A survey of approaches to automatic schema matching
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paper_title: Data warehouse scenarios for model management

paper_content:

Model management is a framework for supporting meta-data related applications where models and mappings are manipulated as first class objects using operations such as Match, Merge, ApplyFunction, and Compose. To demonstrate the approach, we show how to use model management in two scenarios related to loading data warehouses. The case study illustrates the value of model management as a methodology for approaching meta-data related problems. It also helps clarify the required semantics of key operations. These detailed scenarios provide evidence that generic model management is useful and, very likely, implementable.
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paper_title: Issues and approaches of database integration

paper_content:

In many large companies the widespread usage of computers has led a number of different application-specific databases to be installed. As company structures evolve, boundaries between departments move, creating new business units. Their new applications will use existing data from various data stores, rather than new data entering the organization. Henceforth, the ability to make data stores interoperable becomes a crucial factor for the development of new information systems. Data interoperability may come in various degrees. At the lowest level, commercial gateways connect specific pairs of database management systems (DBMSs). Software providing facilities for defining persistent views over different databases [6] simplifies access to distant data but does not support automatic enforcement of consistency constraints among different databases. Full interoperability is achieved by distributed or federated database systems, which support integration of existing data into virtual databases (i.e. databases which are logically defined but not physically materialized). The latter allow existing databases to remain under control of their respective owners, thus supporting a harmonious coexistence of scalable data integration and site autonomy requirements [9]. Federated systems are very popular today. However, before they become marketable, many issues remain to be solved. Design issues focus on either human-centered aspects (cooperative work, including autonomy issues and negotiation procedures) or database-centered aspects (data integration, schema/database evolution). Operational issues investigate system interoperability mainly in terms of support of new transaction types, new query processing algorithms, security concerns, etc. General overviews may be found elsewhere [4, 9]. This paper is devoted to database integration, possibly the most critical issue. Simply stated, database integration is the process which takes as input a set of databases, and produces as output a single unified description of the input schemas (the integrated schema) and the associated mapping information supporting integrated access to existing data through the integrated schema. As such, database integration is also used in the process of re-engineering an exist i ng l egacy system. Database integration has attracted many diverse and diverging contributions. The purpose, and the main intended contribution of this article is to provide a clear picture of what are the approaches and the current solutions and what remains to be achieved.
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paper_title: A comparative analysis of methodologies for database schema integration

paper_content:

One of the fundamental principles of the database approach is that a database allows a nonredundant, unified representation of all data managed in an organization. This is achieved only when methodologies are available to support integration across organizational and application boundaries. Methodologies for database design usually perform the design activity by separately producing several schemas, representing parts of the application, which are subsequently merged. Database schema integration is the activity of integrating the schemas of existing or proposed databases into a global, unified schema. The aim of the paper is to provide first a unifying framework for the problem of schema integration, then a comparative review of the work done thus far in this area. Such a framework, with the associated analysis of the existing approaches, provides a basis for identifying strengths and weaknesses of individual methodologies, as well as general guidelines for future improvements and extensions.
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paper_title: Federated database systems for managing distributed, heterogeneous, and autonomous databases

paper_content:

A federated database system (FDBS) is a collection of cooperating database systems that are autonomous and possibly heterogeneous. In this paper, we define a reference architecture for distributed database management systems from system and schema viewpoints and show how various FDBS architectures can be developed. We then define a methodology for developing one of the popular architectures of an FDBS. Finally, we discuss critical issues related to developing and operating an FDBS.
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paper_title: Data warehouse scenarios for model management

paper_content:

Model management is a framework for supporting meta-data related applications where models and mappings are manipulated as first class objects using operations such as Match, Merge, ApplyFunction, and Compose. To demonstrate the approach, we show how to use model management in two scenarios related to loading data warehouses. The case study illustrates the value of model management as a methodology for approaching meta-data related problems. It also helps clarify the required semantics of key operations. These detailed scenarios provide evidence that generic model management is useful and, very likely, implementable.
---
paper_title: Data warehouse scenarios for model management

paper_content:

Model management is a framework for supporting meta-data related applications where models and mappings are manipulated as first class objects using operations such as Match, Merge, ApplyFunction, and Compose. To demonstrate the approach, we show how to use model management in two scenarios related to loading data warehouses. The case study illustrates the value of model management as a methodology for approaching meta-data related problems. It also helps clarify the required semantics of key operations. These detailed scenarios provide evidence that generic model management is useful and, very likely, implementable.
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paper_title: A theory of attributed equivalence in databases with application to schema integration

paper_content:

The authors present a common foundation for integrating pairs of entity sets, pairs of relationship sets, and an entity set with a relationship set. This common foundation is based on the basic principle of integrating attributes. Any pair of objects whose identifying attributes can be integrated can themselves be integrated. Several definitions of attribute equivalence are presented. These definitions can be used to specify the exact nature of the relationship between a pair of attributes. Based on these definitions, several strategies for attribute integration are presented and evaluated. >
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paper_title: Automated resolution of semantic heterogeneity in multidatabases

paper_content:

