Applying Model Management to Classical Meta Data Problems

By Philip A. Bernstein. Conference on Innovative Data Systems Research, 2003

595 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/28196d7ffc32a6c48b9f7b364fa3df6c8e17127f

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Citations in the corpus

Merging Models Based on Given Correspondences (2003, methodology): “Merge is one of the operators proposed in [5] as part of model management, a framework that consists of operators for manipulating models and mappings.”
Matching and Merging of Statecharts Specifications (2007, background): “Such operators include Match, for finding correspondences between models, Diff, for finding differences between models, Merge, for putting together a set of models with respect to known relationships between them, and Slice, for producing a projection of a model based on a given criterion [2, 18, 6]”
Composing Mappings Among Data Sources (2003, background): “A second motivation for mapping composition comes from the area of model management [3, 23].”
Rondo: a programming platform for generic model management (2003, methodology): “The change propagation script of Section 2 is an alternative realization of the round-trip engineering scenario presented in [5].”
Data Integration for the Relational Web (2009, methodology): “In this way, the Octopus operators are similar to traditional Web search ranking (or to the match operator in the model management literature [1]).”
Composing schema mappings: second-order dependencies to the rescue (2004, background): “Bernstein [5] has introduced such a framework, called model management , in which the main abstractions are schemas and mappings between schemas, as well as operators for manipulating schemas”
Automating Co-evolution in Model-Driven Engineering (2008, background): “The issues discussed in this work can be also found in the context of database evolution and metadata handling, which have been demonstrated to share several problems related to model management [1].”
Schema mappings, data exchange, and metadata management (2005, background): “Bernstein [6] has made a compelling case for the importance of developing both the theory and the practice of metadata management.”
Web-Scale Data Integration: You can afford to Pay as You Go (2007, result): “While similar in spirit to model management [4], our repository stores approximate mappings and schema clusters rather than exact mappings.”
The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox (2014, result): “In contrast with prior work on model management in database systems, which was largely concerned with managing deterministic metadata (such as schema) [4], Velox focuses on the use and management of statistical models from the domain of machine learning.”