This paper equips researchers for addressing a wide range of data collection challenges experienced when interacting with marginalized communities as part of ICT4D projects in developing countries. This secondary research categorizes data collection challenges reported in multiple disciplines, and summarizes the guidance from the past literature to deal with the challenges. The open, axial, and selective coding of data collection challenges reported by the past literature suggests that it is necessary to manage scope, time, cost, quality, human resources, communication, and risks for addressing the data collection challenges. This paper illustrates the ways to manage these seven dimensions using (a) the success stories of data collection in the past, (b) the lessons learned by researchers during data collection as documented by the past literature, and (c) the advice they offer for collection data from marginalized communities in developing countries
