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

ONTOLOGY-BASED SYSTEM DEVELOPMENT FOR MEDICAL DATABASE ACCESS

Medical research is a complex multi-disciplinary task involving specialists from different fields and professions, not only medical professionals. Medical databases are structured by information technology experts, but the contents must be tailored to the medical field. When the medical staff defines the information they use, terminology from their particular field of expertise is employed. This leads to misunderstandings between the maintainers and developers of information technology solutions, and the users of those solutions. When the time comes that a user, who is a medical professional, requires very specific data from the database, the chance of obtaining the data incorrectly is very high. By defining specific concepts and relationships between the data, in an explicit shared specification, some of the above problems can be avoided. The developed ontology-based data access system, described in this paper, provides a tool to store, manage and use definitions of common terminology and their mappings to the database. It is also capable of reasoning about the relationships between terms and indicates inconsistencies of term definitions, if any are present. By defining these interconnected terms in the ontology and by working through the system, all experts and software tools, who use the data, are able to use and reuse these terms to obtain data in a reliable and predefined way. This paper discusses the development and implementation of the ontology-based data access system, the ontology describing the medical data and the data mapping system, linking data from the database to concepts and virtual ontology individuals

The Bag Semantics of Ontology-Based Data Access

Ontology-based data access (OBDA) is a popular approach for integrating and querying multiple data sources by means of a shared ontology. The ontology is linked to the sources using mappings, which assign views over the data to ontology predicates. Motivated by the need for OBDA systems supporting database-style aggregate queries, we propose a bag semantics for OBDA, where duplicate tuples in the views defined by the mappings are retained, as is the case in standard databases. We show that bag semantics makes conjunctive query answering in OBDA coNP-hard in data complexity. To regain tractability, we consider a rather general class of queries and show its rewritability to a generalisation of the relational calculus to bags

Ontology-based data access to Slegge

We report on our experience in ontology-based data access to the Slegge database at Statoil and share the resources employed in this use case: end-user information needs (in natural language), their translations into SPARQL, the Subsurface Exploration Ontology, the schema of the Slegge database with integrity constraints, and the mappings connecting the ontology and the schema

Circuit Complexity Meets Ontology-Based Data Access

Ontology-based data access is an approach to organizing access to a database augmented with a logical theory. In this approach query answering proceeds through a reformulation of a given query into a new one which can be answered without any use of theory. Thus the problem reduces to the standard database setting. However, the size of the query may increase substantially during the reformulation. In this survey we review a recently developed framework on proving lower and upper bounds on the size of this reformulation by employing methods and results from Boolean circuit complexity.Comment: To appear in proceedings of CSR 2015, LNCS 9139, Springe

Ontology-based data access with databases: a short course

Ontology-based data access (OBDA) is regarded as a key ingredient of the new generation of information systems. In the OBDA paradigm, an ontology defines a high-level global schema of (already existing) data sources and provides a vocabulary for user queries. An OBDA system rewrites such queries and ontologies into the vocabulary of the data sources and then delegates the actual query evaluation to a suitable query answering system such as a relational database management system or a datalog engine. In this chapter, we mainly focus on OBDA with the ontology language OWL 2QL, one of the three profiles of the W3C standard Web Ontology Language OWL 2, and relational databases, although other possible languages will also be discussed. We consider different types of conjunctive query rewriting and their succinctness, different architectures of OBDA systems, and give an overview of the OBDA system Ontop

Inconsistency-tolerant Query Answering in Ontology-based Data Access

Ontology-based data access (OBDA) is receiving great attention as a new paradigm for managing information systems through semantic technologies. According to this paradigm, a Description Logic ontology provides an abstract and formal representation of the domain of interest to the information system, and is used as a sophisticated schema for accessing the data and formulating queries over them. In this paper, we address the problem of dealing with inconsistencies in OBDA. Our general goal is both to study DL semantical frameworks that are inconsistency-tolerant, and to devise techniques for answering unions of conjunctive queries under such inconsistency-tolerant semantics. Our work is inspired by the approaches to consistent query answering in databases, which are based on the idea of living with inconsistencies in the database, but trying to obtain only consistent information during query answering, by relying on the notion of database repair. We first adapt the notion of database repair to our context, and show that, according to such a notion, inconsistency-tolerant query answering is intractable, even for very simple DLs. Therefore, we propose a different repair-based semantics, with the goal of reaching a good compromise between the expressive power of the semantics and the computational complexity of inconsistency-tolerant query answering. Indeed, we show that query answering under the new semantics is first-order rewritable in OBDA, even if the ontology is expressed in one of the most expressive members of the DL-Lite family

Teaching an RDBMS about ontological constraints

International audienceIn the presence of an ontology, query answers must reflect not only data explicitly present in the database, but also implicit data, which holds due to the ontology, even though it is not present in the database. A large and useful set of ontology languages enjoys FOL reducibility of query answering: answering a query can be reduced to evaluating a certain first-order logic (FOL) formula (obtained from the query and ontology) against only the explicit facts. We present a novel query optimization framework for ontology-based data access settings enjoying FOL reducibility. Our framework is based on searching within a set of alternative equivalent FOL queries, i.e., FOL reformulations, one with minimal evaluation cost when evaluated through a relational database system. We apply this framework to the DL-LiteR Description Logic underpinning the W3C's OWL2 QL ontology language, and demonstrate through experiments its performance benefits when two leading SQL systems, one open-source and one commercial, are used for evaluating the FOL query reformulations