scholarly journals Designing online species identification tools for biological recording: the impact on data quality and citizen science learning

PeerJ ◽  
2019 ◽  
Vol 6 ◽  
pp. e5965 ◽  
Author(s):  
Nirwan Sharma ◽  
Laura Colucci-Gray ◽  
Advaith Siddharthan ◽  
Richard Comont ◽  
René van der Wal
Keyword(s):  
Species Identification ◽  
Citizen Science ◽  
Scientific Data ◽  
Science Data ◽  
Lay People ◽  
Digital Identification ◽  
Quality Of Learning ◽  
The Impact ◽  
Interface Type

In recent years, the number and scale of environmental citizen science programmes that involve lay people in scientific research have increased rapidly. Many of these initiatives are concerned with the recording and identification of species, processes which are increasingly mediated through digital interfaces. Here, we address the growing need to understand the particular role of digital identification tools, both in generating scientific data and in supporting learning by lay people engaged in citizen science activities pertaining to biological recording communities. Starting from two well-known identification tools, namely identification keys and field guides, this study focuses on the decision-making and quality of learning processes underlying species identification tasks, by comparing three digital interfaces designed to identify bumblebee species. The three interfaces varied with respect to whether species were directly compared or filtered by matching on visual features; and whether the order of filters was directed by the interface or a user-driven open choice. A concurrent mixed-methods approach was adopted to compare how these different interfaces affected the ability of participants to make correct and quick species identifications, and to better understand how participants learned through using these interfaces. We found that the accuracy of identification and quality of learning were dependent upon the interface type, the difficulty of the specimen on the image being identified and the interaction between interface type and ‘image difficulty’. Specifically, interfaces based on filtering outperformed those based on direct visual comparison across all metrics, and an open choice of filters led to higher accuracy than the interface that directed the filtering. Our results have direct implications for the design of online identification technologies for biological recording, irrespective of whether the goal is to collect higher quality citizen science data, or to support user learning and engagement in these communities of practice.

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 Citizen Science Tools Reveal Changes in Estuarine Water Quality Following Demolition of Buildings

2021 ◽  
Vol 13 (9) ◽  
pp. 1683
Author(s):  
Nandini Menon ◽  
Grinson George ◽  
Rajamohananpillai Ranith ◽  
Velakandy Sajin ◽  
Shreya Murali ◽  
...  
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Citizen Science ◽  
Secchi Depth ◽  
Lake Water Quality ◽  
Demolition Waste ◽  
Water Colour ◽  
Water Quality Variables ◽  
The Impact

Turbidity and water colour are two easily measurable properties used to monitor pollution. Here, we highlight the utility of a low-cost device—3D printed, hand-held Mini Secchi disk (3DMSD) with Forel-Ule (FU) colour scale sticker on its outer casing—in combination with a mobile phone application (‘TurbAqua’) that was provided to laymen for assessing the water quality of a shallow lake region after demolition of four high-rise buildings on the shores of the lake. The demolition of the buildings in January 2020 on the banks of a tropical estuary—Vembanad Lake (a Ramsar site) in southern India—for violation of Indian Coastal Regulation Zone norms created public uproar, owing to the consequences of subsequent air and water pollution. Measurements of Secchi depth and water colour using the 3DMSD along with measurements of other important water quality variables such as temperature, salinity, pH, and dissolved oxygen (DO) using portable instruments were taken for a duration of five weeks after the demolition to assess the changes in water quality. Paired t-test analyses of variations in water quality variables between the second week of demolition and consecutive weeks up to the fifth week showed that there were significant increases in pH, dissolved oxygen, and Secchi depth over time, i.e., the impact of demolition waste on the Vembanad Lake water quality was found to be relatively short-lived, with water clarity, colour, and DO returning to levels typical of that period of year within 4–5 weeks. With increasing duration after demolition, there was a general decrease in the FU colour index to 17 at most stations, but it did not drop to 15 or below, i.e., towards green or blue colour indicating clearer waters, during the sampling period. There was no significant change in salinity from the second week to the fifth week after demolition, suggesting little influence of other factors (e.g., precipitation or changes in tidal currents) on the inferred impact of demolition waste. Comparison with pre-demolition conditions in the previous year (2019) showed that the relative changes in DO, Secchi depth, and pH were very high in 2020, clearly depicting the impact of demolition waste on the water quality of the lake. Match-ups of the turbidity of the water column immediately before and after the demolition using Sentinel 2 data were in good agreement with the in situ data collected. Our study highlights the power of citizen science tools in monitoring lakes and managing water resources and articulates how these activities provide support to Sustainable Development Goal (SDG) targets on Health (Goal 3), Water quality (Goal 6), and Life under the water (Goal 14).

