Requirement analysis and metric development for public participatory GIS

During the last few decades, many rural communities in the developing countries are facing a crisis due to over exploitation of natural resources. Governmental and other agencies are carrying out various intervention programs to remedy the situation. However, the achievements of many of these programs have been sub-optimal due to lack of participation by stakeholders in effective monitoring of their implementation. A majority of the stakeholders do not have formal education and are unable to understand and participate in these programs effectively. Public Participatory GIS (PP-GIS) can help such stakeholders to visualize, understand and participate better. Hence, there is a need for a framework to identify, describe and analyze requirements of rural communities for such a PP-GIS solution. While such frameworks are used extensively when developing commercial software, they are not being widely practiced when developing PP-GIS solutions. In this paper, we propose a 'Quality Function Deployment' based framework for developing a PP-GIS solution. We demonstrate it using case study of a PP-GIS solution developed using 'Free and Open Source Software' modules for participatory monitoring of natural resource management programs. A detailed requirement analysis was carried out with various user groups. The qualitative user requirements gathered during these discussions were translated into quantifiable metrics. These were then assigned weights based on their relative importance using 'Analytic Hierarchy Process' method. A PP-GIS solution with following three components was developed to meet these requirements: 1) an Android mobile application for collecting field data, 2) a cloud based Quantum GIS Python plugin that converts field data into maps and 3) a GeoServer that serves these maps using 'Web Feature Service' to a Quantum GIS desktop client. Usability trials of the PP-GIS solution were carried in an Indian village and it met most of the requirements well.