Newton did not discover that apples fall: the information was available prior to his gravitational hypothesis. Hypotheses can be tested not only by performing experiments but also by retrieving experiments from the literature (via PubMed, for example). Here I show how disconnected facts from known data, if properly connected, can generate novel predictions testable in turn by other published data. With examples from cell cycle, aging, cancer and other fields of biology and medicine, I discuss how new knowledge was and will be derived from old information. Millions of experiments have been already performed to test unrelated hypotheses and the results of those experiments are available to' test' your hypotheses too. But most data (99% by some estimates) remain unpublished, because they were negative, seemed of low priority, or did not fit the story. Yet for other investigators those data may be valuable. The well-known story of Franklin and Watson is a case in point. By making preliminary data widely available, ' data-owners' will benefit most, receiving the credit for otherwise unused results. If posted (pre-published) on searchable databases, these data may fuel thousands of projects without the need for repetitive experiments. Enormous ' pre-published' databases coupled with Google-like search engines can change the structure of scientific research, and shrinking funding will make this inevitable.