Continued progress toward systematic generation of large-scale and comprehensive proteomics data in the context of biomedical research will create project-level data sets of unprecedented size and ultimately overwhelm current practices for results validation that are based on distribution of native or surrogate mass spectrometry files. Moreover, the majority of proteomics studies leverage discovery-mode MS/MS analyses, rendering associated data-reduction efforts incomplete at best, and essentially ensuring future demand for re-analysis of data as new biological and technical information become available. Based on these observations, we propose to move beyond the sharing of interpreted spectra, or even the distribution of data at the individual file or project level, to a system much like that used in high-energy physics and astronomy, whereby raw data are made programmatically accessible at the site of acquisition. Toward this end we have developed a web-based server (mzServer), which exposes our common API (mzAPI) through very intuitive (RESTful) uniform resource locators (URL) and provides remote data access and analysis capabilities to the research community. Our prototype mzServer provides a model for lab-based and community-wide data access and analysis.