Overview of schema matching to enable seamless data exchange and conversion

Mathematics Machine Learning Technology Artificial Intelligence Technology 　Database Technology Algorithm Programming Technology 　Digital Transformation ICT

From “Schema Matching and Mapping”.

In application areas such as e-business, web-based mashups, and life sciences, it is becoming increasingly important for heterogeneous information systems to communicate cooperatively. Such cooperative systems must automatically and efficiently collate, exchange, transform, and integrate large data sets from different sources and different structures to enable seamless data exchange and transformation.

This book, edited by Bellahsene, Bonifati, and Rahm, provides an overview of how schema and ontology collation and mapping tools have met the above requirements and points out future technical challenges. The contributions by leading experts are organized into three parts: “Large-scale, knowledge-driven schema matching,” “Quality-driven schema mapping and evolution,” and “Evaluation and tuning of matching tasks. The authors illustrate the state of the art by discussing the latest results on more effective methods for data matching, validation of mapping transformations, adaptation of matching and mapping tasks to context and size, evolution and merging of mapping-driven schemas, and evaluation and tuning of mappings. The paper provides an overview of the field. The result is a coherent overview of the field.

The book introduces graduate students and advanced students to this exciting field. For researchers, it also provides up-to-date reference material on schema and ontology matching, schema and ontology evolution, and schema merging.

The table of contents is given below.

1.Large-Scale and Knowledge-Driven Schema Matching

  1. Towards Large-Scale Schema and Ontology Matching

  2. Interactive Techniques to Support Ontology Matching

  3. Enhancing the Capabilities of Attribute Correspondences

  4. Uncertainty in Data Integration and Dataspace Support Platforms


2.Quality-Driven Schema Mapping and Evolution

  5. Discovery and Correctness of Schema Mapping Transformation

  6. Recent Advances in Schema and Ontology Evaluation

  7. Schema Mapping Evolution Trough Composition and Inversions

  8. Mapping Based Merging of Schemas


3.Evaluating and Tuning Matching Tasks

  9. On Evaluating Schema Matching and Mapping

 10. Tuning for Schema Matching