Explanation of notes in table:

* = Confirmed leader of investigation task
S = Special conditions may be required at times during data run, perhaps dedicated shift
P = Special preparation may be needed before start of E2 run
C = Participation by a detector commissioner may be needed

• Investigate source(s) of lock losses.

Title speaks for itself.
• Quantify fraction of noise in 5-50 Hz band due to seismic motion.

Seismic noise is expected to be the dominant contributor to the interferometer noise below about 50 Hz.  There are seismometers  in the vertex and mid stations, and differential motion between pairs on the two arms *should* correlate with the differential arm length as measured by the interferometer.
• Quantify correlations between GW channel and other channels.

Such as laser frequency or intensity.  Investigate use of cross-correlations to reduce noise in GW channel. Adrian Ottewill has written a DMT tool that may prove useful for this investigation.
• Quantify stationarity of interferometer noise level.

There are are a number of contributors to the interferometer noise, and many of these can vary with environmental excitations, with the operating point of the interferometer, etc. Check dependence on temperature, lock-point of MC, etc).
• Quantify stability of calibration with injected signal.

(requires some pre-run preparation) The calibration of the GW signal may vary in time, with laser power, with gain in the servos, and from other factors. Characterizing how stable the calibration is will help determine how frequently different calibrations will need to be performed.
• Quantify deviations from Gaussianity (band-limited).

One of the biggest unknowns in the LIGO noise is the question of how gaussian it will be in the time domain.  Ultimately, this will need to be determined using the filters that will be aplied to search for burst events, but for this engineering run it might be easier (and more useful from a detector characterization point of view) to look at the statistics in medium bandwidth (30-100 Hz) slices of frequency. Different frequency bands are likely to behave rather differently, and the behavior may be correlated with other data channels as well.
• Investigate angular fluctuations.

Quantify relative angular fluctuations between the local frames of different buildings. Look into the consequences of large angular deviations on stability of servo systems and sensitivity levels.
• Look for impulses and transient in interferometer/mode cleaner error signals.

Make a catalogue of impulses introduced by the environment and understand their propagation into the detector signals. Quantify their probability in size and test if their occurrence is correlated with itself and operation state conditions.
• Look for bursts (long and short) and chirp type events.

Make a catalogue of bursts and chirps introduced by the environment and servo instabilities. Quantify their probability in size and test if their occurrence is correlated with itself and operation state conditions. Test and verify the airplane hypothesis.
• Check data against detailed tidal prediction.

(Including effects of ocean loading) The earlier engineering run showed clear evidence of earthtides in the control signal for the arm length.  There are two components to the earthtides--a part that is common to the two arms and a differential component.  this run would be our first opportunity to investigate the magnitude of the two components and to compare with models.
• End-to-end timing precision/accuracy calibration.

Include the entire interferometer chain - from mirror excitation/motion to acquisition system readout. I think this has been done in part already, although I am not sure the opto-mechanical component (mirror excitation to ADC readout) was included.
• End-to-end data integrity check.

Make sure data is valid when it is read out, written to disk, transferred to tape, sent to the CIT, injected into the archive, and read back from the archive.
• Quantify strength and stability of line noise in GW channel.

60 Hz and its harmonics are expected to be apparent in the GW channel. Study amplitude and phase stability of the contamination through course of run. Look for correlations between strength and IFO or environment conditions. Characterize violin modes and test mass vibration modes, i.e., Rayleigh behavior consistency, and correlation with IFO or environment. For example, is there ringdown immediately after lock acquisition? Is there growth?
• Evaluate data compression algorithms.

Compare lossy and lossless techniques, including statistical summaries when environmental data appear "quiet". Produce samples of reduced data with which other DC investigators can make comparisons in algorithm performance before and after compression (e.g., efficiency for transient detection, cross-channel regression).
• Investigate occurrence and propagation of frequency noise

Frequency noise may very well dominate many or all of the outputs over much of the frequency range. This investigation would follow this prototypical noise source through the system and learn as much as possible about it. Part of this investigation is studying the correlations among the longitudinal servo control signals, including the behavior of the heirarchical scheme for l+ and L+ control. Since there is natural overlap with other tasks above (e.g. stationarity, gaussianity, bursts and transients, line features), investigators on this task will work with other task teams.