Stuart Ozer, Alex Szalay, Katalin Szlavecz, Andreas Terzis, R\u azvan Mus\u aloiu-E., and Joshua Cogan
Science is increasingly driven by data collected automatically from arrays of inexpensive sensors. The collected data volumes require a different approach from the scientist’s current Excel spreadsheet storage and analysis model. Spreadsheets work well for small data sets; but scientists want high level summaries of their data for various statistical analyses without sacrificing the ability to drill down to every bit of the raw data. This article describes our prototype end-to-end system that is as simple to use as a spreadsheet, but that can scale to much larger data sets. The project (1) collects data using an array of wireless moisture and temperature sensors as a part of a soil ecosystem study, (2) inserts the raw data into an on-line database through a simple workflow system, (3) calibrates and grids the data as part of this workflow, (4) builds an OLAP data cube of the results, and (5) integrates the cube and base relational data with various simple graphical tools.