Increasing trust in new data sources: crowdsourcing image classification for ecology

Crowdsourcing methods facilitate the production of scientific information by non-experts. This form of citizen science (CS) is becoming a key source of complementary data in many fields to inform data-driven decisions and study challenging problems. However, concerns about the validity of these data often constrain their utility. In this paper, we focus on the use of citizen science data in addressing complex challenges in environmental conservation. We consider this issue from three perspectives. First, we present a literature scan of papers that have employed Bayesian models with citizen science in ecology. Second, we compare several popular majority vote algorithms and introduce a Bayesian item response model that estimates and accounts for participants' abilities after adjusting for the difficulty of the images they have classified. The model also enables participants to be clustered into groups based on ability. Third, we apply the model in a case study involving the classification of corals from underwater images from the Great Barrier Reef, Australia. We show that the model achieved superior results in general and, for difficult tasks, a weighted consensus method that uses only groups of experts and experienced participants produced better performance measures. Moreover, we found that participants learn as they have more classification opportunities, which substantially increases their abilities over time. Overall, the paper demonstrates the feasibility of CS for answering complex and challenging ecological questions when these data are appropriately analysed. This serves as motivation for future work to increase the efficacy and trustworthiness of this emerging source of data.Comment: 25 pages, 10 figure

Improving Legibility of User Interfaces for Low Vision Conditions with a Crowdsource Platform

The growing importance of inclusive design solutions has prompted this study examining typography legibility and its impact on accessibility for users with low vision conditions. Focusing on factors such as typographic form, letter spacing, and font size, this research seeks to understand the unique demands of low vision individuals and how typography and user interface design can be adapted to improve legibility and accessibility. Previous research has provided insights into various aspects of typography legibility, but a comprehensive approach addressing the specific needs of low vision users has been lacking. This study contributes to the existing body of knowledge by deconstructing user interfaces (UI) and analyze the fundamental elements affecting legibility. By examining various UI elements and their relationship to text, this research offers personalized, integrated solutions for individuals to tailor websites to their unique needs. The proposed platform differentiates itself from existing accessibility overlays (additional software that is intended to detect and address web accessibility issues on web sites) by emphasizing personalization based on individual preferences, leveraging crowdsourcing to create a variety of modification options. Although the proposal's primary focus is on low vision, it has the potential to assist a wide range of users with various needs. Despite some limitations and challenges faced during the project, this study provides insights into the factors contributing to the legibility of various typefaces, emphasizing the importance of customization to cater to specific needs. Future research should continue to explore these factors, further promoting a more inclusive approach to typography in diverse UI contexts

When in doubt ask the crowd : leveraging collective intelligence for improving event detection and machine learning

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Comparing automatic accessibility testing tools

Recently, the Web has become increasingly important as information and many essential ser-vices move to the Web. Accessibility aims to make services to users with disabilities. Web accessibility’s goal is to make the Web accessible, which means disabled people can use the Web. It has been estimated that 15% of the world's population lives with some form of disabil-ity, and the aging population makes web accessibility increasingly important. Similarly, recent legislation Increasingly requires the Web to be accessible to all. Web accessibility evaluation can be done to ensure that the website conforms to the needs of disabled people or legal requirements. There exist different accessibility evaluation meth-ods, each with its benefits and drawbacks, and the methods often complement each other. Automatic testing tools are an important part of accessibility testing. There are many different automatic accessibility evaluation tools to choose from. And previous studies show that tools detect a different number of issues. In this thesis, we compared three automatic accessibility testing tools in terms of how many success criteria they cover, testing speed, and the number of detected issues. Tools were used to test Finnish e-commerce sites and a test site containing a set of accessibility issues. We found that the WAVE was the fastest tool to scan pages. IBM Accessibility Checker covered the greatest number of WCAG success criteria. The number of detected issues de-pends on the selected page and the type of accessibility issues present on the page. In five out of six tested pages, IBM Equal Access Accessibility Checker found the greatest number of issues, and in one out of six pages WAVE found the greatest number of issues

Usability of disaster apps : understanding the perspectives of the public as end-users : a dissertation presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Emergency Management at Massey University, Wellington, New Zealand

