The Millennium Development Goals (MDG) provide clear targets by 2015 and it turns out that sanitation is by far the largest of all the MDG targets affecting about 40% of the global population. The objective of the Sustainable Sanitation Alliance (SuSanA) is to show how Sustainable Sanitation projects should be planned with participation of stakeholders through capacity development activities. Developing the capacity of societies to collaboratively learn through change and uncertainty is fundamental for sustainability science. The aim of this contribution it is to analyze the role of graph database management (GDM) for improve capacity development and knowledge building in the Sustainable Sanitation framework. We provide a theoretical model with four features of network research: link analysis, social network, pattern recognition and keyword search that we illustrate with some examples. Network research allows us to observe how the information in Sustainable Sanitation is scattered properly through the structure and also to detect the emergencies, objections and other characteristics of the network

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