Choosing the right data collection solution is critical to the success of policy research and program evaluation. Sometimes, researchers or clients accustomed to a particular approach or familiar with a certain tool might want to re-use that tool, even if it is not necessarily right for the current project. While it’s often possible to tailor a tool to meet needs even when it is a sub-optimal choice, it’s better to be familiar with the range of solutions and their core uses and choose the tool that best fits the need.

Some tools are fully research driven, used to collect data generated only for the specific purposes of a research study; others are best for obtaining activity-based, secondary data not generated with research in mind. Another key distinction is whether we are collecting data based on what research subjects self-report or tracking subjects’ interactions, experiences, or conditions.  

Using these two concepts we can organize data collection methods and tools into four categories, wherein a taxonomy emerges. The choice of approaches affects data content, reliability, and the level and types of research effort. In this paper, we explore exemplars of each quadrant—then expand the taxonomy to discuss approaches that fall in between these lines.