This paper explores the nexus of data science and evaluation, probing the issues and challenges of incorporating big data into evaluation practice.
This paper provides detailed guidance on using big data to fill data gaps in impact evaluations. Data gaps can arise due to the inaccessibility of target populations, inadequate aggregation of data, data collection lag times, and data being missing in some contexts, like pandemics, conflicts, and humanitarian emergency situations. The paper includes a number of specific examples and additional references.
One issue to note when using the paper is that it uses the terms 'control group' and 'comparison group' inconsistently. The examples provided mostly refer to the use of comparison groups and quasi-experimental designs, not to randomly assigned control groups
The report from UN Women, with support from UN Global Pulse, outlines the value of big data for monitoring the Sustainable Development Goals (SDGs) in relation to women. It presents the benefits of big data (for example, real time data), risks (for example, elite capture and privacy), and policy implications (for example, how it can be incorporated in project cycles from planning to evaluation). It ends with a compendium of gender-related big data projects and their relevance to the SDGs.
This report by NPC highlights their research into the latest developments in theory and practice in measurement and evaluation. The authors found that new thinking, techniques, and technology are influencing and improving practice. This report highlights eight developments that the authors think have the greatest potential to improve evaluation and programme design, and the careful collection and use of data.