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The participation of non-professionally trained people in so-called citizen science (CS) projects is a much discussed topic at the moment. Frequently, however, the contribution of citizens is limited to only a few narrow tasks. Focusing on an initiative dedicated to the study of the human microbiome, this paper describes such a case where citizen participation is limited to the provision of funding, samples, and personal data. Researchers opted for a crowdsourced approaches because other forms of funding and recruitment did not seem feasible. We argue that despite the narrow understanding of participation in the context of some CS projects, they can address some of the democratic concerns related to scientific knowledge creation. For example, CS and crowdsourcing can help to foster dialogue between researchers and publics, and increase the influence of citizens on research agenda setting.

Crowdsourcing has been proven to be an effective and efficient tool to annotate large data-sets. User annotations are often noisy, so methods to combine the annotations to produce reliable estimates of the ground truth are necessary. We claim that considering the existence of clusters of users in this combination step can improve the performance. This is especially important in early stages of crowdsourcing implementations, where the number of annotations is low. At this stage there is not enough information to accurately estimate the bias introduced by each annotator separately, so we have to resort to models that consider the statistical links among them. In addition, finding these clusters is interesting in itself as knowing the behavior of the pool of annotators allows implementing efficient active learning strategies. Based on this, we propose in this paper two new fully unsupervised models based on a Chinese restaurant process (CRP) prior and a hierarchical structure that allows inferring these groups jointly with the ground truth and the properties of the users. Efficient inference algorithms based on Gibbs sampling with auxiliary variables are proposed. Finally, we perform experiments, both on synthetic and real databases, to show the advantages of our models over state-of-the-art algorithms. ; Pablo G. Moreno is supported by an FPU fellowship from the Spanish Ministry of Education (AP2009-1513). This work has been partly supported by Ministerio de Economía of Spain ('COMONSENS', id. CSD2008-00010, 'ALCIT', id. TEC2012-38800-C03-01, 'COMPREHENSION', id. TEC2012-38883-C02-01) and Comunidad de Madrid (project 'CASI-CAM-CM', id. S2013/ICE-2845). This work was also supported by the European Union 7th Framework Programme through the Marie Curie Initial Training Network "Machine Learning for Personalized Medicine" MLPM2012, Grant No. 316861. Yee Why Teh's research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) ERC grant agreement no. 617411.

Local administrations and governments aim at leveraging wireless communications and Internet of Things (IoT) technologies to manage the city infrastructures and enhance the public services in an efficient and sustainable manner. Furthermore, they strive to adopt smart and cost-effective mobile applications to deal with major urbanization problems, such as natural disasters, pollution, and traffic congestion. Mobile crowdsourcing (MCS) is known as a key emerging paradigm for enabling smart cities, which integrates the wisdom of dynamic crowds with mobile devices to provide decentralized ubiquitous services and applications. Using MCS solutions, residents (i.e., mobile carriers) play the role of active workers who generate a wealth of crowdsourced data to significantly promote the development of smart cities. In this paper, we present an overview of state-of-the-art technologies and applications of MCS in smart cities. First, we provide an overview of MCS in smart cities and highlight its major characteristics.Second, we introduce the general architecture of MCS and its enabling technologies. Third, we study novel applications of MCS in smart cities. Finally, we discuss several open problems and future research challenges in the context of MCS in smart cities. ; Peer reviewed

Crowdsourcing has taken root in the business world, but applications in the fields of science and pop culture pre-date this boom. By now it's clear that the catalyst for this Cambrian explosion of collaborative projects has been the Internet. Crowdsourcing efforts come in many different forms, but the same characteristics appear over and over in the most successful examples. Crowdsourcing has had a profound impact wherever an organization's needs intersect the crowd's desires to accomplish something. Entire sections of industries have been decimated by crowdsourcing. Government organizations are not completely immune to the effect. A public good such as defense is safe from obsolescence, but there is strong evidence to indicate that there's nothing preventing defense from reaping rewards from crowdsourcing. Cost savings, innovation, manning issues, and even success on the battlefield might all benefit from applying the lessons learned from crowdsourcing. Other industries have carved a roadmap for defense to follow. It needs to start experimenting with these methods now before rivals learn to perfect crowdsourcing's varied and proven techniques.

