Date of Award:

8-2021

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Computer Science

Committee Chair(s)

Curtis Dyreson

Committee

Curtis Dyreson

Committee

Dan Watson

Committee

Steve Petruzza

Abstract

This research is about transforming data. Data comes in different shapes; it can be structured as a graph, a tree, a collection of tables, or some other shape. In this thesis, we focus on data structured as a tree, which is known as hierarchical data. The same data could be structured in many different tree shapes. Previously it was shown how to transform data from one tree shape, one hierarchy to another without losing any information. But sometimes the pieces of the hierarchy are annotated or associated with metadata, that is, with data about the data itself. The metadata can have special semantics that must be preserved when the data is transformed. Previous research also sketched how to transform hierarchical data annotated with metadata without losing information while preserving the semantics of the metadata. In this thesis, we implement the research on transforming data with metadata by extending XMorph, a data transformation language. And we evaluate the extension showing that the overhead is modest.

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