Heterogeneous Database Integration Research Articles

Semantic Integration of Heterogeneous Databases of Same Domain Using Ontology

Heterogeneous database integration is the study of integrating data from multiple databases. Integrating the heterogeneous database of the same domain has three main challenges that make the heterogeneity problem difficult to solve. The three problems are Semantic, Syntactic and Structural Heterogeneity. Conventional heterogeneous database integration schemes, like De-duplication Techniques, Data Warehouse, and Information Retrieval (IR) Search technique lack the capability to solve the integration of databases completely. The only reason is they cannot deal with Semantic heterogeneity problems efficiently. The semantic Web ontology model is experimented and discussed in the article, which is based on the query execution model. The ontology modeling is divided into two phases, initially to translate the database rules according to ontology rules to find an abstract ontology model. Secondly, to extend the abstract ontology model according to the databases. The method facilitates to apply similarly SPQRAL queries to search the data in the databases. Therefore, the Jena API is used to retrieve semantically similar records. The experiment is based on the two heterogeneous Universities Library Databases. The results show the effectiveness and scalability of the methodology.

Implementing an Improved Mediator Wrapper Paradigm for Heterogeneous Database Integration

This study developed and implemented an improved mediator wrapper approach to addressing the challenges of integration of semantic heterogeneous databases. It employed Local as View (LaV) paradigm of database integration so as to reduce its cost as well as offer the local sources a degree of independence. The developed model was implemented as web service using JEE and some software development tools with a number of heterogeneous databases as a case study.

Semantic Integration and Enrichment of Heterogeneous Biological Databases.

Biological databases are growing at an exponential rate, currently being among the major producers of Big Data, almost on par with commercial generators, such as YouTube or Twitter. While traditionally biological databases evolved as independent silos, each purposely built by a different research group in order to answer specific research questions; more recently significant efforts have been made toward integrating these heterogeneous sources into unified data access systems or interoperable systems using the FAIR principles of data sharing. Semantic Web technologies have been key enablers in this process, opening the path for new insights into the unified data, which were not visible at the level of each independent database. In this chapter, we first provide an introduction into two of the most used database models for biological data: relational databases and RDF stores. Next, we discuss ontology-based data integration, which serves to unify and enrich heterogeneous data sources. We present an extensive timeline of milestones in data integration based on Semantic Web technologies in the field of life sciences. Finally, we discuss some of the remaining challenges in making ontology-based data access (OBDA) systems easily accessible to a larger audience. In particular, we introduce natural language search interfaces, which alleviate the need for database users to be familiar with technical query languages. We illustrate the main theoretical concepts of data integration through concrete examples, using two well-known biological databases: a gene expression database, Bgee, and an orthology database, OMA.

Ontology based heterogeneous materials database integration and semantic query

Materials digital data, high throughput experiments and high throughput computations are regarded as three key pillars of materials genome initiatives. With the fast growth of materials data, the integration and sharing of data is very urgent, that has gradually become a hot topic of materials informatics. Due to the lack of semantic description, it is difficult to integrate data deeply in semantic level when adopting the conventional heterogeneous database integration approaches such as federal database or data warehouse. In this paper, a semantic integration method is proposed to create the semantic ontology by extracting the database schema semi-automatically. Other heterogeneous databases are integrated to the ontology by means of relational algebra and the rooted graph. Based on integrated ontology, semantic query can be done using SPARQL. During the experiments, two world famous First Principle Computational databases, OQMD and Materials Project are used as the integration targets, which show the availability and effectiveness of our method.

Big Data Analytics on Aviation data for the prediction of Airline Trends in Seasonal Delay

The trajectory of the global airline industry is pretty much like that of an aircraft. At times it takes off for the high skies and at times, it dips to ground levels. In between these highs and lows, lies the story of the industry – of its survival, of the new and emerging trends that fuel its growth. The issue of airline delays, as measured by the number of late arrivals as a percent of total operations, has been of increasing importance in recent years as most of the population chooses air travel as a preferred mode of transportation. This study provides the result about the total flight delay for a specific period of time caused due to climate, security, carrier, NAS, Arrival and Departure based on total number of flights getting delayed over the past few years (2006, 2007 and 2008). The historic data which is to be analysed is stored on the databases such as MongoDB and Hive. The usage of time series analysis along with the integration of heterogeneous database helps to achieve the Airline Seasonal Delay which is implemented and visualized in R. The reports are generated by using time series modeling to provide the insights for the aviation industry to take future measures to avoid delays and manage them.