The impact of stigma and discrimination on the quality of life and social disability in persons with a diagnosis of mental disorder. A pilot study

2017 ◽  
Vol 41 (S1) ◽  
pp. S571-S571
Author(s):  
T.M. Gondek ◽  
K. Kotowicz ◽  
A. Kiejna
Keyword(s):  
Quality Of Life ◽  
Pilot Study ◽  
Mental Disorders ◽  
Mental Disorder ◽  
Public Information ◽  
Scientific Data ◽  
Social Disability ◽  
Stigma And Discrimination ◽  
The Impact

Stigma and discrimination of persons diagnosed with mental disorder is a common issue. In many European countries, research studies on the prevalence and implications of this problem are conducted in order to better understand how to overcome it. In Poland, there is a scarcity of such studies, what results in neglecting this issue by the policy makers. The objective of the study is to assess the prevalence of stigma and discrimination affecting the patients hospitalized in psychiatric day units and in-patient wards between 2016–2017 as well as to analyze the relationship between the stigma and the quality of life and social disability in persons with a mental disorder diagnosis of F20–F48 according to ICD-10, aged 18–65, in a day ward and an in-patient ward settings. The pilot study presents the data gathered from a preliminary sample of 20 patients of both genders diagnosed with the aforementioned mental disorders, equaling 10 per cent of the targeted total study sample. The quality of life is assessed with WHOQOL-Bref, WHO-5 questionnaire and Rosenberg self-esteem scale, while social disability is measured with the second version of the Groningen Social Disabilities Schedule. The assessment of the impact of stigma on the social disability of persons with mental disorders and their quality of life can be useful in the context of developing evidence-based interventions for these persons, while it could also provide the scientific data to support public information campaigns aiming at tackling the stigma against persons with mental disorders in Poland.Disclosure of InterestThe authors have not supplied their declaration of competing interest.

scholarly journals Analisis Efektifitas Penyelenggaraan Pembelajaran Daring di Sekolah Dasar Pada Masa Pandemi Covid-19

2021 ◽  
Vol 1 (1) ◽  
pp. 41-49
Author(s):  
Melia Astuti
Keyword(s):  
Online Learning ◽  
Research Method ◽  
Learning Support ◽  
Internet Connection ◽  
Quality Of Learning ◽  
Motivation To Participate ◽  
The Impact ◽  
Support Devices

