control experimental conditions. Yet the basic elements of scientific method are identical to those used with other experiments: observations inspire hypotheses, which can be tested only with further observation.
Scientists generally use the term ‘observations’ as a synonym for ‘data’, whether or not the experiment actively manipulates the observed environment. This section, in contrast, focuses on that distinction. Unlike experimental science, much observational science is akin to the Chinese concept of wu-wei, or ‘not doing’. Wu-wei is a balance of active and receptive, an alertness coupled with a willingness to allow nature to unfold and reveal itself.
Throughout scientific history, some scientists have chosen this method of alert receptivity. Greek science was almost entirely observational; it sought order in the universe through observation, interpretation, and classification rather than through experimentation. Charles Darwin, as biological taxonomer on the Beagle, recognized patterns that allowed him to understand both the evolution of coral reefs and the process of biological evolution through natural selection. Within the science of geology, a more observational science than most, there are highly experimental fields such as experimental geochemistry as well as largely observational fields such as paleontology. The lack of experimentation in paleontology has not prevented the field from providing the age-dating foundations for most of the rest of geology, or from revealing a wealth of climatic and evolutionary information.
Observation is the primary method for understanding complex systems. Control of all possibly relevant variables in such systems may be impossible, and the theories may be so simplified that they cannot predict the observations reliably. In studying complex systems, the search for one phenomenon frequently reveals an even more interesting phenomenon.
The approach to observational science often begins qualitatively, as a search for an order that characterizes the system. Usually the researcher observes many variables, hoping to detect any patterns. These patterns or relationships may or may not be causal. If an apparent pattern is found, a suite of later observations can be designed to test its significance.
An observational science can evolve into a more experimental science, particularly when a new paradigm guides observations by imposing order on the complexity and indicating which parameters are important for study. Astronomy is a good example: for thousands of years it was purely observational, then it became capable of quantitative predictions such as the occurrence of seasons and eclipses. Since Newton, work in astronomy has been increasingly quantitative and theoretical. Even without the ability to affect the planets and stars, astronomical experiments can isolate variables and test hypotheses.
Unlike hypothesis-driven experimentation, with its limited choice of expected results, observational science often yields unpredicted results. While this can be advantageous, promoting insight and creativity, there also are drawbacks. Unexpected results often are overlooked or rationalized (see Chapter 6). A particularly challenging aspect of observation is the necessity of noticing absence of a phenomenon; absence can be as significant as presence. For example, consider Sherlock Holmes’s search for the perpetrator of a break-in:
“ ‘Is there any point to which you would wish to draw my attention?’ [asked Inspector Ross].
‘To the curious incident of the [watch]dog in the night-time,’ [answered Sherlock Holmes].
‘The dog did nothing in the night-time.’
‘That was the curious incident,’ remarked Sherlock Holmes.” [Doyle, 1893a]
