What this illustrates is that how you see the change in millennia depends on how dates are counted and where the breaks are placed. That is, what tools are used to interpret the data. A lot of data either are, or can be made, readily available for all interested parties. But how an individual interprets a data set, and more importantly, what an individual does with the data, often depends on a personal view. The recent U.S. presidential election was a textbook example of individualized data interpretation.
Science is predicated on unique interpretations of data whose explanation has become generalized.
From apples falling in the 1670s to crystallographic spots on photographic film in the 1940s, scientific phenomena have generally been available to many more people than those who finally and correctly explained it, whether that explanation was of gravity or DNA's double helix. But in all these cases, the correct interpretation depended on the tools used to evaluate the data. One of the great tools of data interpretation in today's genomic world is bioinformatics, the theme of this month's issue. Both pharmaceutical companies and consumers are in a real bind these days. For the companies, many of the blockbuster drugs are coming off patent, and replacements are getting harder to develop.