Crowd-Sourcing and Data Mashups Challenges: A Mini Case Study for Assisting and Solving a Disaster Management Scenario

During the past few years much effort has been put into developing community-based methods to capture and analyse a large amount of data in a systematic manner. The concept of crowd-sourcing (also known as citizen science) becomes quite popular. This is mainly due to its distributed service orientation and its group intelligence problem solving production model. Parallel to this emerging technology, Data Mashups join information from different data related services or applications available on the web for presenting a combination of functionalities among two or more services. The large amount of data generating and gathering from the client applications are hosted online and published in APIs so they facilitate an easy to integrate mechanism for future developers. Therefore, a new vision for scientists is the data information processing of Data Mashups alongside with the crowd-sourcing framework in the direction of how to store, process and benefit from collected data. In this exploratory paper we present a case-based scenario of a disaster management by highlighting how the aforementioned standards may play a significant role for solving such problems. Moreover, we discuss the emergence of paradigms and next generation technologies including Grids, Clouds and Ubiquitous and address issues related to their use in crowd-sourcing problem solver.