Listed in 2020 Dean's List of Exceptional ThesesMultiple smartphone applications (apps) exist that can enhance the public’s resilience to disasters. Despite the capabilities of these apps, they can only be effective if users find them usable. Availability does not automatically translate to usability nor does it guarantee continued usage by the target users. A disaster app will be of little or no value if a user abandons it after the initial download. It is, therefore, essential to understand the users’ perspectives on the usability of disaster apps. In the context of disaster apps, usability entails providing the elements that effectively facilitate users in retrieving critical information, and thus enabling them to make decisions during crises. Establishing good usability for effective systems relies upon focussing on the user whereby technological solutions match the user’s needs and expectations. However, most studies on the usability of disaster context technologies have been conducted with emergency responders, and only a few have investigated the publics’ perspectives as end-users. This doctoral project, written within a ‘PhD-thesis-with-publication’ format, addresses this gap by investigating the usability of disaster apps through the perspectives of the public end-users. The investigation takes an explicitly perceived usability standpoint where the experiences of the end-users are prioritised. Data analysis involved user-centric information to understand the public’s context and the mechanisms of disaster app usability. A mixed methods approach incorporates the qualitative analysis of app store data of 1,405 user reviews from 58 existing disaster apps, the quantitative analysis of 271 survey responses from actual disaster app users, and the qualitative analysis of usability inquiries with 18 members of the public. Insights gathered from this doctoral project highlight that end-users do not anticipate using disaster apps frequently, which poses particular challenges. Furthermore, despite the anticipated low frequency of use, because of the life-safety association of disasters apps, end-users have an expectation that the apps can operate with adequate usability when needed. This doctoral project provides focussed outcomes that consider such user perspectives. First, an app store analysis investigating user reviews identified new usability concerns particular to disaster apps. It highlighted users’ opinion on phone resource usage and relevance of content, among others. More importantly, it defined a new usability factor, app dependability, relating to the life-safety context of disaster apps. App dependability is the degree to which users’ perceive that an app can operate dependably during critical scenarios. Second, the quantitative results from this research have contributed towards producing a usability-continuance model, highlighting the usability factors that affect end-users’ intention to keep or uninstall a disaster app. The key influences for users’ intention to keep disaster apps are: (1) users’ perceptions as to whether the app delivers its function (app utility), (2) whether it does so dependably (app dependability), and (3) whether it presents information that can be easily understood (user-interface output). Subsequently, too much focus on (4) user-interface graphics and (5) user-interface input can encourage users to uninstall apps. Third, the results from the qualitative analysis of the inquiry data provide a basis for developing guidelines for disaster app usability. In the expectation of low level of engagement with disaster app users, the guidelines list recommendations addressing information salience, cognitive load, and trust. This doctoral project provides several contributions to the body of knowledge for usability and disaster apps. It reiterates the importance of investigating the usability of technological products for disasters and showcases the value of user-centric data in understanding usability. It has investigated usability with particular attention to the end-users’ perspectives on the context of disaster apps and, thus, produces a theoretical usability-continuance model to advance disaster app usability research and usability guidelines to encourage responsible design in practice

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

EXPLORING VOLUNTEERED GEOGRAPHIC INFORMATION WITH DATA QUALITY CONTROL FOR INTEGRATED PEST MANAGEMENT

Ph.DDOCTOR OF PHILOSOPH

Impact of Perceived Peer Attitudes and Social Network Diversity on Violent Extremist Intentions

Perceived peer attitudes often influence young adult men’s violent attitudes and intentions, whereas the structure of peer networks can moderate this relationship. For example, people with more diverse social networks are less likely to adopt their close peers’ violent attitudes and behaviors. Despite that, there is currently limited research examining the role of structural features of peer networks in the relationship between perceived peer attitudes and violent extremist attitudes or intentions. Consequently, the current study sought to address this gap in research and answer the following questions: (1) To what extent are perceived peer attitudes, personal attitudes, and violent extremist intentions related to each other? (2) To what extent does the relationship between perceived peer attitudes and violent extremist intentions differ at different levels of social network diversity? The study sample consisted of 340 young adult men (i.e., 18-29 years old). Data collection took place via Amazon Mturk, an online-based crowdsourcing platform. Participants first indicated a social group with which they most strongly identify and listed their five closest male peers from the same group. Next, participants reported their violent extremist attitudes, intentions, and their perceptions of their peers’ opinions. Overall, perceived peer attitudes were positively and significantly associated with violent extremist intentions through their relationship with personal attitudes. The mediating effect, however, was partial: personal attitudes did not fully account for the total association. Furthermore, social network diversity moderated the relationship between personal and perceived peer attitudes: participants with more diverse social networks were less likely to hold beliefs similar to their perceived peer attitudes. In general, study findings were in line with past research on the impact of perceived peer attitudes and social network structure on violent outcomes. Thus, future studies should explore the potential role of other aspects of peer networks in the development of violent extremist attitudes and intentions. Regarding its policy implications, the study highlights the need for social-ecological approaches to counter violent extremism, offering young adult men opportunities for community involvement and growth of social ties

An Interdisciplinary Survey on Origin-destination Flows Modeling: Theory and Techniques

Origin-destination~(OD) flow modeling is an extensively researched subject across multiple disciplines, such as the investigation of travel demand in transportation and spatial interaction modeling in geography. However, researchers from different fields tend to employ their own unique research paradigms and lack interdisciplinary communication, preventing the cross-fertilization of knowledge and the development of novel solutions to challenges. This article presents a systematic interdisciplinary survey that comprehensively and holistically scrutinizes OD flows from utilizing fundamental theory to studying the mechanism of population mobility and solving practical problems with engineering techniques, such as computational models. Specifically, regional economics, urban geography, and sociophysics are adept at employing theoretical research methods to explore the underlying mechanisms of OD flows. They have developed three influential theoretical models: the gravity model, the intervening opportunities model, and the radiation model. These models specifically focus on examining the fundamental influences of distance, opportunities, and population on OD flows, respectively. In the meantime, fields such as transportation, urban planning, and computer science primarily focus on addressing four practical problems: OD prediction, OD construction, OD estimation, and OD forecasting. Advanced computational models, such as deep learning models, have gradually been introduced to address these problems more effectively. Finally, based on the existing research, this survey summarizes current challenges and outlines future directions for this topic. Through this survey, we aim to break down the barriers between disciplines in OD flow-related research, fostering interdisciplinary perspectives and modes of thinking.Comment: 49 pages, 6 figure