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Time Series Data Server (TSDS) is a software package for implementing aserver that provides fast super-setting, sub-setting, filtering, and uniformgridding of time series-like data. TSDS was developed to respond quickly torequests for long time spans of data. Data may be served from a fast database,typically created by aggregating granules (e.g., data files) from a remote datasource and storing them in a local cache that is optimized for serving timeseries. The system was designed specifically for time series data, and isoptimized for requests where the longest dimension of the requested datastructure is time. Scalar, vector, and spectrogram time series types aresupported. The user can interact with the server by requesting a time series, adate range, and an optional filter to apply to the data. Available filtersinclude strides, block average/minimum/maximum, exclude, and inequality.Constraint expressions are supported, which allow such operations as a requestfor data from one time series when a different time series satisfied aspecified relationship. TSDS builds upon DAP (Data Access Protocol), NcML(netCDF Mark-up language) and related software libraries. In this work, wedescribe the current design of this server, as well as planned features andpotential implementation strategies.

TSDS: high-performance merge, subset, and filter software for time series-like data