Project Title: III: EAGER: Aspect-Oriented Data Weaving
PI: Curtis Dyreson
Awardee: Utah State University
Award Number: 1144404

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 (AOP). 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. But developers currently have to rely on ad-hoc techniques to add these concerns to a data collection. To make the task easier, more flexible, and more general, we plan to apply techniques adapted from AOP to database management systems, preserving three key benefits of the aspect-oriented approach.

1. Aspect independence - Aspects are designed, developed, and coded independent of a particular database.
2. Late binding - Aspects can be woven into existing databases.
3. Lightweight footprint - It should be inexpensive and easy to weave an aspect into data.

In our approach, a data aspect "tags" data with metadata from a crosscutting data concern creating AOD. Once it is attached the aspect becomes active whenever the data is used. We plan to re-engineer Pig Latin to support AOD. Pig Latin is a cloud computing platform, used primarily for the analysis of massive data sets. We propose to build a data aspect weaver for weaving metadata into Pig Latin programs. The data weaver needs to be extensible so that developers can "plug-in" the semantics of different cross-cutting data concerns by specifying only a few core functions. In this way, many different aspects can be seamlessly supported. We also plan to develop test cases for AOD and show that aspects themselves can be aspected to model meta-metadata.