Relational databases conceptual preservation

Previously, a neutral format was adopted to pursue the goal of platform independence and to achieve a standard format in the digital preservation of relational databases, both data and structure (logical model). Currently, we intend to address the preservation of relational databases by focusing on the conceptual model of the database, considering the database semantics as an important preservation ”property”. For the representation of this higher level of abstraction present in databases we use an ontology based approach. At this higher abstraction level exists inherent Knowledge associated to the database semantics that we tentatively represent using ”Web Ontology Language” (OWL). We developed a prototype (supported by case study) and define a mapping algorithm for the conversion between the database and OWL

Using ontologies in database preservation

This paper addresses the problematic Digital Preservation and focuses on the conceptual model within a specific class of digital objects: Relational Databases. Previously, a neutral format was adopted to pursue the goal of platform independence and to achieve a standard format in the digital preservation of relational databases, both data and structure (logical model). Currently, in this project, we intend to address the preservation of relational databases by focusing on the conceptual model of the database, considering the database semantics as an impor- tant preservation ”property”. For the representation of this higher level of abstraction present in databases we use an ontology based approach. At this higher abstraction level exists inherent Knowledge associated to the database semantics that we tentatively represent using ”Web Ontol- ogy Language” (OWL). We developed a prototype (supported by case study) and define a mapping algorithm for the conversion between the database and OWL. The ontology approach is adopted to formalize the knowledge associated to the conceptual model of the database and also a methodology to create an abstract representation of it

Using ontologies to abstract relational databases conceptual model

This paper addresses the problematic Digital Preservation and focuses on the conceptual model within a specific class of digital objects: Relational Databases. Previously, a neutral format was adopted to pursue the goal of platform independence and to achieve a standard format in the digital preservation of relational databases, both data and structure (logical model). Currently, in this project, we intend to address the preservation of relational databases by focusing on the conceptual model of the database, considering the database semantics as an impor- tant preservation ”property”. For the representation of this higher level of abstraction present in databases we use an ontology based approach. At this higher abstraction level exists inherent Knowledge associated to the database semantics that we tentatively represent using ”Web Ontol- ogy Language” (OWL). We developed a prototype (supported by case study) and define a mapping algorithm for the conversion between the database and OWL. The ontology approach is adopted to formalize the knowledge associated to the conceptual model of the database and also a methodology to create an abstract representation of it

Reasoning with Data Flows and Policy Propagation Rules

Data-oriented systems and applications are at the centre of current developments of the World Wide Web. In these scenarios, assessing what policies propagate from the licenses of data sources to the output of a given data-intensive system is an important problem. Both policies and data flows can be described with Semantic Web languages. Although it is possible to define Policy Propagation Rules (PPR) by associating policies to data flow steps, this activity results in a huge number of rules to be stored and managed. In a recent paper, we introduced strategies for reducing the size of a PPR knowledge base by using an ontology of the possible relations between data objects, the Datanode ontology, and applying the (A)AAAA methodology, a knowledge engineering approach that exploits Formal Concept Analysis (FCA). In this article, we investigate whether this reasoning is feasible and how it can be performed. For this purpose, we study the impact of compressing a rule base associated with an inference mechanism on the performance of the reasoning process. Moreover, we report on an extension of the (A)AAAA methodology that includes a coherency check algorithm, that makes this reasoning possible. We show how this compression, in addition to being beneficial to the management of the knowledge base, also has a positive impact on the performance and resource requirements of the reasoning process for policy propagation

Greedy Algorithm for Inference of Decision Trees from Decision Rule Systems

Decision trees and decision rule systems play important roles as classifiers, knowledge representation tools, and algorithms. They are easily interpretable models for data analysis, making them widely used and studied in computer science. Understanding the relationships between these two models is an important task in this field. There are well-known methods for converting decision trees into systems of decision rules. In this paper, we consider the inverse transformation problem, which is not so simple. Instead of constructing an entire decision tree, our study focuses on a greedy polynomial time algorithm that simulates the operation of a decision tree on a given tuple of attribute values.Comment: arXiv admin note: substantial text overlap with arXiv:2305.01721, arXiv:2302.0706

Sharing e-Health information through ontological layering

e-Health information, including patient clinical and demographic data, is very often dispersed across various environments, which either generate them or retrieve them from different sources. Healthcare professionals often need related e-health information in order to obtain a more comprehensive picture of a patient's health status. There are many obstacles to retrieving information and data from heterogeneous sources. In this paper we show that our ontological layering helps in (a) classifying requests imposed by healthcare professionals when retrieving e-health information from heterogeneous sources and (b) resolving semantic heterogeneities across repositories and composing an adequate answer to issued requests. We use a layered software architectural model based on Generic ontology for Context-aware, Interoperable and Data sharing (Go- CID) software applications, applicable to e-Health environments. Ontological layering and reasoning have been demonstrated with semantic web technologies

Application independent in location tracking framework

Due to significant popularity of location-based services and multimedia communication over mobile devices, many researches have been conducted to extend the features of location tracking and make it cost effective to users. This research focuses on the performance of an indoor location tracking system on IPv6 network island with multiple real time applications that has location assisted session transfer feature for mobile users. Received signal strength Indicator mechanism has been used to locate the moving nodes. This research involved the development of location tracking server that monitors the dynamic and centralised MySQL database management system. Session initial protocols user agent has been used to deploy intercommunicating of multimedia data such as video and audio conference, text messaging among the moving nodes and users are able to transfer the multimedia sessions seamlessly to their nearest mobile nodes which will be determined by the location server. This study, thus, presents the variation of location tracking accuracy of triangulation system and fingerprint system on different indoor surroundings to compare the performance of their location tracking accuracy. Two indoor positioning systems, triangulation method (TM) and fingerprint method (FPM) were implemented and experiments were successfully conducted in different large area and small area scenarios of indoor environment. FPM experiments were examined into two sections: FPM database with data redundancy and FPM database without data redundancy. FPM database without data redundancy achieved 94.287% tracking accuracy which is the highest comparing to the FPM database with data redundancy and TM

Time and defeasibility in FIPA ACL semantics

AbstractInferences about speech acts are often conditional, non-monotonic, and involve the issue of time. Most agent communication languages, however, ignore these issues, due to the difficulty to combine them in a single formalism. This paper addresses such issues in defeasible logic, and shows how to express a semantics for ACLs in order to make non-monotonic inferences on the basis of speech acts