cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/tk4j-vx62
title: Wide Band Raised Printed Monopole for Automotive 5G Wireless Communications 

description: This paper introduces a compact Multiple input Multiple output (MIMO) antenna system for vehicular application in the sub-6GHz 5G systems that operates in the middle and high frequency bands from 1.71GHz to 5GHz. The proposed design consists of two symmetrical raised printed monopoles on Flame Retardant 4 (FR4) dielectric material with Electromagnetic Band Gap shape (EBG) to provide defected ground to improve bandwidth impedance and higher isolation across the operating frequency range. The design is an excellent candidate to be implement in a shark-fin housing due to its low-profile characteristics and good electrical performance. The antennas are simulated using HFSS software and then prototypes are made and measured on a one-meter rolled-edge ground plane in an anechoic chamber. The electrical performance results of the proposed design and its MIMO characteristics are discussed and plotted in terms of Voltage Standing Wave Ratio (VSWR), passive isolation, radiation patterns, radiation efficiency, linear average gain (LAG), Diversity Gain (DG), and Envelope Correlation Coefficient (ECC).
DOI: 10.5281/zenodo.5770164
title: Water Sentinels Motivation Survey

description: The Water Sentinels motivation study was conducted within the ongoing H2020 project named ACTION (pArticipatory sCience Toolkit agaInst pollutiON) on citizen science. Volunteers participate to citizen science initiatives for multiple reasons: personal enjoyment, desire for improvement or achievement, establishment of personal relationships, care for the environment, etc.<br> Studying motivation and investigating the factors influencing people participation to citizen science projects is an essential aspect in the analysis of citizen science communities. Understanding the reasons that foster people to engage can support the successful design and implementation of effective participant involvement tasks, as well as pave the way for long-term engagement.<br> The goal of the study is to analyse the motivation to participate of a specific citizen science community focused on fighting water pollution in the Water Sentinels pilot supported by the ACTION project. More info on the pilot available at https://actionproject.eu/citizen-science-pilots/water-sentinels/. The Water Sentinels motivation study is part of the study about motivation in citizen science projects conducted within the ACTION project (https://doi.org/10.5281/zenodo.5753092). The survey was designed using the Coney toolkit and administered using Google Forms. The research object adopts the RO-Crate specification. Files made available within the research object are: <em>*-procedure.ttl</em> contains the RDF representation of the structure of the conversational survey (questions, answers, etc.) using the Survey Ontology <em>*-results.ttl </em>contains the RDF representation of the answers collected using the Survey Ontology <em>*-survey.tll </em>contains a comprehensive RDF representation of the survey data using the Survey Ontology <em>*-results.csv </em>contains the CSV of the collected answers <em>*-results-google-forms</em><em>.csv </em>contains the CSV of the collected answers exported from Google Forms *-<em>script.R</em> is the R script developed to analyse the collected answers *-<em>mean-var-motivating-questions.csv </em>contains the computed mean and average for each question considered (observable variables) *-<em>mean-var-motivating-factor.csv </em>contains the computed mean and average for each motivation factor considered (latent variables) *-<em>correlation-factors-global-motivation.csv </em>contains the correlation analysis between each motivation factor and the global motivation
DOI: 10.5281/zenodo.5770163
title: Water Sentinels Motivation Survey

description: The Water Sentinels motivation study was conducted within the ongoing H2020 project named ACTION (pArticipatory sCience Toolkit agaInst pollutiON) on citizen science. Volunteers participate to citizen science initiatives for multiple reasons: personal enjoyment, desire for improvement or achievement, establishment of personal relationships, care for the environment, etc.<br> Studying motivation and investigating the factors influencing people participation to citizen science projects is an essential aspect in the analysis of citizen science communities. Understanding the reasons that foster people to engage can support the successful design and implementation of effective participant involvement tasks, as well as pave the way for long-term engagement.<br> The goal of the study is to analyse the motivation to participate of a specific citizen science community focused on fighting water pollution in the Water Sentinels pilot supported by the ACTION project. More info on the pilot available at https://actionproject.eu/citizen-science-pilots/water-sentinels/. The Water Sentinels motivation study is part of the study about motivation in citizen science projects conducted within the ACTION project (https://doi.org/10.5281/zenodo.5753092). The survey was designed using the Coney toolkit and administered using Google Forms. The research object adopts the RO-Crate specification. Files made available within the research object are: <em>*-procedure.ttl</em> contains the RDF representation of the structure of the conversational survey (questions, answers, etc.) using the Survey Ontology <em>*-results.ttl </em>contains the RDF representation of the answers collected using the Survey Ontology <em>*-survey.tll </em>contains a comprehensive RDF representation of the survey data using the Survey Ontology <em>*-results.csv </em>contains the CSV of the collected answers <em>*-results-google-forms</em><em>.csv </em>contains the CSV of the collected answers exported from Google Forms *-<em>script.R</em> is the R script developed to analyse the collected answers *-<em>mean-var-motivating-questions.csv </em>contains the computed mean and average for each question considered (observable variables) *-<em>mean-var-motivating-factor.csv </em>contains the computed mean and average for each motivation factor considered (latent variables) *-<em>correlation-factors-global-motivation.csv </em>contains the correlation analysis between each motivation factor and the global motivation
DOI: 10.5281/zenodo.5770198
title: Wow Nature Motivation Survey

