Abstract. Database transformations arise in many di erent settings including database integration, evolution of database systems, and implementing user views and data-entry tools. This paper surveys approaches that have beentaken to problems in these settings, assesses their strengths and weaknesses, and develops requirements on a formal model for specifying and implementing database transformations. We also consider the problem of insuring the correctness of database transformations. In particular, we demonstrate that the usefulness of correctness conditions such as information preservation is hindered by theinteractions of transformations and database constraints, and the limited expressive power of established database constraint languages. We conclude that more general notions of correctness are required, and that there is a need for a uniform formalism for expressing both database transformations and constraints, and reasoning about their interactions. Finally we introduce WOL, a declarative language for specifying and implementing database transformations and constraints. We brie y describe the WOL language and its semantics, and argue that it addresses many of the requirements on a formalism for dealing with general database transformations. 1

We present a formal framework for the combination of schemas. A main problem addressed is that of determining when two schemas can be meaningfully integrated. Another problem is how to merge two schemas into an integrated schema that has the same information capacity as the original ones, i.e., that the resulting schema can represent as much information as the original schemas. We show that both these problems can be solved by placing a restriction on the schemas to be integrated. The restriction, called conflictfreeness, states that the rules of one schema together with a set of correspondence assertions may not restrict the models of the other schema. We also give decidability and complexity results for the problem of determining conflictfreeness. Keywords: schema integration, semantic interoperability, conceptual modelling 1. Introduction Database management systems have been available for more than two decades. They have been used mainly in the form of the hierarchical, network, a...

Database reformulation is the process of rewriting the data and rules of a deductive database in a functionally equivalent manner.

Two algorithms, called NeT and CoT, to translate relational schemas to XML schemas using various semantic constraints are presented. The XML schema representation we use is a language-independent formalism named XSchema, that is both precise and concise. A given XSchema can be mapped to a schema in any of the existing XML schema language proposals. Our proposed algorithms have the following characteristics: (1) NeT derives a nested structure from a flat relational model by repeatedly applying the nest operator on each table so that the resulting XML schema becomes hierarchical, and (2) CoT considers not only the structure of relational schemas, but also semantic constraints such as inclusion dependencies during the translation. It takes as input a relational schema where multiple tables are interconnected through inclusion dependencies and converts it into a good XSchema. To validate our proposals, we present experimental results using both real schemas from the UCI repository and synthetic schemas from TPC-H.

The future of the Semantic Web depends on whether or not we succeed to integrate reliably thousands of online applications, services, and databases. These systems are tied together using mediators, mappings, database views, and transformation scripts. Model-management aims at reducing the amount of programming needed for the development of such integrated applications. We present a first complete prototype of a generic model-management system, in which high-level operators are used to manipulate models and mappings between models. We define the key operators and conceptual structures and describe their use and implementation. We examine the solutions for three model-management tasks: change propagation, view reuse, and reintegration. © 2003 Elsevier B.V. All rights reserved.

Abstract. Existing solutions to data and schema integration require user interaction/input to generate a data transformation between two different schemas. These approaches are not appropriate in situations where many data transformations are needed or where data transformations have to be generated frequently. We describe an approach to an automatic XML-transformation generator that is based on a theory of information-preserving and-approximating XML operations. Our approach builds on a formal semantics for XML operations and their associated DTD transformation and on an axiomatic theory of information preservation and approximation. This combination enables the inference of a sequence of XML transformations by a search algorithm based on the operations ’ DTD transformations. 1

Abstract. Data integration is frequently performed between heterogeneous data sources, requiring that not only a schema, but also the data modelling language in which that schema is represented must be transformed between one data source and another. This paper describes an extension to the hypergraph data model (HDM), used in the AutoMed data integration approach, that allows constraint constructs found in static data modelling languages to be represented by a small set of primitive constraint operators in the HDM. In addition, a set of five equivalence preserving transformation rules are defined that operate over this extended HDM. These transformation rules are shown to allow a bidirectional mapping to be defined between equivalent relational, ER, UML and ORM schemas. The approach we propose provides a precise framework in which to compare data modelling languages, and precisely identifies what semantics of a particular domain one data model may express that another data model may not express. The approach also forms the platform for further work in automating the process of transforming between different data modelling languages. The use of the both-as-view approach to data integration means that a bidirectional association is produced between schemas in the data modelling language. Hence a further advantage of the approach is that composition of data mappings may be performed such that mapping two schemas to one common schema will produce a bidirectional mapping between the original two data sources.

this report from s2 also. In this case, all we have to do is replace (R6.2) with the following rule.

A fundamental concern of information integration in an XML context is the ability to embed one or more source documents in a target document so that (a) the target document conforms to a target schema and (b) the information in the source document(s) is preserved. In this paper, information preservation for XML is formally studied, and the results of this study guide the definition of a novel notion of schema embedding between two XML DTD schemas represented as graphs. Schema embedding generalizes the conventional notion of graph similarity by allowing an edge in a source DTD schema to be mapped to a path in the target DTD. Instance-level embeddings can be defined from the schema embedding in a straightforward manner, such that conformance to a target schema and information preservation are guaranteed. We show that it is NP-complete to find an embedding between two DTD schemas. We also provide efficient heuristic algorithms to find candidate embeddings, along with experimental results to evaluate and compare the algorithms. These yield the first systematic and effective approach to finding information preserving XML mappings.

We develop a formal basis of correct schema transformations. Schemas are formalized as abstract data types, and correct schema transformations are formalized as information-preserving signature interpretations. Our formalism captures transformations of all schema components, making it possible to transform uniformly constraints and queries along with structures. In addition, our formalism captures schema transformations between different data models as easily as those within the same data model. Compared with Hull's notion of relative information capacity, our notion of information preservation captures more schema transformations that are natural, and fewer schema transformations that are unnatural. Our work lays the foundation of a transformational framework of schema manipulations. 1 Introduction Schema transformations, such as removing anomalies and redundancies, schema restructuring, and translating one schema to another (possibly in a different data model), constitute the major ...