Beyond the Noise: Open Source Soundscapes. A mixed methodology to analyze and plan small, quiet areas on the local scale, applying the soundscape approach, the citizen science paradigm, and open source technology

2017 ◽  
Vol 141 (5) ◽  
pp. 3622-3622 ◽  
Author(s):  
Antonella Radicchi
Keyword(s):  
Open Source ◽  
Citizen Science ◽  
Local Scale ◽  
Mixed Methodology

scholarly journals CWDAT—An Open-Source Tool for the Visualization and Analysis of Community-Generated Water Quality Data

2021 ◽  
Vol 10 (4) ◽  
pp. 207
Author(s):  
Annie Gray ◽  
Colin Robertson ◽  
Rob Feick
Keyword(s):  
Water Quality ◽  
Data Quality ◽  
Capacity Building ◽  
Open Source ◽  
Citizen Science ◽  
Water Resource ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
User Engagement ◽  
Community Based

Citizen science initiatives span a wide range of topics, designs, and research needs. Despite this heterogeneity, there are several common barriers to the uptake and sustainability of citizen science projects and the information they generate. One key barrier often cited in the citizen science literature is data quality. Open-source tools for the analysis, visualization, and reporting of citizen science data hold promise for addressing the challenge of data quality, while providing other benefits such as technical capacity-building, increased user engagement, and reinforcing data sovereignty. We developed an operational citizen science tool called the Community Water Data Analysis Tool (CWDAT)—a R/Shiny-based web application designed for community-based water quality monitoring. Surveys and facilitated user-engagement were conducted among stakeholders during the development of CWDAT. Targeted recruitment was used to gather feedback on the initial CWDAT prototype’s interface, features, and potential to support capacity building in the context of community-based water quality monitoring. Fourteen of thirty-two invited individuals (response rate 44%) contributed feedback via a survey or through facilitated interaction with CWDAT, with eight individuals interacting directly with CWDAT. Overall, CWDAT was received favourably. Participants requested updates and modifications such as water quality thresholds and indices that reflected well-known barriers to citizen science initiatives related to data quality assurance and the generation of actionable information. Our findings support calls to engage end-users directly in citizen science tool design and highlight how design can contribute to users’ understanding of data quality. Enhanced citizen participation in water resource stewardship facilitated by tools such as CWDAT may provide greater community engagement and acceptance of water resource management and policy-making.

Citizen Science and Open Source Labs

2015 ◽  
pp. 73-83
Author(s):  
Joan Horvath ◽  
Rich Cameron
Keyword(s):  
Open Source ◽  
Citizen Science

scholarly journals An Open-source Dual-beam Spectrophotometer for Citizen-science-based Water Quality Monitoring

HardwareX ◽  
2021 ◽  
pp. e00241
Author(s):  
Jiansheng Feng ◽  
Banafsheh Khakipoor ◽  
Jacob May ◽  
Melissa Mulford ◽  
Joshua Davis ◽  
...  
Keyword(s):  
Water Quality ◽  
Open Source ◽  
Citizen Science ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Dual Beam

An EU-wide citizen science network to monitor hydrological conditions in intermittent rivers and ephemeral streams

2020 ◽  
Author(s):  
Eric Sauquet ◽  
Ilja van Meerveld ◽  
Cath Sefton ◽  
Josep Fortesa ◽  
Helena Ramos Ribeiro ◽  
...  
Keyword(s):  
Citizen Science ◽  
Current Flow ◽  
Local Scale ◽  
Ephemeral Streams ◽  
Intermittent Streams ◽  
Flow State ◽  
Intermittent Rivers ◽  
Flow Intermittence ◽  
International Initiative