description: The Wow Nature motivation study was conducted within the ongoing H2020 project named ACTION (pArticipatory sCience Toolkit agaInst pollutiON) on citizen science. Volunteers participate to citizen science initiatives for multiple reasons: personal enjoyment, desire for improvement or achievement, establishment of personal relationships, care for the environment, etc.<br> Studying motivation and investigating the factors influencing people participation to citizen science projects is an essential aspect in the analysis of citizen science communities. Understanding the reasons that foster people to engage can support the successful design and implementation of effective participant involvement tasks, as well as pave the way for long-term engagement.<br> The goal of the study is to analyse the motivation to participate of a specific citizen science community focused on fighting air pollution in the Wow Nature pilot supported by the ACTION project. More info on the pilot available at https://actionproject.eu/citizen-science-pilots/wow-nature/. The Wow Nature motivation study is part of the study about motivation in citizen science projects conducted within the ACTION project (https://doi.org/10.5281/zenodo.5753092). The survey was designed and administered using the Coney toolkit. The research object adopts the RO-Crate specification. Files made available within the research object are: <em>*-procedure.ttl</em> contains the RDF representation of the structure of the conversational survey (questions, answers, etc.) using the Survey Ontology <em>*-results.ttl </em>contains the RDF representation of the answers collected using the Survey Ontology <em>*-survey.tll </em>contains a comprehensive RDF representation of the survey data using the Survey Ontology <em>*-results.csv </em>contains the CSV of the collected answers *-<em>script.R</em> is the R script developed to analyse the collected answers *-<em>mean-var-motivating-questions.csv </em>contains the computed mean and average for each question considered (observable variables) *-<em>mean-var-motivating-factor.csv </em>contains the computed mean and average for each motivation factor considered (latent variables) *-<em>correlation-factors-global-motivation.csv </em>contains the correlation analysis between each motivation factor and the global motivation
DOI: 10.5281/zenodo.5753123
title: Restart Data Workbench Motivation Survey

description: The Restart Data Workbench motivation study was conducted within the ongoing H2020 project named ACTION (pArticipatory sCience Toolkit agaInst pollutiON) on citizen science. Volunteers participate to citizen science initiatives for multiple reasons: personal enjoyment, desire for improvement or achievement, establishment of personal relationships, care for the environment, etc.<br> Studying motivation and investigating the factors influencing people participation to citizen science projects is an essential aspect in the analysis of citizen science communities. Understanding the reasons that foster people to engage can support the successful design and implementation of effective participant involvement tasks, as well as pave the way for long-term engagement.<br> The goal of the study is to analyse the motivation to participate of a specific citizen science community focused on fighting soil pollution through waste reduction/management in the Restart Data Workbench pilot supported by the ACTION project. More info on the pilot available at https://actionproject.eu/citizen-science-pilots/restart-data-workbench/. The Restart Data Workbench motivation study is part of the study about motivation in citizen science projects conducted within the ACTION project (https://doi.org/10.5281/zenodo.5753092). The survey was designed and administered using the Coney toolkit. The research object adopts the RO-Crate specification. Files made available within the research object are: <em>*-procedure.ttl</em> contains the RDF representation of the structure of the conversational survey (questions, answers, etc.) using the Survey Ontology <em>*-results.ttl </em>contains the RDF representation of the answers collected using the Survey Ontology <em>*-survey.tll </em>contains a comprehensive RDF representation of the survey data using the Survey Ontology <em>*-results.csv </em>contains the CSV of the collected answers *-<em>script.R</em> is the R script developed to analyse the collected answers *-<em>mean-var-motivating-questions.csv </em>contains the computed mean and average for each question considered (observable variables) *-<em>mean-var-motivating-factor.csv </em>contains the computed mean and average for each motivation factor considered (latent variables) *-<em>correlation-factors-global-motivation.csv </em>contains the correlation analysis between each motivation factor and the global motivation
DOI: 10.5281/zenodo.5770197
title: Wow Nature Motivation Survey

