VGI and crowdsourced data credibility analysis using spam email detection techniques

Volunteered geographic information (VGI) can be considered a subset of crowdsourced data (CSD) and its popularity has recently increased in a number of application areas. Disaster management is one of its key application areas in which the benefits of VGI and CSD are potentially very high. However, quality issues such as credibility, reliability and relevance are limiting many of the advantages of utilising CSD. Credibility issues arise as CSD come from a variety of heterogeneous sources including both professionals and untrained citizens. VGI and CSD are also highly unstructured and the quality and metadata are often undocumented. In the 2011 Australian floods, the general public and disaster management administrators used the Ushahidi Crowd-mapping platform to extensively communicate flood-related information including hazards, evacuations, emergency services, road closures and property damage. This study assessed the credibility of the Australian Broadcasting Corporation’s Ushahidi CrowdMap dataset using a Naïve Bayesian network approach based on models commonly used in spam email detection systems. The results of the study reveal that the spam email detection approach is potentially useful for CSD credibility detection with an accuracy of over 90% using a forced classification methodology

Geospatial crowdsourced data fitness analysis for spatial data infrastructure based disaster management actions

The reporting of disasters has changed from official media reports to citizen reporters who are at the disaster scene. This kind of crowd based reporting, related to disasters or any other events, is often identified as 'Crowdsourced Data' (CSD). CSD are freely and widely available thanks to the current technological advancements. The quality of CSD is often problematic as it is often created by the citizens of varying skills and backgrounds. CSD is considered unstructured in general, and its quality remains poorly defined. Moreover, the CSD's location availability and the quality of any available locations may be incomplete. The traditional data quality assessment methods and parameters are also often incompatible with the unstructured nature of CSD due to its undocumented nature and missing metadata. Although other research has identified credibility and relevance as possible CSD quality assessment indicators, the available assessment methods for these indicators are still immature. In the 2011 Australian floods, the citizens and disaster management administrators used the Ushahidi Crowd-mapping platform and the Twitter social media platform to extensively communicate flood related information including hazards, evacuations, help services, road closures and property damage. This research designed a CSD quality assessment framework and tested the quality of the 2011 Australian floods' Ushahidi Crowdmap and Twitter data. In particular, it explored a number of aspects namely, location availability and location quality assessment, semantic extraction of hidden location toponyms and the analysis of the credibility and relevance of reports. This research was conducted based on a Design Science (DS) research method which is often utilised in Information Science (IS) based research. Location availability of the Ushahidi Crowdmap and the Twitter data assessed the quality of available locations by comparing three different datasets i.e. Google Maps, OpenStreetMap (OSM) and Queensland Department of Natural Resources and Mines' (QDNRM) road data. Missing locations were semantically extracted using Natural Language Processing (NLP) and gazetteer lookup techniques. The Credibility of Ushahidi Crowdmap dataset was assessed using a naive Bayesian Network (BN) model commonly utilised in spam email detection. CSD relevance was assessed by adapting Geographic Information Retrieval (GIR) relevance assessment techniques which are also utilised in the IT sector. Thematic and geographic relevance were assessed using Term Frequency – Inverse Document Frequency Vector Space Model (TF-IDF VSM) and NLP based on semantic gazetteers. Results of the CSD location comparison showed that the combined use of non-authoritative and authoritative data improved location determination. The semantic location analysis results indicated some improvements of the location availability of the tweets and Crowdmap data; however, the quality of new locations was still uncertain. The results of the credibility analysis revealed that the spam email detection approaches are feasible for CSD credibility detection. However, it was critical to train the model in a controlled environment using structured training including modified training samples. The use of GIR techniques for CSD relevance analysis provided promising results. A separate relevance ranked list of the same CSD data was prepared through manual analysis. The results revealed that the two lists generally agreed which indicated the system's potential to analyse relevance in a similar way to humans. This research showed that the CSD fitness analysis can potentially improve the accuracy, reliability and currency of CSD and may be utilised to fill information gaps available in authoritative sources. The integrated and autonomous CSD qualification framework presented provides a guide for flood disaster first responders and could be adapted to support other forms of emergencies

