Using ontologies to synchronize change in relational database systems

Ontology is a building block of the semantic Web. Ontology building requires a detailed domain analysis, which in turn requires financial resources, intensive domain knowledge and time. Domain models in industry are frequently stored as relational database schemas in relational databases. An ontology base underlying such schemas can represent concepts and relationships that are present in the domain of discourse. However, with ever increasing demand for wider access and domain coverage, public databases are not static and their schemas evolve over time. Ontologies generated according to these databases have to change to reflect the new situation. Once a database schema is changed, these changes in the schema should also be incorporated in any ontology generated from the database. It is not possible to generate a fresh version of the ontology using the new database schema because the ontology itself may have undergone changes that need to be preserved. To tackle this problem, this paper presents a generic framework that will help to generate and synchronize ontologies with existing data sources. In particular we address the translation between ontologies and database schemas, but our proposal is also sufficiently generic to be used to generate and maintain ontologies based on XML and object oriented databases

Development of dynamic database structures using OWL ontologies

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.Includes bibliographical references (leaves 22-23).Standard query language database systems cannot provide the level of flexibility and functionality needed to store all of the data that a modem biologist requires. OWL ontologies provide much more information about how fields relate to each other including adding annotations with each field, but do not allow for the storage of mass amounts of data. By integrating OWL ontologies with modem database systems, scientists will be able to build ontology-based databases that combine the ease of development of ontologies with the power of the modem database. In addition, other scientists can now search ontology-based databases and know that even though the databases are different, the types of data are the same because they are based on a consistent ontology. The use of ontologies in building modem databases will create a new environment where users can customize databases to account for new methods in biology, while at the same time maintaining the ability for others to effectively search the modified databases.by Kurt R. Stiehl.S.B

1st INCF Workshop on Sustainability of Neuroscience Databases

The goal of the workshop was to discuss issues related to the sustainability of neuroscience databases, identify problems and propose solutions, and formulate recommendations to the INCF. The report summarizes the discussions of invited participants from the neuroinformatics community as well as from other disciplines where sustainability issues have already been approached. The recommendations for the INCF involve rating, ranking, and supporting database sustainability

Business intelligence and contribution of entrepreneurial information architecture

We are witnessing the need for a quick and intelligent reaction from organizations to the level and speed of change in business processes. The arising problems can be: from wrong lasting information; systems not fully used or explored; slow reaction to change; etc. This requires two main confluent action methods: people to synchronize their visions, ideas and strategies in the whole organization; and, in that context, select the information that strictly answers to the performance factors at the right moment. The proposed methodology turns to the potential of approach to the entrepreneurial architecture as well as to the potential of the information system in order to integrate the data and resources needed for that performance. The modeling of an information architecture of the company and its business helps in the identification of critical information, the one which is according to the mission, prospects and business success factors

Semantic Integration of Identity Data Repositories

With the continuously growing number of distributed and heterogeneous IT systems there is the need for structured and efficient identity management (IdM) processes. This implies that new users are created once and then the information is distributed to all applicable software systems same as if changes on existing user objects occur. The central issue is that there is no generally ac-cepted standard for handling this information distribution because each system has its own internal representation of this data. Our approach is to give a se-mantic definition of the digital user objects attributes to ease the mapping process of an abstract user object to the concrete instantiation of each software system. Therefore we created an ontology to define the mapping of users at-tributes as well as an architecture which enables the semantic integration of identity data repositories. Our solution has been tested in an implementation case study

Ontology-Based Resolution of Cloud Data Lock-in Problem

Cloud computing is nowadays becoming a popular paradigm for the provision of computing infrastructure that enables organizations to achieve financial savings. On the other hand, there are some known obstacles, among which vendor lock-in stands out. Furthermore, due to missing standards and heterogeneities of cloud storage systems, the migration of data to alternative cloud providers is expensive and time-consuming. We propose an approach based on Semantic Web services and AI planning to tackle cloud vendor data lock-in problem. To complete the mentioned task, data structures and data type mapping rules between different types of cloud storage systems are defined. The migration of data among different providers of platform as a service is presented in order to prove the practical applicability of the proposed approach. Additionally, this concept was also applied to software as a service model of cloud computing to perform one-shot data migration from Zoho CRM to Salesforce CRM