MOBBED is a lightweight, easy-to-use, extensible toolkit that allows users to incorporate a computational database into their normal MATLAB workflow. Although capable of storing quite general types of annotated data, MOBBED is particularly well-suited to multichannel time series such as EEG that have event streams overlaid with sensor data.
A MOBBED database can archive primary data in a central place for a single investigator or research lab to save space and avoid inconsistencies. The database infrastructure includes the ability to manage, search, and retrieve events across multiple datasets without reading in the entire dataset, as well as being able to handle more complex event patterns that include environmental and context conditions. Systematic evaluation of algorithms and phenomena requires that primary data be subjected to a consistent preprocessing pipeline. MOBBED database allows users to store, catalog, and share the output of these pipelines. The database can also cache expensive intermediate results so that they can be reused in such activities as cross-validation of machine learning algorithms.
MOBBED is implemented over PostgreSQL, a widely used open source database and is freely available under the GNU general public license at http://visual.cs.utsa.edu/mobbed.
MOBBED and its supporting packages are freely available under the GNU general public license at:
CS-TR-2013-005, MOBBED (Mobile Brain-Body-Environment Decision Making) Part I: Database Design, by Jeremy Cockfield, Kyung Min Su and Kay Robbins, Department of Computer Science, University of Texas at San Antonio, Apr. 2013
CS-TR-2013-006, MOBBED (Mobile Brain-Body-Environment Decision Making) Part II: User Guide, by Jeremy Cockfield, Kyung Min Su and Kay Robbins, Department of Computer Science, University of Texas at San Antonio, Apr. 2013
Credit: The digital mosaic of cloud pictures was taken by the Environmental Science Services Administration (ESSA) 5 satellite on September 14, 1967. It shows more than a dozen storm areas, including hurricanes Beulah, Dora, Chloe, Monica, and Nannette. The image is not copyrighted.