International audience ; Digital technology is undoubtedly the main lever for outsourcing administrative activities to the crowd. It invites a profound redefinition of the participatory logic. The "capture of the multitude" by public authorities is illustrated by two phenomena, both of which rely on digital tool: on the one hand, they are seeking to exploit Big data - i.e. the data produced by the crowd - to improve public decision-making and, on the other hand, they intend, with Open data, to free up their data in order to encourage the emergence of innovative services and regenerate existing public services in a logic of coproduction. The combination of these two phenomena - Big data to redefine the general interest and Open data for the co-production of the general interest - is leading to a profound reconfiguration of the relationship between administrations and citizens and a renewal of the democratic process, which is blurring the boundaries between the public and private sectors even more than in the past. ; Le numérique est sans nul doute le levier privilégié de l'externalisation vers la foule des activités administratives. Il invite à une profonde redéfinition de la logique participative. La « captation de la multitude » par les autorités publiques s'illustre par deux phénomènes, qui tous deux reposent sur le levier numérique : elles cherchent, d'une part, à exploiter le Big data - c'est-à-dire les données produites par la foule - pour améliorer la décision publique et entendent, d'autre part, avec l'Open data, libérer leurs données, afin de favoriser l'émergence de services innovants et de régénérer les services publics existants dans une logique de coproduction. A travers la conjugaison de ces deux phénomènes - Big data au service d'une redéfinition de l'intérêt général et Open data pour une coproduction de l'intérêt général, se dessinent une profonde reconfiguration de la relation administrations-administrés et un renouvellement du processus démocratique, non sans brouiller, plus encore que par le passé, les frontières entre public et privé.

International audience ; Digital technology is undoubtedly the main lever for outsourcing administrative activities to the crowd. It invites a profound redefinition of the participatory logic. The "capture of the multitude" by public authorities is illustrated by two phenomena, both of which rely on digital tool: on the one hand, they are seeking to exploit Big data - i.e. the data produced by the crowd - to improve public decision-making and, on the other hand, they intend, with Open data, to free up their data in order to encourage the emergence of innovative services and regenerate existing public services in a logic of coproduction. The combination of these two phenomena - Big data to redefine the general interest and Open data for the co-production of the general interest - is leading to a profound reconfiguration of the relationship between administrations and citizens and a renewal of the democratic process, which is blurring the boundaries between the public and private sectors even more than in the past. ; Le numérique est sans nul doute le levier privilégié de l'externalisation vers la foule des activités administratives. Il invite à une profonde redéfinition de la logique participative. La « captation de la multitude » par les autorités publiques s'illustre par deux phénomènes, qui tous deux reposent sur le levier numérique : elles cherchent, d'une part, à exploiter le Big data - c'est-à-dire les données produites par la foule - pour améliorer la décision publique et entendent, d'autre part, avec l'Open data, libérer leurs données, afin de favoriser l'émergence de services innovants et de régénérer les services publics existants dans une logique de coproduction. A travers la conjugaison de ces deux phénomènes - Big data au service d'une redéfinition de l'intérêt général et Open data pour une coproduction de l'intérêt général, se dessinent une profonde reconfiguration de la relation administrations-administrés et un renouvellement du processus démocratique, non sans brouiller, plus encore que par le ...

International audience ; Digital technology is undoubtedly the main lever for outsourcing administrative activities to the crowd. It invites a profound redefinition of the participatory logic. The "capture of the multitude" by public authorities is illustrated by two phenomena, both of which rely on digital tool: on the one hand, they are seeking to exploit Big data - i.e. the data produced by the crowd - to improve public decision-making and, on the other hand, they intend, with Open data, to free up their data in order to encourage the emergence of innovative services and regenerate existing public services in a logic of coproduction. The combination of these two phenomena - Big data to redefine the general interest and Open data for the co-production of the general interest - is leading to a profound reconfiguration of the relationship between administrations and citizens and a renewal of the democratic process, which is blurring the boundaries between the public and private sectors even more than in the past. ; Le numérique est sans nul doute le levier privilégié de l'externalisation vers la foule des activités administratives. Il invite à une profonde redéfinition de la logique participative. La « captation de la multitude » par les autorités publiques s'illustre par deux phénomènes, qui tous deux reposent sur le levier numérique : elles cherchent, d'une part, à exploiter le Big data - c'est-à-dire les données produites par la foule - pour améliorer la décision publique et entendent, d'autre part, avec l'Open data, libérer leurs données, afin de favoriser l'émergence de services innovants et de régénérer les services publics existants dans une logique de coproduction. A travers la conjugaison de ces deux phénomènes - Big data au service d'une redéfinition de l'intérêt général et Open data pour une coproduction de l'intérêt général, se dessinent une profonde reconfiguration de la relation administrations-administrés et un renouvellement du processus démocratique, non sans brouiller, plus encore que par le ...