A review of volunteered geographic information for disaster management

The immediacy of locational information requirements and importance of data currency for natural disaster events highlights the value of volunteered geographic information (VGI) in all stages of disaster management, including prevention, preparation, response, and recovery. The practice of private citizens generating online geospatial data presents new opportunities for the creation and dissemination of disaster-related geographic data from a dense network of intelligent observers. VGI technologies enable rapid sharing of diverse geographic information for disaster management at a fraction of the resource costs associated with traditional data collection and dissemination, but they also present new challenges. These include a lack of data quality assurance and issues surrounding data management, liability, security, and the digital divide. There is a growing need for researchers to explore and understand the implications of these data and data practices for disaster management. In this article, we review the current state of knowledge in this emerging field and present recommendations for future research. Significantly, we note further research is warranted in the pre-event phases of disaster management, where VGI may present an opportunity to connect and engage individuals in disaster preparation and strengthen community resilience to potential disaster events. Our investigation of VGI for disaster management provides broader insight into key challenges and impacts of VGI on geospatial data practices and the wider field of geographical science

A Review of Citizen Science and Crowdsourcing in Applications of Pluvial Flooding

Pluvial flooding can have devastating effects, both in terms of loss of life and damage. Predicting pluvial floods is difficult and many cities do not have a hydrodynamic model or an early warning system in place. Citizen science and crowdsourcing have the potential for contributing to early warning systems (EWS) and can also provide data for validating flood forecasting models. Although there are increasing applications of citizen science and crowdsourcing in fluvial hydrology, less is known about activities related to pluvial flooding. Hence the aim of this paper is to review current activities in citizen science and crowdsourcing with respect to applications of pluvial flooding. Based on a search in Scopus, the papers were first filtered for relevant content and then classified into four main themes. The first two themes were divided into (i) applications relevant during a flood event, which includes automated street flooding detection using crowdsourced photographs and sensors, analysis of social media, and online and mobile applications for flood reporting; and (ii) applications related to post-flood events. The use of citizen science and crowdsourcing for model development and validation is the third theme while the development of integrated systems is theme four. All four main areas of research have the potential to contribute to EWS and build community resilience. Moreover, developments in one will benefit others, e.g., further developments in flood reporting applications and automated flood detection systems will yield data useful for model validation

Life and death of volunteered geographic information contributors in a large online community - the case of OpenStreetMap

The advent of the Web 2.0 has democratized both the production and dissemination of knowledge by enabling communities of online contributors to generate content collectively. This thesis focuses on “Volunteered Geographic Information” (VGI), a type of user-generated content (UGC) oriented toward geographic information. The provided content is known to be highly heterogeneous in coverage, nature and quality, reflecting a patchwork of motivations, interests, knowledge and skills of individual contributors. Characterizing VGI data requires understanding contributors’ behaviour. Typologies of contributors are proposed in an attempt to link VGI contributors with the nature of the data they provide. Those typologies are directly or indirectly related to the time spent by the contributors in a project, but they do not use a formal temporal perspective to understand their behaviour. We considered the time spent by contributors in a given VGI project as an essential component for understanding their contribution patterns (e.g. volume, content, quality). In order to fill this knowledge gap regarding how the time in the project may have impacted contributors’ behaviors, I analyzed the behaviour of the OpenStreetMap (OSM) contributors, of a large VGI community. I identified different events that affected enrollments and withdrawals over a project’s history using time series analyses. I established the phases of contributors’ life cycle using survival analyses and linked their contributions to the different phases. Six distinct phases were identified in the life cycle of OSM contributors. Analyses revealed that these phases were grouped into three major stages: An “Assessment” stage that last a few months, followed by an “Engagement” stage that can extend over more than a decade, to eventually move to a “Detachment” stage over which the contributors leave the project. Analysis of contributions at each phase revealed that contributors’ behaviour is dominated by two distinct processes. When contributors enroll in a project, they seem to be driven by a learning-adaptation-dominated process before switching to a cumulative-damage-dominated process followed by a withdrawal from the project. In parallel, I found that the diffusion of innovation theory (DoIT) had an important impact all along the project’s history. This research not only shed light on online contributions but also reveals different aspects of human behaviours

Geoinformatics in Citizen Science

The book features contributions that report original research in the theoretical, technological, and social aspects of geoinformation methods, as applied to supporting citizen science. Specifically, the book focuses on the technological aspects of the field and their application toward the recruitment of volunteers and the collection, management, and analysis of geotagged information to support volunteer involvement in scientific projects. Internationally renowned research groups share research in three areas: First, the key methods of geoinformatics within citizen science initiatives to support scientists in discovering new knowledge in specific application domains or in performing relevant activities, such as reliable geodata filtering, management, analysis, synthesis, sharing, and visualization; second, the critical aspects of citizen science initiatives that call for emerging or novel approaches of geoinformatics to acquire and handle geoinformation; and third, novel geoinformatics research that could serve in support of citizen science

