The Stanford Fiber Seismic Observatory (SFSO) has been recording data using a distributed acoustic sensing (DAS) laser interrogator attached to a fiber-optic cable that was deployed in telecommunication conduits buried under the Stanford University campus. Analysis of a sequence of local earthquakes demonstrates that using SFSO data, we could detect a weak event that was not previously cataloged. The comparison of signal amplitudes of data recorded by the SFSO array with data recorded by two nearby broadband seismometers demonstrates that DAS arrays could be useful in determining event magnitudes. Time-lapse seismic noise interferometry results show that repeatable virtual source gathers and frequency-velocity spectra can be computed from SFSO data. Time-lapse interferometry using arrivals from quarry blasts shows changes in time delays that can be related to changes in ground conditions caused by excavation of a building foundation. Comparing data recorded by two laser interrogators of different sensitivity, we show that data quality improves with the sensitivity of the interrogator. This result demonstrates that data quality could improve in the future as interrogator technology advances. We also show that new machine-learning algorithms could tackle the challenges of processing, analyzing, and interpreting huge data streams that would be recorded if we scaled up the SFSO experiment. [link to publication]