<p>Studying Intermittent Rivers and Ephemeral Streams (IRES) requires regular observations of streamflow. Unfortunately, intermittent streams are poorly monitored, particularly in temperate climates. To fill gaps in knowledge of the dynamics of intermittent streams, a pilot initiative within the SMIRES project (Datry et al., 2017, https://www.smires.eu/) was launched in April 2019. This initiative invited citizens to submit observations for a large number of European intermittent streams.</p><p>The goal was collecting datasets that can be used in robust scientific inquiries:</p><p>-             To identify IRES at the European scale. Everyone was encouraged to report the flow state for any stream in Europe at any time during 2019;</p><p>-             To investigate the dynamics of flow intermittence by repeating field observations along an IRES at least once each month and if possible at multiple locations.</p><p>The CrowdWater app (https://crowdwater.ch/en/crowdwaterapp-en/) was used to collect the observations. Each contributor was asked to take a picture of the stream and to identify the current flow state of the stream as one of six classes, from “dry” to “flowing”. The citizen science network has collected, in eight months, more than 3500 observations in ~500 river reaches across 15 countries.</p><p>In this presentation, we will discuss the benefits and the limitations of this citizen science effort (i.e., how these data complement the information provided by gauging stations, how and why the collected data were used by the main contributors, how participants can be engaged in the long-term etc.). We will compare the success of this international initiative to other regional or local scale initiatives.</p><p>References:</p><p>Datry, T., Singer, G., Sauquet, E., Jorda-Capdevilla, D., Von Schiller, D., Subbington, R., Magand, C., Pařil, P., Miliša, M., Acuña, V., Alves, M., Augeard, B., Brunke, M., Cid, N., Csabai, Z., England, J., Froebrich, J., Koundouri, P., Lamouroux, N., Martí, E., Morais, M., Munné, A., Mutz, M., Pesic, V., Previšić, A., Reynaud, A., Robinson, C., Sadler, J., Skoulikidis, N., Terrier, B., Tockner, K., Vesely, D., Zoppini, A (2017) Science and Management of Intermittent Rivers and Ephemeral Streams (SMIRES). Research Ideas and Outcomes 3: e21774. https://doi.org/10.3897/rio.3.e21774</p>

scholarly journals An open-source, citizen science and machine learning approach to analyse subsea movies

2021 ◽  
Vol 9 ◽  
Author(s):  
Victor Anton ◽  
Jannes Germishuys ◽  
Per Bergström ◽  
Mats Lindegarth ◽  
Matthias Obst
Keyword(s):  
Machine Learning ◽  
Open Source ◽  
Citizen Science ◽  
High Performance ◽  
Marine Protected Area ◽  
Cold Water ◽  
Biological Data ◽  
Machine Learning Algorithms ◽  
Test Machine ◽  
Ecological Research

The increasing access to autonomously-operated technologies offer vast opportunities to sample large volumes of biological data. However, these technologies also impose novel demands on ecologists who need to apply tools for data management and processing that are efficient, publicly available and easy to use. Such tools are starting to be developed for a wider community and here we present an approach to combine essential analytical functions for analysing large volumes of image data in marine ecological research. This paper describes the Koster Seafloor Observatory, an open-source approach to analysing large amounts of subsea movie data for marine ecological research. The approach incorporates three distinct modules to: manage and archive the subsea movies, involve citizen scientists to accurately classify the footage and, finally, train and test machine learning algorithms for detection of biological objects. This modular approach is based on open-source code and allows researchers to customise and further develop the presented functionalities to various types of data and questions related to analysis of marine imagery. We tested our approach for monitoring cold water corals in a Marine Protected Area in Sweden using videos from remotely-operated vehicles (ROVs). Our study resulted in a machine learning model with an adequate performance, which was entirely trained with classifications provided by citizen scientists. We illustrate the application of machine learning models for automated inventories and monitoring of cold water corals. Our approach shows how citizen science can be used to effectively extract occurrence and abundance data for key ecological species and habitats from underwater footage. We conclude that the combination of open-source tools, citizen science systems, machine learning and high performance computational resources are key to successfully analyse large amounts of underwater imagery in the future.

scholarly journals A continental measure of urbanness predicts avian response to local urbanization

