  
Public Land Management ◽  
Federal Land ◽  
Botanical Research ◽  
Federal Land Management

Federal land management agencies in the US are tasked with maintaining the ecological integrity of over 2 million km2 of land for myriad public uses. Citizen science, operating at the nexus of science, education, and outreach, offers unique benefits to address socio-ecological questions and problems, and thus may offer novel opportunities to support the complex mission of public land managers. Here, we use a case study of an iNaturalist program, the Tribal Nations Botanical Research Collaborative (TNBRC), to examine the use of citizen science programs in public land management. The TNBRC collected 2030 observations of 34 plant species across the project area, while offering learning opportunities for participants. Using occurrence data, we examined observational trends through time and identified five species with 50 or fewer digital observations to investigate as species of possible conservation concern. We compared predictive outcomes of habitat suitability models built using citizen science data and Forest Inventory and Analysis (FIA) data. Models exhibited high agreement, identifying the same underlying predictors of species occurrence and, 95% of the time, identifying the same pixels as suitable habitat. Actions such as staff training on data use and interpretation could enhance integration of citizen science in Federal land management.

scholarly journals Abundant Citizen Science Data Reveal That the Peacock Butterfly Aglais io Recently Became Bivoltine in Belgium

Insects ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 683
Author(s):  
Marc Herremans ◽  
Karin Gielen ◽  
Jos Van Kerckhoven ◽  
Pieter Vanormelingen ◽  
Wim Veraghtert ◽  
...  
Keyword(s):  
Citizen Science ◽  
Western Europe ◽  
Environmental Changes ◽  
Early Summer ◽  
Science Data ◽  
The Public ◽  
Online Portal ◽  
Spring Generation ◽  
Reproductive Cycles ◽  
New Generation

The peacock butterfly is abundant and widespread in Europe. It is generally believed to be univoltine (one generation per year): adults born in summer overwinter and reappear again in spring to reproduce. However, recent flight patterns in western Europe mostly show three peaks during the year: a first one in spring (overwintering butterflies), a second one in early summer (offspring of the spring generation), and a third one in autumn. It was thus far unclear whether this autumn flight peak was a second new generation or consisted of butterflies flying again in autumn after a summer rest (aestivation). The life cycle of one of Europe’s most common butterflies is therefore still surprisingly inadequately understood. We used hundreds of thousands of observations and thousands of pictures submitted by naturalists from the public to the online portal observation.orgin Belgium and analyzed relations between flight patterns, condition (wear), reproductive cycles, peak abundances, and phenology to clarify the current life history. We demonstrate that peacocks have shifted towards two new generations per year in recent decades. Mass citizen science data in online portals has become increasingly important in tracking the response of biodiversity to rapid environmental changes such as climate change.

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