THE DEVELOPMENT EFFECTIVENESS OF INTERNATIONAL WATER AND SANITATION INFRASTRUCTURE PROJECTS: DEFINING “QUALITY AT ENTRY” OF WORLD BANK PROJECTS.

Over the past 15 years, the number of international development projects aimed at combating global poverty has increased significantly. Within the water and sanitation sector however, and despite heightened global attention and an increase in the number of infrastructure projects, over 800 million people remain without access to appropriate water and sanitation facilities. The majority of donor aid in the water supply and sanitation sector of developing countries is delivered through standalone projects. The quality of projects at the design and preparation stage is a critical determinant in meeting project objectives. The quality of projects at early stage of design, widely referred to as quality at entry (QAE), however remains unquantified and largely subjective. This research argues that water and sanitation infrastructure projects in the developing world tend to be designed in the absence of a specific set of actions that ensure high QAE, and consequently have relatively high rates of failure. This research analyzes 32 cases of water and sanitation infrastructure projects implemented with partial or full World Bank financing globally from 2000 – 2010. The research uses categorical data analysis, regression analysis and descriptive analysis to examine perceived linkages between project QAE and project development outcomes and determines which upstream project design factors are likely to impact the QAE of international development projects in water supply and sanitation. The research proposes a number of specific design stage actions that can be incorporated into the formal review process of water and sanitation projects financed by the World Bank or other international development partners.

Community-based Data Validation Practices in Citizen Science

Technology-supported citizen science has created huge volumes of data with increasing potential to facilitate scientific progress, however, verifying data quality is still a substantial hurdle due to the limitations of existing data quality mechanisms. In this study, we adopted a mixed methods approach to investigate community-based data validation practices and the characteristics of records of wildlife species observations that affected the outcomes of collaborative data quality management in an online community where people record what they see in the nature. The findings describe the processes that both relied upon and added to information provenance through information stewardship behaviors, which led to improved reliability and informativity. The likelihood of community-based validation interactions were predicted by several factors, including the types of organisms observed and whether the data were submitted from a mobile device. We conclude with implications for technology design, citizen science practices, and research.