Scientific knowledge is typically regarded as "positive"knowledge.  I will address the contrasting concept of negative knowledge, or explicit knowledge of false claims, known artifacts, and clarified errors.  Drawing on the familiar concept of sources of error, I will profile the significance of what Deborah Mayo calls error repertoires in guiding experimental research and publication.  Finally, I will describe the general program of Error Analytics, which aims to articulate the spectrum of error types in science and their role in shaping scientific practice. I will alsobriefly discuss the origin of methodological principles, factors in research design, Kuhn loss, and scientific literacy education.