A multidatabase system provides integrated access to heterogeneous, autonomous local databases in a distributed system. An important problem in current multidatabase systems is identification of semantically similar data in different local databases. The Summary Schemas Model (SSM) is proposed as an extension to multidatabase systems to aid in semantic identification. The SSM uses a global data structure to abstract the information available in a multidatabase system. This abstracted form allows users to use their own terms (imprecise queries) when accessing data rather than being forced to use system-specified terms. The system uses the global data structure to match the user's terms to the semantically closest available system terms. A simulation of the SSM is presented to compare imprecise-query processing with corresponding query-processing costs in a standard multidatabase system. The costs and benefits of the SSM are discussed, and future research directions are presented.
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paper_title: A theory of attributed equivalence in databases with application to schema integration

paper_content:

The authors present a common foundation for integrating pairs of entity sets, pairs of relationship sets, and an entity set with a relationship set. This common foundation is based on the basic principle of integrating attributes. Any pair of objects whose identifying attributes can be integrated can themselves be integrated. Several definitions of attribute equivalence are presented. These definitions can be used to specify the exact nature of the relationship between a pair of attributes. Based on these definitions, several strategies for attribute integration are presented and evaluated. >
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paper_title: SYSTEM/U: a database system based on the universal relation assumption

paper_content:

System/U is a universal relation database system under development at Standford University which uses the language C on UNIX. The system is intended to test the use of the universal view, in which the entire database is seen as one relation. This paper describes the theory behind System/U, in particular the theory of maximal objects and the connection between a set of attributes. We also describe the implementation of the DDL (Data Description Language) and the DML (Data Manipulation Language), and discuss in detail how the DDL finds maximal objects and how the DML determines the connection between the attributes that appear in a query.
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paper_title: DataGuides : Enabling Query Formulation and Optimization in Semistructured Databases *

paper_content:

In semistructured databases there is no schema fixed in advance. To provide the benefits of a schema in such environments, we introduce DataGuides: concise and accurate structural summaries of semistructured databases. DataGuides serve as dynamic schemas, generated from the database; they are useful for browsing database structure, formulating queries, storing information such as statistics and sample values, and enabling query optimization. This paper presents the theoretical foundations of DataGuides along with an algorithm for their creation and an overview of incremental maintenance. We provide performance results based on our implementation of DataGuides in the Lore DBMS for semistructured data. We also describe the use of DataGuides in Lore, both in the user interface to enable structure browsing and query formulation, and as a means of guiding the query processor and optimizing query execution.
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paper_title: Multifaceted exploitation of metadata for attribute match discovery in information integration

paper_content:

Automating semantic matching of attributes for the purpose of information integration is challenging, and the dynamics of the Web further exacerbate this problem. Believing that many facets of metadata can contribute to a resolution, we present a framework for multifaceted exploitation of metadata in which we gather information about potential matches from various facets of metadata and combine this information to generate and place confidence values on potential attribute matches. To make the framework apply in the highly dynamic Web environment, we base our process largely on machine learning. Experiments we have conducted are encouraging, showing that when the combination of facets converges as expected, the results are highly reliable.
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paper_title: Experience with a Combined Approach to Attribute-Matching Across Heterogeneous Databases

paper_content:

Determining attribute correspondences is a difficult, time-consuming, knowledge-intensive part of database integration. We report on experiences with tools that identified candidate correspondences, as a step in a large scale effort to improve communication among Air Force systems. First, we describe a new method that was both simple and surprisingly successful: Data dictionary and catalog information were dumped to unformatted text; then off-the-shelf information retrieval software estimated string similarity, generated candidate matches, and provided the interface. The second method used a different set of clues, such as statistics on database populations, to compute separate similarity metrics (using neural network techniques). We report on substantial use of the first tool, and then report some limited initial experiments that examine the two techniques’ accuracy, consistency and complementarity.
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paper_title: Global viewing of heterogeneous data sources

paper_content:

The problem of defining global views of heterogeneous data sources to support querying and cooperation activities is becoming more and more important due to the availability of multiple data sources within complex organizations and in global information systems. Global views are defined to provide a unified representation of the information in the different sources by analyzing conceptual schemas associated with them and resolving possible semantic heterogeneity. We propose an affinity based unification method for global view construction. In the method: (1) the concept of affinity is introduced to assess the level of semantic relationship between elements in different schemas by taking into account semantic heterogeneity; (2) schema elements are classified by affinity levels using clustering procedures so that their different representations can be analyzed for unification; (3) global views are constructed starting from selected clusters by unifying representations of their elements. Experiences of applying the proposed unification method and the associated tool environment ARTEMIS on databases of the Italian Public Administration information systems are described.
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paper_title: Using Schema Matching to Simplify Heterogeneous Data Translation

paper_content:

