Within the last decade, advances in the acquisition, processing and transmission of data from real-time seismic monitoring systems has contributed to the growth in the number structures instrumented with such systems. An equally important factor for such growth can be attributed to the demands by stakeholders to find rapid answers to important questions related to the functionality (or “state of health”) of structures during and immediately following a seismic event. Hence, rapid and accurate assessment of the damage condition or performance of a building or a lifeline structure is of paramount importance to stakeholders, including owners, leasers, permanent and/or temporary occupants, users of infrastructures, city officials and rescue teams that are concerned with safety of those in the building, and those that may be affected in nearby buildings and infrastructures. In earlier papers, we described how observed data from sensors deployed in structures can be configured to establish seismic health monitoring of structures. In these configurations, drift ratios are the main parametric indicator of damage condition of a building. The process described for buildings can be applied directly for bridges as well. For bridges, the term, “drift ratio” is not generally used; however, relative displacements of critical elements of a bridge can be construed as such. While real-time data from structural arrays indicate that these methods are reliable and provide requisite information for owners and other parties to make informed decisions and to choose among pre-defined actions following significant events, there are several issues related to data ownership, transmission and archiving. This paper examines the real-time seismic monitoring systems deployed mainly in the United States, with particular attention to data issues – handling, dissemination, storage, and archiving. In most cases, due to the numerous channels involved, the deployments in each one of the real-time structures can be considered to be an individual array. Two detailed cases are described that demonstrate the variability in data ownership and dissemination.