WASET
	%0 Journal Article
	%A Mikel Niño and  Roberto V. Zicari and  Todor Ivanov and  Kim Hee and  Naveed Mushtaq and  Marten Rosselli and  Concha Sánchez-Ocaña and  Karsten Tolle and  José Miguel Blanco and  Arantza Illarramendi and  Jörg Besier and  Harry Underwood
	%D 2017
	%J International Journal of Humanities and Social Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 125, 2017
	%T Data Projects for “Social Good”: Challenges and Opportunities
	%U https://publications.waset.org/pdf/10006923
	%V 125
	%X One of the application fields for data analysis techniques and technologies gaining momentum is the area of social good or “common good”, covering cases related to humanitarian crises, global health care, or ecology and environmental issues, among others. The promotion of data-driven projects in this field aims at increasing the efficacy and efficiency of social initiatives, improving the way these actions help humanity in general and people in need in particular. This application field, however, poses its own barriers and challenges when developing data-driven projects, lagging behind in comparison with other scenarios. These challenges derive from aspects such as the scope and scale of the social issue to solve, cultural and political barriers, the skills of main stakeholders and the technological resources available, the motivation to be engaged in such projects, or the ethical and legal issues related to sensitive data. This paper analyzes the application of data projects in the field of social good, reviewing its current state and noteworthy initiatives, and presenting a framework covering the key aspects to analyze in such projects. The goal is to provide guidelines to understand the main challenges and opportunities for this type of data project, as well as identifying the main differential issues compared to “classical” data projects in general. A case study is presented on the initial steps and stakeholder analysis of a data project for the inclusion of refugees in the city of Frankfurt, Germany, in order to empirically confront the framework with a real example.
	%P 1094 - 1104