AGILE DATA METHOD APPLICATIONS IN A REAL-WORLD INTERDISCIPLINARY RESEARCH CONTEXT

New scientific discoveries that require collaboration across scientific disciplines will need strong data models to resolve data complexity. Blueprint Earth is pioneering the use of a new data model that is pushing the limits of data collection and analysis. This data model was created using the agile development model most commonly found in business, where development occurs in small, regressive cyclical phases to design, test, and improve development. Using data collected in the field from 4 broad scientific disciplines and numerous other subdisciplines, the new data architecture was developed in parallel with maturing data collection processes. This new paradigm emphasizes practical application and testing of the data model, instead of using traditional waterfall methods that can be slow and often miss the mark. This flexible data development paradigm allows for complex data from interdisciplinary scientific fields to be collected within a data set that can accommodate future unknowns. This approach to data model development produces a more useful data model with an alacrity that allows science to focus on science as opposed to data integration, data loss, and over-engineering of data solutions.