In this paper, we begin to address the question of which scientists are online. Prior studies have shown that Web users are only a segmented reflection of the actual offline population, and thus when studying online behaviors we need to be explicit about the representativeness of the sample under study to accurately relate trends to populations. When studying social phenomena on the Web, the identification of individuals is essential to be able to generalize about specific segments of a population offline. Specifically, we present a method for assessing the online activity of a known set of actors. The method is tailored to the domain of science. We apply the method to a population of Dutch computer scientists and their co-authors. The results when combined with metadata of the set provide insights into the representativeness of the sample of interest. The study results show that scientists of above average tenure and performance are overrepresented online; suggesting that when studying online behaviors of scientists we are commenting specifically on behaviors of above average per-forming scientists. Given this finding, metrics of Web behaviors of science may provide a key tool for measuring knowledge production and innovation at a faster rate than traditional delayed bibliometric studies.