A broad spectrum of data is available on the Web in distinct heterogeneous sources, and stored under different formats. As the number of systems that utilize this heterogeneous data grows, the importance of data translation and conversion mechanisms increases greatly. In this paper we present a new translation system, based on schema-matching, aimed at simplifying the intricate task of data conversion. We observe that in many cases the schema of the data in the source system is very similar to that of the target system. In such cases, much of the translation work can be done automatically, based on the schemas similarity. This saves a lot of effort for the user, limiting the amount of programming needed. We define common schema and data models, in which schemas and data (resp.) from many common models can be represented. Using a rule-based method, the source schema is compared with the target one, and each component in the source schema is matched with a corresponding component in the target schema. Then, based on the matching achieved, data instances of the source schema can be translated to instances of the target schema. We show that our schema-based translation system allows a convenient specification and customization of data conversions, and can be easily combined with the traditional data-based translation languages.
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paper_title: Generic Schema Matching with Cupid

paper_content:

Schema matching is a critical step in many applications, such as XML message mapping, data warehouse loading, and schema integration. In this paper, we investigate algorithms for generic schema matching, outside of any particular data model or application. We first present a taxonomy for past solutions, showing that a rich range of techniques is available. We then propose a new algorithm, Cupid, that discovers mappings between schema elements based on their names, data types, constraints, and schema structure, using a broader set of techniques than past approaches. Some of our innovations are the integrated use of linguistic and structural matching, context-dependent matching of shared types, and a bias toward leaf structure where much of the schema content resides. After describing our algorithm, we present experimental results that compare Cupid to two other schema matching systems.
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paper_title: The Clio project: managing heterogeneity

paper_content:

Clio is a system for managing and facilitating the complex tasks of heterogeneous data transformation and integration. In Clio, we have collected together a powerful set of data management techniques that have proven invaluable in tackling these difficult problems. In this paper, we present the underlying themes of our approach and present a brief case study.
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paper_title: Data-driven understanding and refinement of schema mappings

paper_content:

At the heart of many data-intensive applications is the problem of quickly and accurately transforming data into a new form. Database researchers have long advocated the use of declarative queries for this process. Yet tools for creating, managing and understanding the complex queries necessary for data transformation are still too primitive to permit widespread adoption of this approach. We present a new framework that uses data examples as the basis for understanding and refining declarative schema mappings. We identify a small set of intuitive operators for manipulating examples. These operators permit a user to follow and refine an example by walking through a data source. We show that our operators are powerful enough both to identify a large class of schema mappings and to distinguish effectively between alternative schema mappings. These operators permit a user to quickly and intuitively build and refine complex data transformation queries that map one data source into another.
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paper_title: Experience with a Combined Approach to Attribute-Matching Across Heterogeneous Databases

paper_content:

Determining attribute correspondences is a difficult, time-consuming, knowledge-intensive part of database integration. We report on experiences with tools that identified candidate correspondences, as a step in a large scale effort to improve communication among Air Force systems. First, we describe a new method that was both simple and surprisingly successful: Data dictionary and catalog information were dumped to unformatted text; then off-the-shelf information retrieval software estimated string similarity, generated candidate matches, and provided the interface. The second method used a different set of clues, such as statistics on database populations, to compute separate similarity metrics (using neural network techniques). We report on substantial use of the first tool, and then report some limited initial experiments that examine the two techniques’ accuracy, consistency and complementarity.
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Title: A Survey of Approaches to Automatic Schema Matching

Section 1: Introduction
Description 1: Provide an overview and motivation for the problem of schema matching, highlighting the need for automated solutions in various application domains.

Section 2: Application domains
Description 2: Summarize the use of schema matching across different database application domains to emphasize its importance.

Section 3: The match operator
Description 3: Define the match operator, including its input, output, and how it functions to match schema elements.

Section 4: Architecture for generic match
Description 4: Describe the high-level architecture for implementing a generic and customizable match operator, detailing the interaction between different components.

Section 5: Classification of schema matching approaches
Description 5: Provide a taxonomy for the different approaches to schema matching, categorizing them based on various criteria such as schema-level vs. instance-level, element-level vs. structure-level, and linguistic vs. constraint-based approaches.

Section 6: Schema-level matchers
Description 6: Discuss schema-level matching techniques, including element-level and structure-level matching, linguistic approaches, and constraint-based matchers.

Section 7: Instance-level approaches
Description 7: Explore instance-level matching techniques that rely on the actual data instances to improve the accuracy of schema matching.

Section 8: Combining different matchers
Description 8: Explain the methodologies for combining different matchers to enhance the accuracy and effectiveness of schema matching, including hybrid matchers and composite matchers.

Section 9: Prototype schema matchers
Description 9: Review various prototype implementations of schema matchers, comparing their approaches, strengths, and weaknesses.

Section 10: Conclusion
Description 10: Summarize the key points covered in the survey and discuss potential future research directions in the field of schema matching.