Abstrak Bahasa IndonesiaPenelitian ini bertujuan untuk mengetahui dampak pelaksanaan pembelajaran daring terhadap pengajar dan kualitas pembelajaran. Metode penelitian ini adalah survei dengan instrument angket likert. Hasil penelitian ini menunjukan bahwa tingkat keefektifan pembelajaran daring dimasa pandemi Covid-19 adalah 39,6%, artinya berada pada ketegori rendah. Beberapa kendala yang ditemukan dalam pelaksanaan pembelajaran daring di masa pendemi Covid-19 adalah: pengajar kesulitan membangun komunikasi dua arah dengan siswa, terjadi miss komunikasi baik antara siswa dengan pengajar, maupun wali siswa dengan pengajar, perangkat pendukung pembelajaran daring kurang memadai, koneksi internet kurang baik, dan motivasi belajar siswa dalam mengikuti pembelajaran menurun.Abstract in englishThis study aims to determine the impact of the implementation of online learning on teachers and the quality of learning. This research method is a survey with a Likert questionnaire instrument. The results of this study indicate that the level of effectiveness of online learning during the Covid-19 pandemic was 39.6%, which is in the low category. Some of the obstacles found in the implementation of online learning during the Covid-19 epidemic were: teachers had difficulty building two-way communication with students, there was a miss of communication between students and teachers, as well as student guardians and teachers, inadequate online learning support devices, insufficient internet connection good, and students' motivation to participate in learning decreased.

Outlier detection methods to improve the quality of citizen science data

2020 ◽  
Vol 64 (11) ◽  
pp. 1825-1833
Author(s):  
Jennifer S. Li ◽  
Andreas Hamann ◽  
Elisabeth Beaubien
Keyword(s):  
Outlier Detection ◽  
Citizen Science ◽  
Detection Methods ◽  
Science Data

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 Analytical guidelines to increase the value of citizen science data: using eBird data to estimate species occurrence

2019 ◽  
Author(s):  
A Johnston ◽  
WM Hochachka ◽  
ME Strimas-Mackey ◽  
V Ruiz Gutierrez ◽  
OJ Robinson ◽  
...  
Keyword(s):  
Data Processing ◽  
Citizen Science ◽  
Model Performance ◽  
Species Distributions ◽  
Ecological Knowledge ◽  
Sample Sizes ◽  
Science Data ◽  
Science Projects ◽  
Wide Range ◽  
The Impact

AbstractCitizen science data are valuable for addressing a wide range of ecological research questions, and there has been a rapid increase in the scope and volume of data available. However, data from large-scale citizen science projects typically present a number of challenges that can inhibit robust ecological inferences. These challenges include: species bias, spatial bias, and variation in effort.To demonstrate addressing key challenges in analysing citizen science data, we use the example of estimating species distributions with data from eBird, a large semi-structured citizen science project. We estimate two widely applied metrics of species distributions: encounter rate and occupancy probability. For each metric, we assess the impact of data processing steps that either degrade or refine the data used in the analyses. We also test whether differences in model performance are maintained at different sample sizes.Model performance improved when data processing and analytical methods addressed the challenges arising from citizen science data. The largest gains in model performance were achieved with: 1) the use of complete checklists (where observers report all the species they detect and identify); and 2) the use of covariates describing variation in effort and detectability for each checklist. Occupancy models were more robust to a lack of complete checklists and effort variables. Improvements in model performance with data refinement were more evident with larger sample sizes.Here, we describe processes to refine semi-structured citizen science data to estimate species distributions. We demonstrate the value of complete checklists, which can inform the design and adaptation of citizen science projects. We also demonstrate the value of information on effort. The methods we have outlined are also likely to improve other forms of inference, and will enable researchers to conduct robust analyses and harness the vast ecological knowledge that exists within citizen science data.

scholarly journals Citizen science with colour blindness: A case study on the Forel-Ule scale

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249755
Author(s):  
Olivier Burggraaff ◽  
Sanjana Panchagnula ◽  
Frans Snik
Keyword(s):  
Citizen Science ◽  
Data Entry ◽  
Science Data ◽  
Training Materials ◽  
Colour Scale ◽  
The Social ◽  
Uncertainty Estimates ◽  
Colour Blindness ◽  
The Impact

