The objective of the Ciliary proteome database is to assemble all existing ciliary and basal body proteomics data into an open resource for the scientific community with the ultimate aim of exploring further the role of the cilium in disease and the mechanisms underlying ciliary biology. We have integrated the recent results of several unique, yet overlapping proteomics investigations involving mass spectroscopy, comparative genomics, transcriptional profiling and promoter analyses to decipher the repertoire of proteins required for ciliary biogenesis and function in eukaryotes. Cilia and flagella are highly specialized cellular compartments that can be found in a broad range of species. A wealth of evidence has implicated cilia in diverse roles such as cellular motility, displacement of extracellular fluid, chemosensation, mechanosensation, and paracrine signal transduction. Given such important cellular functions, cilia are critical for proper organism development, homeostasis, and reproduction. Although cilia are restricted to specific tissue types in invertebrates, they have been recruited in a nearly ubiquitous fashion in mammals. In humans, defects in the cilium and its cellular anchor, the basal body, have been associated with an accumulating number of pathophysiological phenotypes including Kartagener syndrome (KS) Polycystic Kidney Disease (PKD), Nephronophthisis (NPH), Bardet-Biedl Syndrome (BBS) and Meckel-Gruber Syndrome (MKS) and their elucidation has led to the identification of a constellation of bona fide ciliary proteins. Still, a comprehensive understanding of the protein makeup of the cilium and basal body remains obscure. Dating back to the 1970s, two-dimensional polyacrylamide gel electrophoresis analyses of Chlamydomonas flagella placed initial estimates at some 150 and 250 proteins at the basal body and cilium respectively. Still, the procurement of these estimates was limited by insufficient protein resolution, which was not addressed until the more recent advent of optimized mass spectrometry techniques coupled to whole-genome sequence data.