The increased interdependence and complexity of modern societies have increased the need to involve all members of a community into solving problems. In times of great uncertainty, when communities face threats of different kinds and magnitudes, the traditional top-down approach where government provides solely for community wellbeing is no longer plausible. Crowdsourcing has emerged as an effective means of empowering communities with the potential to engage individuals in innovation, self-organization activities, informal learning, mutual support, and political action that can all lead to resilience. However, there remains limited resource on the topic. In this paper, we outline the various forms of crowdsourcing, economic and community resilience, crowdsourcing and economic resilience, and a case study of the Nepal earthquake. his article presents an exploratory perspective on the link can be found between crowdsourcing and economic resilience. It introduces and describes a framework that can be used to study the impact of crowdsourcing initiatives for economic resilience by future research. An initial a set of indicators to be used to measure the change in the level of resilience is presented.

The increased interdependence and complexity of modern societies have increased the need to involve all members of a community into solving problems. In times of great uncertainty, when communities face threats of different kinds and magnitudes, the traditional top-down approach where government provides solely for community wellbeing is no longer plausible. Crowdsourcing has emerged as an effective means of empowering communities with the potential to engage individuals in innovation, self-organization activities, informal learning, mutual support, and political action that can all lead to resilience. However, there remains limited resource on the topic. In this paper, we outline the various forms of crowdsourcing, economic and community resilience, crowdsourcing and economic resilience, and a case study of the Nepal earthquake. his article presents an exploratory perspective on the link can be found between crowdsourcing and economic resilience. It introduces and describes a framework that can be used to study the impact of crowdsourcing initiatives for economic resilience by future research. An initial a set of indicators to be used to measure the change in the level of resilience is presented. ...

Crowdsourcing has been known as developing industry that able to be used as a platform to get more income and provide opportunity for busineses to conduct their operation in more innovative ways. Crowdsourcing has become an effective way for the companies to offer work opportunity for crowd outside organization to apply their abilities and skills, and receive more money. Under the Malaysian government initiatives called Digital economy, various crowdsourcing efforts and programs have been introduced to catch up with the global development. The ecosystem of crowdsourcing which consists of job provider, platform, micro worker and industry is considered still in a formative stage. Thus, the integration of all these components is not fully discovered and understood yet which, can cause confusion among the crowdsourcing industry players. In order to understand the complex integration of multi perspective micro sourcing ecosystem, the components and its significance priority level need to be identified. In this study, the components that involved in crowdsourcing ecosystem were identified and ranked using analytical hierarchy process (AHP) method. The results can be later used by crowdsourcing industry players to plan more proper crowd sourcing strategic development in Malaysia

abstract: The increased interdependence and complexity of modern societies have increased the need to involve all members of a community into solving problems. In times of great uncertainty, when communities face threats of different kinds and magnitudes, the traditional top-down approach where government provides solely for community wellbeing is no longer plausible. Crowdsourcing has emerged as an effective means of empowering communities with the potential to engage individuals in innovation, self-organization activities, informal learning, mutual support, and political action that can all lead to resilience. However, there remains limited resource on the topic. In this paper, we outline the various forms of crowdsourcing, economic and community resilience, crowdsourcing and economic resilience, and a case study of the Nepal earthquake. his article presents an exploratory perspective on the link can be found between crowdsourcing and economic resilience. It introduces and describes a framework that can be used to study the impact of crowdsourcing initiatives for economic resilience by future research. An initial a set of indicators to be used to measure the change in the level of resilience is presented. ; The final version of this article, as published in Journal of Information Systems and Technology Management, can be viewed online at: http://www.jistem.fea.usp.br/index.php/jistem/article/view/10.4301%252FS1807-17752015000300006

Crowdsourcing is a phenomenon emerging in various sectors and industries that provides an opportunity for governments to collaborate with the public to generate information, deliver public services, or facilitate policy innovation. This review paper synthesizes prior research and practices on crowdsourcing from a variety of disciplines and focuses on the purpose, crowd, motivation, process design and outcomes. A process map for governments to design crowdsourcing is generated and three key actions are highlighted, namely incentive design, communication, and information aggregation.

