Uniformly Integrated Database Approach for Heterogenous Databases

The demands of more storage, scalability, commodity of heterogenous data for storing, analyzing and retrieving data are rapidly increasing in today data-centric area such as cloud computing, big data analytics, etc. These demands cannot be solely handled by relational database system (RDBMS) due to its strict relational model for scalability and adaptability. Therefore, NoSQL (Not only SQL) database called non-relational database is recently introduced to extend RDBMS, and now it is widely used in some software developments. As a result, it becomes challenges regarding how to transform relational to non-relational database or how to integrate them to achieve business purposes regarding storage and adaptability. This paper therefore proposes an approach for uniformly integrated database to integrate data separately extracted from individual database schema from relational and NoSQL database systems. We firstly try to map the data elements in terms of their semantic meaning and structures with the help of ontological semantic mapping and metamodeling from the extracted data. We then cover structural, semantical and syntactical diversity of each database schema and produce integrated database results. To prove efficiency and usefulness of our proposed system, we test our developed system with popular datasets in BSON and traditional sql format using MongoDB and MySQL database. According to the results compared with other proficient contemporary approaches, we have achieved significant results in mapping similarity results although running time and retrieval time are competitive with the others

Modified Query-Roles Based Access Control Model (Q-RBAC) for Interactive Access of Ontology Data

The data access model plays an important role during accessing and querying the stored data from the database. It provides an access right and authorization of accessing data into a database. It can distinguish the access boundaries between the administrators and the users where the database administrators can create certain policies either from the client application side or directly from the database side, depending upon the nature of running application. However, the emerging technology on the ontology repository has forced some database developers to adapt most of the access policies from the traditional database system and many of the policies were inherited from the relational database. This method of adopting or borrowing access policies from other storage system has created an unnecessary layer between the ontology repository and database. Most of the emerging ontology repositories lack an independent access model that provides or distinguishes access right between the administrators and users or between the ontology data. This paper proposed the improved access layer from the ontology repository with an additional users’ policy creation layer that will lead to increase data security and also increase the performance of querying data. Our effort relies on re-modifying the role based access control model from the traditional one to the new proposed model that organized by the rich users’ policies and perfect query rewriting layer. Although it is associated with query module, the proposed model has an additional security layer to restrict unauthorized users from accessing stored data in order to improve querying and data access performance Keywords: Access methods, Access control, Rule based access control model. Oracle NoSQL database, Virtual data layer, Ontology Query

A Survey of Semantic Integration Approaches in Bioinformatics

Technological advances of computer science and data analysis are helping to provide continuously huge volumes of biological data, which are available on the web. Such advances involve and require powerful techniques for data integration to extract pertinent knowledge and information for a specific question. Biomedical exploration of these big data often requires the use of complex queries across multiple autonomous, heterogeneous and distributed data sources. Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontology. We provide a survey of some approaches and techniques for integrating biological data, we focus on those developed in the ontology community

On the Potential Integration of an Ontology-Based Data Access Approach in NoSQL Stores

International audienceNo SQL stores are emerging as an efficient alternative to relational database management systems in the context of big data. Many actors in this domain consider that to gain a wider adoption, several extensions have to be integrated. Some of them focus on the ways of proposing more schema, supporting adapted declarative query languages and providing integrity constraints in order to control data consistency and enhance data quality. We consider that these issues can be dealt with in the context of Ontology Based Data Access (OBDA). OBDA is a new data management paradigm that exploits the semantic knowledge represented in ontologies when querying data stored in a database. We provide a proof of concept of OBDA's ability to tackle these three issues in a social application related to the medical domain

On The Potential Integration of an Ontology-Based Data Access Approach in NoSQL Stores

International audienc

On the Potential Integration of an Ontology-Based Data Access Approach in NoSQL Stores

International audienceNo SQL stores are emerging as an efficient alternative to relational database management systems in the context of big data. Many actors in this domain consider that to gain a wider adoption, several extensions have to be integrated. Some of them focus on the ways of proposing more schema, supporting adapted declarative query languages and providing integrity constraints in order to control data consistency and enhance data quality. We consider that these issues can be dealt with in the context of Ontology Based Data Access (OBDA). OBDA is a new data management paradigm that exploits the semantic knowledge represented in ontologies when querying data stored in a database. We provide a proof of concept of OBDA's ability to tackle these three issues in a social application related to the medical domain