description: The Wow Nature motivation study was conducted within the ongoing H2020 project named ACTION (pArticipatory sCience Toolkit agaInst pollutiON) on citizen science. Volunteers participate to citizen science initiatives for multiple reasons: personal enjoyment, desire for improvement or achievement, establishment of personal relationships, care for the environment, etc.<br> Studying motivation and investigating the factors influencing people participation to citizen science projects is an essential aspect in the analysis of citizen science communities. Understanding the reasons that foster people to engage can support the successful design and implementation of effective participant involvement tasks, as well as pave the way for long-term engagement.<br> The goal of the study is to analyse the motivation to participate of a specific citizen science community focused on fighting air pollution in the Wow Nature pilot supported by the ACTION project. More info on the pilot available at https://actionproject.eu/citizen-science-pilots/wow-nature/. The Wow Nature motivation study is part of the study about motivation in citizen science projects conducted within the ACTION project (https://doi.org/10.5281/zenodo.5753092). The survey was designed and administered using the Coney toolkit. The research object adopts the RO-Crate specification. Files made available within the research object are: <em>*-procedure.ttl</em> contains the RDF representation of the structure of the conversational survey (questions, answers, etc.) using the Survey Ontology <em>*-results.ttl </em>contains the RDF representation of the answers collected using the Survey Ontology <em>*-survey.tll </em>contains a comprehensive RDF representation of the survey data using the Survey Ontology <em>*-results.csv </em>contains the CSV of the collected answers *-<em>script.R</em> is the R script developed to analyse the collected answers *-<em>mean-var-motivating-questions.csv </em>contains the computed mean and average for each question considered (observable variables) *-<em>mean-var-motivating-factor.csv </em>contains the computed mean and average for each motivation factor considered (latent variables) *-<em>correlation-factors-global-motivation.csv </em>contains the correlation analysis between each motivation factor and the global motivation
DOI: 10.5281/zenodo.5753122
title: Restart Data Workbench Motivation Survey

description: The Restart Data Workbench motivation study was conducted within the ongoing H2020 project named ACTION (pArticipatory sCience Toolkit agaInst pollutiON) on citizen science. Volunteers participate to citizen science initiatives for multiple reasons: personal enjoyment, desire for improvement or achievement, establishment of personal relationships, care for the environment, etc.<br> Studying motivation and investigating the factors influencing people participation to citizen science projects is an essential aspect in the analysis of citizen science communities. Understanding the reasons that foster people to engage can support the successful design and implementation of effective participant involvement tasks, as well as pave the way for long-term engagement.<br> The goal of the study is to analyse the motivation to participate of a specific citizen science community focused on fighting soil pollution through waste reduction/management in the Restart Data Workbench pilot supported by the ACTION project. More info on the pilot available at https://actionproject.eu/citizen-science-pilots/restart-data-workbench/. The Restart Data Workbench motivation study is part of the study about motivation in citizen science projects conducted within the ACTION project (https://doi.org/10.5281/zenodo.5753092). The survey was designed and administered using the Coney toolkit. The research object adopts the RO-Crate specification. Files made available within the research object are: <em>*-procedure.ttl</em> contains the RDF representation of the structure of the conversational survey (questions, answers, etc.) using the Survey Ontology <em>*-results.ttl </em>contains the RDF representation of the answers collected using the Survey Ontology <em>*-survey.tll </em>contains a comprehensive RDF representation of the survey data using the Survey Ontology <em>*-results.csv </em>contains the CSV of the collected answers *-<em>script.R</em> is the R script developed to analyse the collected answers *-<em>mean-var-motivating-questions.csv </em>contains the computed mean and average for each question considered (observable variables) *-<em>mean-var-motivating-factor.csv </em>contains the computed mean and average for each motivation factor considered (latent variables) *-<em>correlation-factors-global-motivation.csv </em>contains the correlation analysis between each motivation factor and the global motivation
DOI: 10.5281/zenodo.5753229
title: Walk Up Aniene Motivation Survey