Frostid: Aplikasi Pelaporan Jalan Banjir Berbasis Warga Pada Navigasi Berlalu Lintas

Di Indonesia, banjir merupakan masalah utama yang dialami saat musim penghujan setiap tahunnya. Jalan banjir membawa dampak kerugian kepada pengendara kendaraan bermotor misalnya dapat menyebabkan kerusakan mesin, serta penyebab utama terjadinya karat pada kendaraan bermotor. Oleh karena itu, diperlukan upaya peringatan dini, berupa sistem pelaporan banjir, yang memberikan informasi kepada pengendara sehingga mereka dapat mengantisipasi jalan banjir. Pada penelitian ini diusulkan aplikasi pelaporan jalan banjir secara online yang berfokus pada peta navigasi berlalu-lintas untuk pengguna jalan. Aplikasi ini melibatkan partisipasi warga secara aktif (crowdsourcing) yaitu pengumpulan dan penyebaran informasi banjir dilakukan oleh kerumunan (crowd) warga dan dinamakan dengan Flooded Road Reporting System Indonesia (Frostid). Aplikasi mobile Frostid dikembangkan dalam lingkungan sistem operasi Android. Pendekatan pengembangan agile Mobile-D diterapkan. Penerimaan pengguna terhadap aplikasi dievaluasi menggunakan model TAM (Technology Acceptance Model). Metriks yang dievaluasi meliputi kegunaan yang dirasakan, kemudahan pengunaan yang dirasakan, sikap pengguna terhadap aplikasi, dan niat untuk menggunakan. Berdasarkan hasil analisis statistik deskriptif hasil pengujian penerimaan pengguna, dapat disimpulkan bahwa konsep crowdsourcing dalam aplikasi pelaporan jalan banjir diterima oleh pengguna. Kesediaan pengguna untuk merekomendasikan kepada orang lain, juga selaras dengan konsep crowdsourcing, dimana nilai dari aplikasi akan optimal jika banyak pengguna yang berkontribusi

Mapping and the Citizen Sensor

Maps are a fundamental resource in a diverse array of applications ranging from everyday activities, such as route planning through the legal demarcation of space to scientific studies, such as those seeking to understand biodiversity and inform the design of nature reserves for species conservation. For a map to have value, it should provide an accurate and timely representation of the phenomenon depicted and this can be a challenge in a dynamic world. Fortunately, mapping activities have benefitted greatly from recent advances in geoinformation technologies. Satellite remote sensing, for example, now offers unparalleled data acquisition and authoritative mapping agencies have developed systems for the routine production of maps in accordance with strict standards. Until recently, much mapping activity was in the exclusive realm of authoritative agencies but technological development has also allowed the rise of the amateur mapping community. The proliferation of inexpensive and highly mobile and location aware devices together with Web 2.0 technology have fostered the emergence of the citizen as a source of data. Mapping presently benefits from vast amounts of spatial data as well as people able to provide observations of geographic phenomena, which can inform map production, revision and evaluation. The great potential of these developments is, however, often limited by concerns. The latter span issues from the nature of the citizens through the way data are collected and shared to the quality and trustworthiness of the data. This book reports on some of the key issues connected with the use of citizen sensors in mapping. It arises from a European Co-operation in Science and Technology (COST) Action, which explored issues linked to topics ranging from citizen motivation, data acquisition, data quality and the use of citizen derived data in the production of maps that rival, and sometimes surpass, maps arising from authoritative agencies

Towards defining a CAVE like system performance evaluation

One of the main goals of Virtual Reality is to provide immersive environments that take participants away from the real life into a virtual one, this is how Cave Automated Virtual Environment (CAVE) came about many years ago. Nowadays there are many of this kind of room-sized systems providing a superior Virtual Reality experience and are used for research into a wide range of disciplines including archaeology, architecture, art, biology, engineering, geometry, geology, medicine and healthcare, meteorology and physics. Nevertheless, for a good Virtual Reality user experience, it is necessary to have a processing system optimized for visual computing (based on CAVE-related features, Interaction, Application, etc.). In this work we propose an evaluation methodology for our Cave-like multi-VRmedia System. The proposal is based on three generic criteria: Performance, Usability and Relevance. The strategy tries to prove how assertive a system is when it comes to solving a problem.Workshop: WCGIV – Computación Gráfica, Imágenes y VisualizaciónRed de Universidades con Carreras en Informátic