Design and analysis of experiments is a systematic strategy to generate and analyze data. It allows for efficient study of input-output relationships or models by deliberately varying the inputs. However, dramatic changes and paradigm shifts in the notion and process of data collection for causal investigation in many scientific fields—including physical, chemical, biological, computer, and engineering sciences—have occurred in recent years. In this seminar, we will identify and synthesize critical research issues in experimental design across fields. The issues, which arise from a changing paradigm, have the potential for making a profound impact on causal investigation in scientific studies.