Automatic Transformation of Relational Database Schema into OWL Ontologies

<p class="R-AbstractKeywords"><span lang="EN-US">Ontology alignment, or ontology matching, is a technique to map different concepts between ontologies. For this purpose at least two ontologies are required. In certain scenarios, such as data integration, heterogeneous database integration and data model compatibility evaluation, a need to transform a relational database schema to an ontology can arise. </span></p><p class="R-AbstractKeywords"><span lang="EN-US">To conduct a successful transformation it is necessary to identify the differences between relational database schema and ontology information representation methods, and then to define transformation rules. The most straight forward but time consuming way to carry out transformation is to do it manually. Often this is not an option due to the size of data to be transformed. For this reason there is a need for an automated solution.</span></p><p class="R-AbstractKeywords"><span lang="EN-US">The automatic transformation of OWL ontology from relational database schema is presented in this paper; the data representation differences between relational database schema and OWL ontologies are described; the transformation rules are defined and the transformation tool’s prototype is developed to perform the described transformation.</span></p>

University Employment Information Integration Model Based on Cloud Computing

Currently, many universities have set up their own system for providing employment information service, problems that following the independently operating and maintaining modes are: on the one hand, employers have to register a number of university employment information system to obtain information on a number of graduates; on the other hand, graduates also need to browse a number of university employment information site to get more information on business recruitment, which severely reduces the transparency and efficiency of information data queries. To solve the above problems, this paper propose the university employment information integration model on the basis of distributed storage and computing technology, which realizes the integration of multiple heterogeneous employment information database.

The olfactory receptor database: web-based resources for the genomics, proteomics and function of olfactory receptors

Olfactory receptors, the largest family in the genome, present an enormous challenge to understanding the molecular basis of how the information contained in odor molecules is transformed into the neural basis of smell perception. The Olfactory Receptor Database (ORDB) was created to support research with this goal. This talk will summarize salient aspects of ORDB as a comprehensive repository that stores and disseminates information related to the genomic, proteomics and functional aspects of olfactory receptors. ORDB is the result of almost two decades of work that has combined the efforts of chemosensory receptor experts, neuroscientists, computational experts, informatics researchers and clinicians, plus a growing community of contributors. Currently containing close to 15,000 olfactory and other chemosensory receptors, ORDB represents the work of more than a 100 laboratories worldwide, and contains receptors information for more than a hundred species. ORDB garners several hundred thousand visits from all over the world every year. ORDB is designed as a web-interface to a database architecture that makes for efficient storage and dissemination of the knowledge. More importantly, it allows the integration of heterogeneous databases within its framework—through a metadata-driven infrastructure. Two companion databases to ORDB—OdorDB (a repository of odor molecule with emphasis on those known to have been experimentally shown to activate ORs) and the new OdorModelDB (a repository of the results of computational modeling experiments on ORs) will also be described. Together, these three component databases aim to provide investigators with a comprehensive framework for understanding odor ligand-olfactory receptor interactions as the initial step in the neural processing of odor information. A fourth component, OdorMapDB, is a resource for investigating how the ligand-receptor interactions lead to representation as spatial activity maps in the olfactory bulb as the nextl step toward the neural basis of smell perception. Also discussed in this presentation will be efforts towards the development of software that not only populates ORDB in an automated manner, but also automatically updates data for relevance and timeliness. The unique infrastructure on which the olfactory databases are based is part of the SenseLab suite of databases. This infrastructure allows the resources to be searched for entries using a multi-parameter search system. These parameters are descriptors of various instances of information stored in ORDB. Such a search system allows the return of few specific and relevant results from several thousand. A live web-demonstration of ORDB, OdorDB and OdorModeDb will be part of the presentation.

On Heterogeneous Database Integration under the Scope of Web Service and Java

More and more accessible databases are available in the Web. In order to provide people a unified access to these Web heterogeneous databases and achieve information from them automatically. This paper proposes a comprehensive solution for heterogeneous database integration, explains the heterogeneity of the data source, analyzes the method of integration mod of heterogeneous data source by using interconnect technology of database and considers mainly the integration about the heterogeneous data source based on Web Service and Java. This solution is extensible and portable.

An Integration Solution to Heterogeneous Database Based on XML

Different databases have different structure,how to co-share those heterogeneous database is becoming a challenge to all of us.The current database integration methods is more and more complex, operability is not very strong, the author proposes an XML interchange file to achieve the integration of heterogeneous database program.The system logic structure diagram is given in this paper,major function modules and structure are introduced in detail combined with graphic, and finally the characteristics of the system is summarized.

The Research and Application of Heterogeneous Database Based on XML in Distance Education

this paper analyzes the problems of heterogeneous databases in a distance education system. It provides a heterogeneous database integration model based on XML and design and develop a heterogeneous database integration platform based on this model. Thus, it provides a unified standard and effective tool for teaching resource description and management in distance education.

A Generalized Framework for Biological Data Integration, Processing and Visualization

Massive amount of present biological datasets and their current rate of expansion demand effective ways of data storage, processing and presentation. The ever increasing nature of biological data sets has tremendously increased the complexity in data integration and presentation processes. This paper presents an experience of a unified framework development which combines complex input module with massive processing methods in a collaborative visualization environment. Our experience of the development of IDGAAM framework is presented in this paper along with functional details of AINAAN application. AINAAN is being used for collaborative environment for data sharing and more specifically for visualization purpose. The present study is an effort towards seamless integration of heterogeneous data bases with a complexity of analysis and varieties in its presentation formats.

