Ability Discovery and Weak Centralized Based Crowdsourcing Service Release System in Social Network

Crowdsourcing developed rapidly for its inspiring public abilities. But how to effectively find qualified participants and how to find and prevent malicious workers may be the main difficulties to ensure the crowdsourcing quality. In this paper, the related theories of social network were used in crowdsourcing services, the task publisher (Seeker) was regarded as the network center, his Abilities Set (AS) would be quantified and his Friends Abilities Matrix (FAM) would be generated according to the communication between them, thus his social network was re-constructed. Subsequently, some friends that conformed to the ability requirements of the task would be chosen to be the task receivers (Solvers). The natural trust relationship in the social network was fully used to build a crowdsourcing service release system on weak centralization. By using the social network, even the privacy information needn’t to be shared with others, the system could help the seeker find solvers accurately in the seeker’s own social network according to task demands, and then help to reduce fraud and invalid data. The simulation experiments showed that the release system could help the seeker discover his own abilities, construct the FAM, and select the appropriate solvers precisely and automatically

Modeling of citizen science cluster in making decision for readiness towards bogor smart village: An application of fuzzy c-means algorithm

The construction of smart villages has begun in many Indonesian villages, along with the advancement of technology and local economic growth. Villagers must participate in constructing the smart economy-smart village by becoming familiar with the characteristics of the village's inhabitants using the citizen science model. This study intends to categorize villagers so that researchers can assess and decide their level of readiness for a smart economy in an ecosystem based on a smart village. Clustering is required to find communities of residents who are ready based on their traits. Using fuzzy C-Means with a Davied Bouldin Index value of 0.129, the data were divided into 4 clusters. The most important variables were chosen using information from the test's 300 responders, and the Kaiser Mayer Olkin assumption of 0.975 was used to validate the results. Our paper provides new information on how smart village readiness is assessed by the citizen science cluster. It was decided to divide residents into four groups: those who are less prepared (24.33%), those who are somewhat prepared (29.33%), those who are ready ( 25.67%) %), those who are ready (level of participatory knowledge), and those who are very ready for the smart economy (20.67%) based on the cluster model

Citizen Science

Citizen science, the active participation of the public in scientific research projects, is a rapidly expanding field in open science and open innovation. It provides an integrated model of public knowledge production and engagement with science. As a growing worldwide phenomenon, it is invigorated by evolving new technologies that connect people easily and effectively with the scientific community. Catalysed by citizens’ wishes to be actively involved in scientific processes, as a result of recent societal trends, it also offers contributions to the rise in tertiary education. In addition, citizen science provides a valuable tool for citizens to play a more active role in sustainable development. This book identifies and explains the role of citizen science within innovation in science and society, and as a vibrant and productive science-policy interface. The scope of this volume is global, geared towards identifying solutions and lessons to be applied across science, practice and policy. The chapters consider the role of citizen science in the context of the wider agenda of open science and open innovation, and discuss progress towards responsible research and innovation, two of the most critical aspects of science today