Big Data research (i.e. genomics, proteomics and metabolomics) has one big advantage and one big disadvantage. The major advantage is that the data is the DATA and not influenced by preconceived notions. It is analogous to looking at every tree in the forest but the truth is still buried in the forest. The central question is to interpret this collection of trees to determine the forest which can be tricky without large clinical experience and the integration of other data (i.e. oxygen toxicity in 100% of cases by IVRT response criteria) and especially epidemiologic data which all give important clues to the meaning of the forest. The analogy is to look at AIDS in the early 1980’s which emphasized large amounts of immunologic data which were like the trees. The key to the forest, however, was the epidemiological data suggesting an epidemic and transmission of a novel infectious agent later to be known as HIV which was the forest. The Big Data of immunology could not help to determine this key findings. Armed with keys to the forest, the treatment turned to treating HIV and not supporting the abnormal immune system or the trees. Some Big Data researchers make the same mistake and so I am not optimistic about such research except perhaps at determining biomarkers for CFS. I have a little more hope for those Big Data researchers who at least listen to me and others with 30 years of experience with CFS though I am not always sure what they think about what I am telling them. I think the key to successful use of Big Data is to integrate other biomarkers such as oxygen toxicity and especially the epidemiology of CFS which is an area that has not seen much attention. For example, why has CFS risen to an incidence of 1-2% of the population which is more people than those with Type I diabetes and MS combined. This impressive rise of seriously disabled people with CFS began around the time of the emergence of HIV in both time and place. Prior to 1980, CFS did not effectively exist, at least in any numbers, in the minds of rank and file physicians who had no knowledge that such a disorder existed. This is a very important epidemiological clue to the cause of CFS and the meaning of the forest.