Research of Data Tree Model in Coal Mine Heterogeneous Database Integration

Through the analysis of the characteristics of heterogeneous database of coal mine, design heterogeneous data integration of coal mine system. The application of the data tree model theory is to eliminate heterogeneous model of all the local databases. The mapping relation of global view and each local view is established in the same data model and we can achieve transparent access of heterogeneous data sources by using middleware technology.

Heterogeneous Databases Integration Approach Based on Hybrid Ontology

Ontology has a strong ability in expressing of the semantics and conception speculating, so is used to deal with the problems in the databases integration. In this paper, we relative analysis the weak points of the local and global ontology, establishing a hybrid ontology framework in the databases integration, integrated the query module, shied of the discrepancy between the different data source, and introduced some of the critical techniques and with the supervisory module, log be produced too, convenient for system maintain and upgrade.

Heterogeneous Database Integration Middleware Based on Web Services

With the company further accelerating the process of information, the heterogeneity problem of each business system database is more and more salient. How to effectively use these historical data, integration of legacy systems, become a hot spot of integration field. In this paper, how to effectively address heterogeneity of data distribution, to achieve customer access, while maintaining the autonomy of the local system for the objectives of heterogeneous database integration middleware based on Web Services solutions.Applications show that middleware solution has certain feasibility and practicality.

A New Bidirectional Method for Ontologies Matching

Recently, much research has focused on developing techniques for schema/ontology matching and mapping as it is required in many areas e.g. heterogeneous database integration, merging of ontologies, semantic query processing. In this paper, we present a novel method to detect and repair the list of homologs concepts; this last is based on the bidirectional comparison (Checking) between the two matched ontologies to filter this list of concepts. The used measures are classical just to show the reliability and realisability of our method, but we can generalize it for supporting other advanced measures.

Local Schemas Modifications Propagation and Maintenance of Metadata in Multidatabase System

of the challenging problems in the multidatabase systems is to find the most viable solution to the problem of interoperability of distributed heterogeneous autonomous local component databases. This has resulted in the creation of a global schema over set of local component database schemas to provide a uniform representation of local schemas. The main objective of this paper is to maintain the Global Schema and the Global Directory/Dictionary/Metadata as the local schemas are autonomous and evolve over time. In this paper we consider uniform object-oriented data models which is used during integration of different heterogeneous distributed databases from different data models and proposed a framework to maintain an objected-oriented Global Schema in the multidatabase system. The Bottom up local schema modifications propagation in the Global schema is proposed and during this process the Global Directory/Dictionary/Metadata is maintained without manual intervention.

Exploring models for semantic category verification

Many artificial intelligence tasks, such as automated question answering, reasoning, or heterogeneous database integration, involve verification of a semantic category (e.g. “coffee” is a drink, “red” is a color, while “steak” is not a drink and “big” is not a color). In this research, we explore completely automated on-the-fly verification of a membership in any arbitrary category which has not been expected a priori. Our approach does not rely on any manually codified knowledge (such as WordNet or Wikipedia) but instead capitalizes on the diversity of topics and word usage on the World Wide Web, thus can be considered “knowledge-light” and complementary to the “knowledge-intensive” approaches. We have created a quantitative verification model and established (1) what specific variables are important and (2) what ranges and upper limits of accuracy are attainable. While our semantic verification algorithm is entirely self-contained (not involving any previously reported components that are beyond the scope of this paper), we have tested it empirically within our fact seeking engine on the well known TREC conference test questions. Due to our implementation of semantic verification, the answer accuracy has improved by up to 16% depending on the specific models and metrics used.

A construction schema for provincial spatial database of China

In order to provide a provincial spatial database, this paper presents a scheme for spatial database construction to meet the needs of China. The objective and overall technical route of spatial database construction are described. The logical and physical database models are designed. Key issues are addressed, such as integration of multi-scale heterogeneous spatial databases, spatial data version management based on metadata and integrative management of map cartography and spatial database.

A Grid-Based Model for Integration of Distributed Medical Databases

Grid has emerged recently as an integration infrastructure for sharing and coordinated use of diverse resources in dynamic, distributed environment. In this paper, we present a prototype system for integration of heterogeneous medical databases based on Grid technology, which can provide a uniform access interface and efficient query mechanism to different medical databases. After presenting the architecture of the prototype system that employs corresponding Grid services and middleware technologies, we make an analysis on its basic functional components including OGSA-DAI, metadata model, transaction management, and query processing in detail, which cooperate with each other to enable uniform accessing and seamless integration of the underlying heterogeneous medical databases. Then, we test effectiveness and performance of the system through a query instance, analyze the experiment result, and make a discussion on some issues relating to practical medical applications. Although the prototype system has been carried out and tested in a simulated hospital information environment at present, the underlying principles are applicable to practical applications.