2019 ◽  
Author(s):  
Corey Thomas Callaghan ◽  
Richard E. Major ◽  
William K. Cornwell ◽  
Ailstair G. B. Poore ◽  
John Wilshire ◽  
...  
Keyword(s):  
Citizen Science ◽  
Spatial Scales ◽  
Environmental Parameters ◽  
Local Scale ◽  
Systematic Sampling ◽  
Small Scale ◽  
Science Data ◽  
Continental Scale ◽  
Specific Variation ◽  
Species Specific

Understanding species-specific relationships with their environment is essential for ecology, biogeography, and conservation biology. Moreover, understanding how these relationships change with spatial scale is critical to mitigating potential threats to biodiversity. But methods which measure inter-specific variation in responses to environmental parameters, generalizable across multiple spatial scales, are lacking. We used broad-scale citizen science data, over a continental scale, integrated with remotely-sensed products, to produce a measure of response to urbanization for a given species at a continental-scale. We then compared these responses to modelled responses to urbanization at a local-scale, based on systematic sampling within a series of small cities. For 49 species which had sufficient data for modelling, we found a significant relationship (R2 = 0.51) between continental-scale urbanness and local-scale urbanness. Our results suggest that continental-scale responses are representative of small-scale responses to urbanization. We also found that relatively few citizen science observations (~250) are necessary for reliable estimates of continental-scale urban scores to predict local-scale response to urbanization. Our method of producing species-specific urban scores is robust and can be generalized to other taxa and other environmental variables with relative ease.

scholarly journals Citizen science on a local scale: the Plants of Concern program

2012 ◽  
Vol 10 (6) ◽  
pp. 321-323 ◽  
Author(s):  
Kayri Havens ◽  
Pati Vitt ◽  
Susanne Masi
Keyword(s):  
Citizen Science ◽  
Local Scale

Success of Open Source in Developing Countries

2015 ◽  
pp. 1126-1142 ◽  
Author(s):  
Alireza Amrollahi ◽  
Mohammad Khansari ◽  
Amir Manian
Keyword(s):  
Developing Countries ◽  
Project Management ◽  
Software Development ◽  
Open Source ◽  
Cultural Context ◽  
Mixed Methodology ◽  
Management Tools ◽  
Factors Affecting ◽  
The Social ◽  
Using Data

Open Source approach has been recognized as one of the best methods for software development in developing countries. Previous research however underemphasized different aspects of Open Source Software (OSS) success in context of developing countries compared to western context. In this research the authors use exploratory mixed methodology to study measures of and factors affecting OSS success with emphasize on the social and cultural context of Iran. In the qualitative section of the research 13 interviews with experts of the field have been conducted and the result is reflected in the research model. In the quantitative section, five research hypotheses have been evaluated by using data of 109 Iranian projects from sourceforge.net repository. The results indicate that the license type and use of project management tools may affect the success of OSS. The authors finally conclude that OSS research especially in the field of OSS success may lead to different findings in different contexts.

scholarly journals CITIZEN SCIENCE FOR WATER QUALITY MONITORING APPLYING FOSS

2019 ◽  
Vol XLII-4/W14 ◽  
pp. 119-126
Author(s):  
S. Jovanovic ◽  
D. Carrion ◽  
M. A. Brovelli
Keyword(s):  
Water Quality ◽  
Open Source ◽  
Citizen Science ◽  
Initial Phase ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Smartphone Applications ◽  
Efficient Tool ◽  
State Of Art

<p><strong>Abstract.</strong> Citizen science is an efficient tool for data collection for scientific projects. In the framework of SIMILE Interreg Italy-Switzerland project, the citizen’s contribution to monitor the quality of lakes water has been envisaged. In the initial phase of this research, state of art of citizen science and water quality monitoring was investigated. The analysis of past and current projects, governed by different organizations and communities, pointed out a variety of tasks that can be accomplished by citizens. In these studies, authors stressed suitability of smartphones for the fulfilment of various assignments given to citizens. Due to that, in this research, different smartphone applications for water quality monitoring were tested and analyzed. Despite the fact that many applications for water quality monitoring are freely available, none of them is open source. Hence, this paper is proposing the design of a new application, for the purposes of SIMILE project, that will be free and open source, addressing not just users but also developers giving them a possibility for customization and improvement.</p>

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