Managing Schema Change in an Heterogeneous Environment

Change is inevitable even for persistent information. Effectively managing change of persistent information, which includes the specification, execution and the maintenance of any derived information, is critical and must be addressed by all database systems. Today, for every data model there exists a well-defined set of change primitives that can alter both the structure (the schema) and the data. Several proposals also exist for incrementally propagating a primitive change to any derived information (or view). However, existing support is lacking in two ways. First, change primitives as presented in literature are very limiting in terms of their capabilities allowing users to simply add or remove schema elements. More complex types of changes such the merging or splitting of schema elements are not supported in a principled manner. Second, algorithms for maintaining derived information often do not account for the potential heterogeneity between the source and the target. The goal of this dissertation is to provide solutions that address these two key issues. The first part of this dissertation addresses the challenge of expressing a rich complex set of changes. We propose the SERF (Schema Evolution through an Extensible, Re-usable and Flexible) framework that allows users to perform a wide range of complex user-defined schema transformations. Our approach combines existing schema evolution primitives using OQL (object query language) as the glue logic. Within the context of this work, we look at the different domains in which SERF can be applied, including web site management. To further enrich our framework, we also investigate the optimization and verification of SERF transformations. The second part of this dissertation addresses the problem of maintaining views in the face of source changes when the source and the view are not in the same data model. With today\u27s increasing heterogeneity in information structure, it is critical that maintenance of views addresses the data model boundaries. However, view definitions that go across data models are limited to hard-coded algorithms, thereby making it difficult to develop general maintenance algorithms. We provide a two-step solution for this problem. We have developed a cross algebra, that defines views such that there is no restriction that forces the view and the source data models to be the same. We then define update propagation algorithms that can propagate changes from source to target irrespective of the exact translation and the data models. We validate our ideas by applying them to translation and change propagation between the XML and relational data models

MOMIS: Exploiting agents to support information integration

Information overloading introduced by the large amount of data that is spread over the Internet must be faced in an appropriate way. The dynamism and the uncertainty of the Internet, along with the heterogeneity of the sources of information are the two main challenges for today's technologies related to information management. In the area of information integration, this paper proposes an approach based on mobile software agents integrated in the MOMIS (Mediator envirOnment for Multiple Information Sources) infrastructure, which enables semi-automatic information integration to deal with the integration and query of multiple, heterogeneous information sources (relational, object, XML and semi-structured sources). The exploitation of mobile agents in MOMIS can significantly increase the flexibility of the system. In fact, their characteristics of autonomy and adaptability well suit the distributed and open environments, such as the Internet. The aim of this paper is to show the advantages of the introduction in the MOMIS infrastructure of intelligent and mobile software agents for the autonomous management and coordination of integration and query processing over heterogeneous data sources

Query processing in temporal object-oriented databases

This PhD thesis is concerned with historical data management in the context of objectoriented databases. An extensible approach has been explored to processing temporal object queries within a uniform query framework. By the uniform framework, we mean temporal queries can be processed within the existing object-oriented framework that is extended from relational framework, by extending the existing query processing techniques and strategies developed for OODBs and RDBs. The unified model of OODBs and RDBs in UmSQL/X has been adopted as a basis for this purpose. A temporal object data model is thereby defined by incorporating a time dimension into this unified model of OODBs and RDBs to form temporal relational-like cubes but with the addition of aggregation and inheritance hierarchies. A query algebra, that accesses objects through these associations of aggregation, inheritance and timereference, is then defined as a general query model /language. Due to the extensive features of our data model and reducibility of the algebra, a layered structure of query processor is presented that provides a uniforrn framework for processing temporal object queries. Within the uniform framework, query transformation is carried out based on a set of transformation rules identified that includes the known relational and object rules plus those pertaining to the time dimension. To evaluate a temporal query involving a path with timereference, a strategy of decomposition is proposed. That is, evaluation of an enhanced path, which is defined to extend a path with time-reference, is decomposed by initially dividing the path into two sub-paths: one containing the time-stamped class that can be optimized by making use of the ordering information of temporal data and another an ordinary sub-path (without time-stamped classes) which can be further decomposed and evaluated using different algorithms. The intermediate results of traversing the two sub-paths are then joined together to create the query output. Algorithms for processing the decomposed query components, i. e., time-related operation algorithms, four join algorithms (nested-loop forward join, sort-merge forward join, nested-loop reverse join and sort-merge reverse join) and their modifications, have been presented with cost analysis and implemented with stream processing techniques using C++. Simulation results are also provided. Both cost analysis and simulation show the effects of time on the query processing algorithms: the join time cost is linearly increased with the expansion in the number of time-epochs (time-dimension in the case of a regular TS). It is also shown that using heuristics that make use of time information can lead to a significant time cost saving. Query processing with incomplete temporal data has also been discussed