description: The Walk Up Aniene motivation study was conducted within the ongoing H2020 project named ACTION (pArticipatory sCience Toolkit agaInst pollutiON) on citizen science. Volunteers participate to citizen science initiatives for multiple reasons: personal enjoyment, desire for improvement or achievement, establishment of personal relationships, care for the environment, etc.<br> Studying motivation and investigating the factors influencing people participation to citizen science projects is an essential aspect in the analysis of citizen science communities. Understanding the reasons that foster people to engage can support the successful design and implementation of effective participant involvement tasks, as well as pave the way for long-term engagement.<br> The goal of the study is to analyse the motivation to participate of a specific citizen science community focused on fighting soil and water pollution in the Walk Up Aniene pilot supported by the ACTION project. More info on the pilot available at https://actionproject.eu/citizen-science-pilots/walk-up-aniene/. The Walk Up Aniene motivation study is part of the study about motivation in citizen science projects conducted within the ACTION project (https://doi.org/10.5281/zenodo.5753092). The survey was designed and administered using the Coney toolkit. The research object adopts the RO-Crate specification. Files made available within the research object are: <em>*-procedure.ttl</em> contains the RDF representation of the structure of the conversational survey (questions, answers, etc.) using the Survey Ontology <em>*-results.ttl </em>contains the RDF representation of the answers collected using the Survey Ontology <em>*-survey.tll </em>contains a comprehensive RDF representation of the survey data using the Survey Ontology <em>*-results.csv </em>contains the CSV of the collected answers *-<em>script.R</em> is the R script developed to analyse the collected answers *-<em>mean-var-motivating-questions.csv </em>contains the computed mean and average for each question considered (observable variables) *-<em>mean-var-motivating-factor.csv </em>contains the computed mean and average for each motivation factor considered (latent variables) *-<em>correlation-factors-global-motivation.csv </em>contains the correlation analysis between each motivation factor and the global motivation
DOI: 10.5281/zenodo.5727476
title: Mapping Mobility Motivation Survey

description: The Mapping Mobility motivation study was conducted within the ongoing H2020 project named ACTION (pArticipatory sCience Toolkit agaInst pollutiON) on citizen science. Volunteers participate to citizen science initiatives for multiple reasons: personal enjoyment, desire for improvement or achievement, establishment of personal relationships, care for the environment, etc.<br> Studying motivation and investigating the factors influencing people participation to citizen science projects is an essential aspect in the analysis of citizen science communities. Understanding the reasons that foster people to engage can support the successful design and implementation of effective participant involvement tasks, as well as pave the way for long-term engagement.<br> The goal of the study is to analyse the motivation to participate of a specific citizen science community focused on fighting air pollution in the Mapping Mobility pilot supported by the ACTION project. More info on the pilot available at https://actionproject.eu/citizen-science-pilots/mapping-mobility/. The Mapping Mobility motivation study is part of the study about motivation in citizen science projects conducted within the ACTION project (https://doi.org/10.5281/zenodo.5753092). The survey was designed and administered using the Coney toolkit. The research object adopts the RO-Crate specification. Files made available within the research object are: <em>*-procedure.ttl</em> contains the RDF representation of the structure of the conversational survey (questions, answers, etc.) using the Survey Ontology <em>*-results.ttl </em>contains the RDF representation of the answers collected using the Survey Ontology <em>*-survey.tll </em>contains a comprehensive RDF representation of the survey data using the Survey Ontology <em>*-results.csv </em>contains the CSV of the answers collected
DOI: 10.5281/zenodo.5753228
title: Walk Up Aniene Motivation Survey

description: The Walk Up Aniene motivation study was conducted within the ongoing H2020 project named ACTION (pArticipatory sCience Toolkit agaInst pollutiON) on citizen science. Volunteers participate to citizen science initiatives for multiple reasons: personal enjoyment, desire for improvement or achievement, establishment of personal relationships, care for the environment, etc.<br> Studying motivation and investigating the factors influencing people participation to citizen science projects is an essential aspect in the analysis of citizen science communities. Understanding the reasons that foster people to engage can support the successful design and implementation of effective participant involvement tasks, as well as pave the way for long-term engagement.<br> The goal of the study is to analyse the motivation to participate of a specific citizen science community focused on fighting soil and water pollution in the Walk Up Aniene pilot supported by the ACTION project. More info on the pilot available at https://actionproject.eu/citizen-science-pilots/walk-up-aniene/. The Walk Up Aniene motivation study is part of the study about motivation in citizen science projects conducted within the ACTION project (https://doi.org/10.5281/zenodo.5753092). The survey was designed and administered using the Coney toolkit. The research object adopts the RO-Crate specification. Files made available within the research object are: <em>*-procedure.ttl</em> contains the RDF representation of the structure of the conversational survey (questions, answers, etc.) using the Survey Ontology <em>*-results.ttl </em>contains the RDF representation of the answers collected using the Survey Ontology <em>*-survey.tll </em>contains a comprehensive RDF representation of the survey data using the Survey Ontology <em>*-results.csv </em>contains the CSV of the collected answers *-<em>script.R</em> is the R script developed to analyse the collected answers *-<em>mean-var-motivating-questions.csv </em>contains the computed mean and average for each question considered (observable variables) *-<em>mean-var-motivating-factor.csv </em>contains the computed mean and average for each motivation factor considered (latent variables) *-<em>correlation-factors-global-motivation.csv </em>contains the correlation analysis between each motivation factor and the global motivation