El presente artículo analiza cómo el crowdsourcing puede contribuir al desarrollo de acciones de participación y colaboración ciudadana y por tanto al desarrollo del Gobierno Abierto en instituciones y administraciones públicas. Para este fin, se exponen algunas iniciativas significativas realizadas tanto por instituciones como por ciudadanos u organizaciones civiles. ; Cada vez son más países los que se unen a la Alianza por el Gobierno Abierto, Open Government Partnership. Existe pues un interés mayor por la regeneración democrática a través de este paradigma. Las instituciones públicas tienen la obligación de crear espacios de diálogo con los ciudadanos y empresas. En el presente artículo se muestran distintas iniciativas de crowdsourcing relacionados con la de apertura de procesos de participación y colaboración ciudadana iniciadas por instituciones y administraciones públicas e incluso por organizaciones no gubernamentales y los propios ciudadanos. ; Pardo Gimilio, D. (2014). Crowdsourcing en procesos de Gobierno Abierto. http://hdl.handle.net/10251/38624

Crowdsourcing solutions are receiving more and more attention in the recent literature about social computing and distributed problem solving. In general terms, crowdsourcing can be considered as a social-computing model aimed at fostering the autonomous formation and emergence of the so-called wisdom of the crowd. Quality assessment is a crucial issue for the effectiveness of crowdsourcing systems, both for what concerns task and worker management. Another aspect to be considered in crowdsourcing systems is about the kind of contributions workers can make. Usually, crowdsourcing approaches rely only on tasks where workers have to decide among a predefined set of possible solutions. On the other hand, tasks leaving the workers a higher level of freedom in producing their answer (e.g., free-hand drawing) are more difficult to be managed and verified. In the Thesis, we present the LiquidCrowd approach based on consensus and trustworthiness techniques for managing the xecution of collaborative tasks. By collaborative task, we refer to a task for which a factual answer is not possible/appropriate, or a task whose result depends on the personal perception/point-of-view of the worker. We introduce the notion of worker trustworthiness to denote the worker "reliability", namely her/his capability to foster the successful completion of tasks. Furthermore, we improve the conventional score-based mechanism by introducing the notion of award that is a bonus provided to those workers that contribute to reach the consensus within groups. This way, groups with certain trustworthiness requirements can be composed on-demand, to deal with complex tasks, like for example tasks where consensus has not been reached during the first execution. In LiquidCrowd , we define a democratic mechanism based on the notion of supermajority to enable the flexible specification of the expected degree of agreement required for obtaining the consensus within a worker group. In LiquidCrowd , three task typologies are provided: choice, where the worker is asked to choose the answer among a list of predefined options; range, where the worker is asked to provide a free-numeric answer; proposition, where the worker is asked to provide a free text answer. To evaluate the quality of the produced results obtained through LiquidCrowd consensus techniques, we perform a testing against the SQUARE crowdsourcing benchmark. Furthermore, to evaluate the capability of LiquidCrowd to effectively support a real problem, real case studies about web data classification have been selected.

Abstract In many resource-rich developing countries, policymakers, academics, and practitioners alike seek to promote citizen engagement and monitoring in the management of natural resource revenues. However, many of the approaches to improve citizen engagement have not been effective as citizens often lack access to relevant information and opportunities to voice their concerns, and governments have faced financial challenges in engaging citizens. In this article, the authors propose spatial crowdsourcing as an alternative to the traditional ways of encouraging citizen engagement. The proposed approach is illustrated using a simple, intuitive multimedia-based spatial crowdsourcing platform that was tested among farmers who were benefiting from a petroleum-funded project in Ghana. The farmers accessed the platform via their mobile phones and completed a survey relating to the project and petroleum revenue management in Ghana. The findings suggest that spatial crowdsourcing is a promising approach to promote informed citizen engagement in the context of natural resource revenue management. In particular, the farmers indicated that an opportunity to give feedback on the project through a user-friendly platform was very important for them. Furthermore, the representatives of both the government and an oversight body for petroleum revenue management regarded spatial crowdsourcing as a useful tool for collecting feedback on petroleum-funded projects and to increase citizen engagement in natural resource management in general. The authors conclude that although spatial crowdsourcing can help in citizen engagement, its effectiveness in the management of natural resource revenues depends on behavioural changes in governments and citizens.