Many citizen science projects depend on colour vision. Examples include classification of soil or water types and biological monitoring. However, up to 1 in 11 participants are colour blind. We simulate the impact of various forms of colour blindness on measurements with the Forel-Ule scale, which is used to measure water colour by eye with a 21-colour scale. Colour blindness decreases the median discriminability between Forel-Ule colours by up to 33% and makes several colour pairs essentially indistinguishable. This reduces the precision and accuracy of citizen science data and the motivation of participants. These issues can be addressed by including uncertainty estimates in data entry forms and discussing colour blindness in training materials. These conclusions and recommendations apply to colour-based citizen science in general, including other classification and monitoring activities. Being inclusive of the colour blind increases both the social and scientific impact of citizen science.

scholarly journals An investigation into the spatiotemporal patterns of the Nymphalid butterfly Vagrans egista sinha (Kollar, [1844])

2022 ◽  
Author(s):  
Paul Pop ◽  
Kuldeep Singh Barwal ◽  
Randeep Singh ◽  
Puneet Pandey ◽  
Harminder Pal Singh ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Citizen Science ◽  
Range Shift ◽  
Range Extension ◽  
Science Data ◽  
The West ◽  
North West ◽  
The North ◽  
Spatial Differences ◽  
The Impact

Vagrans egista sinha (Kollar, [1844]), the Himalayan Vagrant is a subspecies of Nymphalid (Brush-footed) butterflies spread across Asia, whose western limit is in the north-west India. Observations of this subspecies have considerably increased over the past half-a-decade, with a spike in new sightings to the west of their previously known range. This has been considered as a range extension. The current study reports new records of this species from Bilaspur District, Himachal Pradesh, India (which are the first records for the district), through systematic and opportunistic sampling. This raises the question of whether the purported range extension towards the west could instead be a range shift or vagrancy, and whether there is any shift in elevational ranges in the populations across their known range. Questions pertaining to spatial differences in elevational ranges and seasonal variation, across their range, also piqued our curiosity. Using data from academic sources (such as published literature and museum collections), supplemented by data from public participation in scientific research and personal observations, these research questions are addressed. The accuracy of results when using citizen science data is also explored using the same dataset, focused on the impact of method of extraction of coordinates, and elevation derived from it under different scenarios. It was discovered that there has not been a range shift (either longitudinal or latitudinal) and observations do not suggest vagrancy but a case of range extension. Other results indicated that there was no climb of population to higher elevations, no spatial differences in elevational ranges in the populations, or seasonal variation in activities across their range. It was also discovered that the method of data collection by, and extraction from, citizen science databases, can influence the accuracy of the results. Some problems involved in collecting data are discussed, and remedial solutions are suggested.

scholarly journals Quality of e-learners’ time and learning performance beyond quantitative time-on-task

2011 ◽  
Vol 12 (5) ◽  
pp. 125 ◽  
Author(s):  
Margarida Romero ◽  
Elena Barberà
Keyword(s):  
Online Education ◽  
Time Of Day ◽  
Learning Activities ◽  
Learning Performance ◽  
Time On Task ◽  
Time Pattern ◽  
Learning Time ◽  
Quality Of Learning ◽  
The Impact

Along with the amount of time spent learning (or time-on-task), the quality of learning time has a real influence on learning performance. Quality of time in online learning depends on students’ time availability and their willingness to devote quality cognitive time to learning activities. However, the quantity and quality of the time spent by adult e-learners on learning activities can be reduced by professional, family, and social commitments. Considering that the main time pattern followed by most adult e-learners is a professional one, it may be beneficial for online education programs to offer a certain degree of flexibility in instructional time that might allow adult learners to adjust their learning times to their professional constraints. However, using the time left over once professional and family requirements have been fulfilled could lead to a reduction in quality time for learning. This paper starts by introducing the concept of quality of learning time from an online student-centred perspective. The impact of students’ time-related variables (working hours, time-on-task engagement, time flexibility, time of day, day of week) is then analyzed according to individual and collaborative grades achieved during an online master’s degree program. The data show that both students’ time flexibility (<em>r</em> = .98) and especially their availability to learn in the morning are related to better grades in individual (<em>r</em> = .93) and collaborative activities (<em>r</em> = .46).

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