The mediated data integration (MeDInt) : An approach to the integration of database and legacy systems

The information required for decision making by executives in organizations is normally scattered across disparate data sources including databases and legacy systems. To gain a competitive advantage, it is extremely important for executives to be able to obtain one unique view of information in an accurate and timely manner. To do this, it is necessary to interoperate multiple data sources, which differ structurally and semantically. Particular problems occur when applying traditional integration approaches, for example, the global schema needs to be recreated when the component schema has been modified. This research investigates the following heterogeneities between heterogeneous data sources: Data Model Heterogeneities, Schematic Heterogeneities and Semantic Heterogeneities. The problems of existing integration approaches are reviewed and solved by introducing and designing a new integration approach to logically interoperate heterogeneous data sources and to resolve three previously classified heterogeneities. The research attempts to reduce the complexity of the integration process by maximising the degree of automation. Mediation and wrapping techniques are employed in this research. The Mediated Data Integration (MeDint) architecture has been introduced to integrate heterogeneous data sources. Three major elements, the MeDint Mediator, wrappers, and the Mediated Data Model (MDM) play important roles in the integration of heterogeneous data sources. The MeDint Mediator acts as an intermediate layer transforming queries to sub-queries, resolving conflicts, and consolidating conflict-resolved results. Wrappers serve as translators between the MeDint Mediator and data sources. Both the mediator and wrappers arc well-supported by MDM, a semantically-rich data model which can describe or represent heterogeneous data schematically and semantically. Some organisational information systems have been tested and evaluated using the MeDint architecture. The results have addressed all the research questions regarding the interoperability of heterogeneous data sources. In addition, the results also confirm that the Me Dint architecture is able to provide integration that is transparent to users and that the schema evolution does not affect the integration

Negotiation in Database Schema Integration

Databases are playing an increasingly important role in organizations. Timely, accurate access to information has become a critical component of gaining competitive advantage. Data availability is commonly perceived as a critical success factor for an organizationÕs long-term survival, and day-to-day operations can be crippled by failure of the database system to satisfy user requirements. However, a number of emerging issues complicate organizationsÕ ability to provide comprehensive and reliable access to disparate information resources. Further, data accessibility is often compromised due to the typically high cost associated with addressing these issues in practice. Examples of such issues which have emerged in the past decade include the proliferation and investment in autonomous databases within organizations, heterogeneity among data models and database management systems employed, the increasingly important role of distributed systems, and the increasing complexity and knowledge-intensive nature of integrating database schemas. All these factors contribute to the increasing importance of developing feasible options for providing interoperability among existing databases, and therefore, of pursuing research in the area of database schema integration. Indeed, this research focuses specifically on knowledge requirement problems involved in integrating the schema of existing databases in order to provide interoperability and transparent access to disparate information resources without the investment involved in complete systems redesig

On Resolving Semantic Heterogeneities and Deriving Constraints in Schema Integration

Ph.DDOCTOR OF PHILOSOPH

Semantic Web Based Relational Database Access With Conflict Resolution

This thesis focuses on (1) accessing relational databases through Semantic Web technologies and (2) resolving conflicts that usually arises when integrating data from heterogeneous source schemas and/or instances. In the first part of the thesis, we present an approach to access relational databases using Semantic Web technologies. Our approach is built on top of Ontop framework for Ontology Based Data Access. It extracts both Ontop mappings and an equivalent OWL ontology from an existing database schema. The end users can then access the underlying data source through SPARQL queries. The proposed approach takes into consideration the different relationships between the entities of the database schema when it extracts the mapping and the equivalent ontology. Instead of extracting a flat ontology that is an exact copy of the database schema, it extracts a rich ontology. The extracted ontology can also be used as an intermediary between a domain ontology and the underlying database schema. Our approach covers independent or master entities that do not have foreign references, dependent or detailed entities that have some foreign keys that reference other entities, recursive entities that contain some self references, binary join entities that relate two entities together, and n-ary join entities that map two or more entities in an n-ary relation. The implementation results indicate that the extracted Ontop mappings and ontology are accurate. i.e., end users can query all data (using SPARQL) from the underlying database source in the same way as if they have written SQL queries. In the second part, we present an overview of the conflict resolution approaches in both conventional data integration systems and collaborative data sharing communities. We focus on the latter as it supports the needs of scientific communities for data sharing and collaboration. We first introduce the purpose of the study, and present a brief overview of data integration. Next, we talk about the problem of inconsistent data in conventional integration systems, and we summarize the conflict handling strategies used to handle such inconsistent data. Then we focus on the problem of conflict resolution in collaborative data sharing communities. A collaborative data sharing community is a group of users who agree to share a common database instance, such that all users have access to the shared instance and they can add to, update, and extend this shared instance. We discuss related works that adopt different conflict resolution strategies in the area of collaborative data sharing, and we provide a comparison between them. We find that a Collaborative Data Sharing System (CDSS) can best support the needs of certain communities such as scientific communities. We then discuss some open research opportunities to improve the efficiency and performance of the CDSS. Finally, we summarize our work so far towards achieving these open research directions

An algorithm for Finding a Relationship Between Entities : Semi-Automated Schema Integration Approach

학위논문 (석사)-- 서울대학교 대학원 경영대학 경영학과, 2017. 8. 박진수.Database schema integration is a very important issue in information systems. Since schema integration is a time-consuming and labor-intensive task, many studies have attempted to automate this task. In the meantime, the researchers used xml as the source schema and still left much of the work to be done through DBA intervention. For example, there are various naming conflicts related to relationship names in schema integration. In the past, the DBA had to intervene to resolve the naming conflict name. In this paper, we introduce an algorithm that automatically generates relationship names to resolve relationship names conflicts that occur during schema integration. This algorithm is based on Internet collocation dictionary and english sentence example dictionary. The relationship between the two entities is generated by analyzing examples extracted based on dictionary data through natural language processing. By building a semi-automated schema integration system and testing this algorithm, we found that it showed about 90% accuracy. Using this algorithm, we can resolve the problems related to naming conflicts that occur at schema integration automatically without DBA intervention.1. Introduction 1 2. Methodologies for semi-automated schema integration 3 3. An algorithm for finding a relationship between entities 14 4. Semi-Automated Schema Integration 20 5. Evaluation 23 6. Limitations 24 7. Conclusion 25 Reference 26Maste

Semantics of Database Transformations

Database transformations arise in many different settings including database integrations, evolution of database systems, and implementing user views and data-entry tools. This paper surveys approaches that have been taken 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 are hindered by the interactions 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 briefly describe the WOL language and its semantics, and argue that it addresses many of the requirements of a formalism for dealing with general database transformations