A PC Chase

PC stands for path-conjunctive, the name of a class of queries and dependencies that we define over complex values with dictionaries. This class includes the relational conjunctive queries and embedded dependencies, as well as many interesting examples of complex value and oodb queries and integrity constraints. We show that some important classical results on containment, dependency implication, and chasing extend and generalize to this class

The Application of Object-Oriented Views to an Engineering Environment.

With the increasing popularity of object-oriented technology, object-oriented database systems are being used in design environments as central repositories. In this thesis, we investigate the role of versioning and the characteristics of design databases in design environments. In an effort to improve the configuration management scheme in a design environment, we also investigate the use of database views as a possible configuration tool. We propose a unified version management scheme that facilitates cooperative team work and show that the use of database views provides a powerful configuration management scheme for a design environment

Schema Management for Data Integration: A Short Survey

Schema management is a basic problem in many database application domains such as data integration systems. Users need to access and manipulate data from several databases. In this context, in order to integrate data from distributed heterogeneous database sources, data integration systems demand the resolution of several issues that arise in managing schemas. In this paper, we present a brief survey of the problem of schema matching which is used for solving problems of schema integration processing. Moreover, we propose a technique for integrating and querying distributed heterogeneous XML schemas.

Migrating relational databases into object-based and XML databases

Rapid changes in information technology, the emergence of object-based and WWW applications, and the interest of organisations in securing benefits from new technologies have made information systems re-engineering in general and database migration in particular an active research area. In order to improve the functionality and performance of existing systems, the re-engineering process requires identifying and understanding all of the components of such systems. An underlying database is one of the most important component of information systems. A considerable body of data is stored in relational databases (RDBs), yet they have limitations to support complex structures and user-defined data types provided by relatively recent databases such as object-based and XML databases. Instead of throwing away the large amount of data stored in RDBs, it is more appropriate to enrich and convert such data to be used by new systems. Most researchers into the migration of RDBs into object-based/XML databases have concentrated on schema translation, accessing and publishing RDB data using newer technology, while few have paid attention to the conversion of data, and the preservation of data semantics, e.g., inheritance and integrity constraints. In addition, existing work does not appear to provide a solution for more than one target database. Thus, research on the migration of RDBs is not fully developed. We propose a solution that offers automatic migration of an RDB as a source into the recent database technologies as targets based on available standards such as ODMG 3.0, SQL4 and XML Schema. A canonical data model (CDM) is proposed to bridge the semantic gap between an RDB and the target databases. The CDM preserves and enhances the metadata of existing RDBs to fit in with the essential characteristics of the target databases. The adoption of standards is essential for increased portability, flexibility and constraints preservation. This thesis contributes a solution for migrating RDBs into object-based and XML databases. The solution takes an existing RDB as input, enriches its metadata representation with the required explicit semantics, and constructs an enhanced relational schema representation (RSR). Based on the RSR, a CDM is generated which is enriched with the RDB's constraints and data semantics that may not have been explicitly expressed in the RDB metadata. The CDM so obtained facilitates both schema translation and data conversion. We design sets of rules for translating the CDM into each of the three target schemas, and provide algorithms for converting RDB data into the target formats based on the CDM. A prototype of the solution has been implemented, which generates the three target databases. Experimental study has been conducted to evaluate the prototype. The experimental results show that the target schemas resulting from the prototype and those generated by existing manual mapping techniques were comparable. We have also shown that the source and target databases were equivalent, and demonstrated that the solution, conceptually and practically, is feasible, efficient and correct