III: EAGER: Aspect-Oriented Data Weaving

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The goal of this research program is to develop a new paradigm for databases, called aspect-oriented data (AOD). AOD enables cross-cutting data concerns to be added to a database using aspect-oriented programming. A cross-cutting data concern is a data need that is universal (potentially applicable to the entire database) and widespread (can be used to enhance many, different databases). Data has a wide variety of cross-cutting data concerns, including provenance, time, lineage, and security. So this research has the potential to impact every database. The project achieves its goal by conducting the following tasks: 1) Develop a model for aspect-oriented data in which advice (metadata) can "tag" or annotate data, 2) Build a data aspect weaver to weave the advice into queries, constraints, and data modification, 3) Develop advice-specific modules for common cross-cutting concerns that plug into the data aspect weaver and add advice-specific behaviors, 4) Demonstrate that aspects themselves can be aspected to model meta-metadata, and 5) Develop test cases for AOD. The data aspect weaver is being developed for Pig Latin, which is a cloud-computing platform for data analysis. The research impacts database management systems, scientific databases, and digital government. The project supports a Ph.D. student to pursue research in databases. Publications, technical reports, and software from this research are disseminated on the project's web site (http://www.cs.usu.edu/~cdyreson/aspectOrientedData).