In tackling my research dissertation on structural inequalities in Kibera, specifically focusing on water and sanitation governance, the recent lecture on Finding and Using Data proved invaluable. It shed light on both the theoretical and practical aspects of incorporating reliable data to map marginalization and advocate for equitable governance.
Key Insights on Data for Research
One of the most impactful takeaways was the emphasis on data as “the basis of reasoning or calculation”. Reliable data forms the backbone of any rigorous research, helping to build on existing work, provide evidence, and ensure reproducibility. For my study, this principle underscores the importance of using credible datasets to highlight the disparities in access to clean water and sanitation facilities in Kibera.
The lecture introduced practical approaches to finding data. It stressed that using datasets created by others is not only acceptable but encouraged. This aligns with the necessity of leveraging existing reports and surveys from government bodies, NGOs, and research institutions operating in informal settlements. For example, publicly available data repositories such as data.gov.uk and platforms like Google Dataset Search can provide critical insights.
Relevance to Water and Sanitation in Kibera
The data issues identified in the lecture—content biases, permissions, and messy data—are particularly relevant to my study. In Kibera, marginalized communities often face data exclusion, either due to incomplete documentation or lack of access to reliable surveys. Understanding these challenges will allow me to critically evaluate any secondary datasets I use. It also strengthens my approach to data collection, ensuring I address gaps, especially in representing the lived realities of those experiencing marginalization.
Moreover, the lecture’s guidance on evaluating a dataset—who produced it, the time period, variables, and units of assessment—resonates with my research objectives. For instance, when using water access surveys, I need to ensure the dataset accounts for gender, household size, and socioeconomic factors, which are critical variables for analyzing intersectional marginalization in sanitation governance.
Methodological Alignment
The focus on defining a clear research question and identifying dependent/independent variables helped refine my methodology. My dissertation aims to assess how exclusionary urban policies and infrastructure gaps perpetuate inequities in water and sanitation access. Here, water access serves as a dependent variable, while factors like governance frameworks, economic status, and spatial segregation act as independent variables.
Bridging Data and Policy Solutions
Finally, the lecture underscored the ethical and impactful use of data to influence future research and policy. Mapping marginalization in Kibera using reliable datasets will not only uncover systemic exclusions but also provide strong evidence to advocate for community-led, equitable governance solutions.
Conclusion
The tools and principles from this lecture have equipped me to approach my research systematically identifying, evaluating, and utilizing data to map inequalities in Kibera’s water and sanitation systems. This foundation strengthens my ability to contribute to both academic discourse and actionable policy reforms for equitable urban development.
