Development of a Logic Layer in the Semantic Web: Research Issues

The ontology layer of the semantic web is now mature enough (i.e. standards like RDF, RDFs, OWL, OWL 2) and the next step is to work on a logic layer for the development of advanced reasoning capabilities for knowledge extraction and efficient decision making. Adding logic to the web means using rules to make inferences. Rules are a means of expressing business processes, policies, contracts etc but most of the studies have focused on the use of monotonic logics in layered development of the semantic web which provides no mechanism for representing or handling incomplete or contradictory information respectively. This paper discusses argumentation, semantic web and defeasible logic programming with their distinct features and identifies the different research issues that need to be addressed in order to realize defeasible argumentative reasoning in the semantic web applications

SAM-SoS: A stochastic software architecture modeling and verification approach for complex System-of-Systems

A System-of-Systems (SoS) is a complex, dynamic system whose Constituent Systems (CSs) are not known precisely at design time, and the environment in which they operate is uncertain. SoS behavior is unpredictable due to underlying architectural characteristics such as autonomy and independence. Although the stochastic composition of CSs is vital to achieving SoS missions, their unknown behaviors and impact on system properties are unavoidable. Moreover, unknown conditions and volatility have significant effects on crucial Quality Attributes (QAs) such as performance, reliability and security. Hence, the structure and behavior of a SoS must be modeled and validated quantitatively to foresee any potential impact on the properties critical for achieving the missions. Current modeling approaches lack the essential syntax and semantics required to model and verify SoS behaviors at design time and cannot offer alternative design choices for better design decisions. Therefore, the majority of existing techniques fail to provide qualitative and quantitative verification of SoS architecture models. Consequently, we have proposed an approach to model and verify Non-Deterministic (ND) SoS in advance by extending the current algebraic notations for the formal models as a hybrid stochastic formalism to specify and reason architectural elements with the required semantics. A formal stochastic model is developed using a hybrid approach for architectural descriptions of SoS with behavioral constraints. Through a model-driven approach, stochastic models are then translated into PRISM using formal verification rules. The effectiveness of the approach has been tested with an end-to-end case study design of an emergency response SoS for dealing with a fire situation. Architectural analysis is conducted on the stochastic model, using various qualitative and quantitative measures for SoS missions. Experimental results reveal critical aspects of SoS architecture model that facilitate better achievement of missions and QAs with improved design, using the proposed approach

A defeasible logic programming-based framework to support argumentation in Semantic Web applications

Using ontologies, the SemanticWeb provides structure and meaning to the vast amount of available information on the World WideWeb (WWW) and enables machines and/or computers to utilize, process, reason and discover knowledge from it. The logic layer of the Semantic Web stack provides a set of logic-based rule languages to perform automated reasoning over such information, produce results and assist the decision maker in the decision making process. Initial efforts in the literature for reasoning in Semantic Web applications have focused on the use of monotonic logic. However such efforts lack the capability to represent and reason when the underlying information is incomplete and/or contradictory.To overcome this problem, defeasible reasoning-based Semantic Web applications have been proposed that are capable of representing and reasoning over incomplete and/or contradictory information after defining the priorities between them. However their drawback is that they can only represent and reason over information coming from a single source. In scenarios where the decision maker is interested in considering information from multiple sources (such as information from collaborating enterprises or the feedback from customers) and where such information is incomplete and/or contradictory, current Semantic Web-based approaches do not provide any solution to represent, reason, resolve conflicts and integrate it to assist in the decision making process. This is in contrast to the approaches proposed in the literature in Artificial intelligence, where argumentation formalisms have been used to reason over contradictory information and produce a justifiable, tractable conclusion.Therefore, to overcome such limitations in the Semantic Web discussed above, in this thesis a generic defeasible logic programming-based framework is proposed to support argumentation in Semantic Web applications (GF@SWA). GF@SWA enables Semantic Web applications to represent both structured and unstructured information and/or translate the existing information into a defeasible logic programming (DeLP) format, perform hybrid reasoning for arguments construction, identify and resolve conflicts among arguments, integrate them and produce their graphical representation in the form of reasoning chains. The GF@SWA also provides a solution to integrate the reasoning chains produced by different Semantic Web applications and assists the decision maker in the decision making process. For validation and evaluation of GF@SWA, three Semantic Web applications are developed using GF@SWA to provide decision support to an enterprise to achieve business intelligence. The functionality and features of each Semantic Web application are validated and evaluated to highlight the effectiveness of GF@SWA in addressing the decision making requirements of an enterprise

Rule-based business policies specification, reasoning and integration for business process model extraction

Business policies are pervasive in web-based information systems and the introduction of the semantic web has opened new fertile horizons for their representation and automated processing. However, a number of challenges have also emerged. One of those challenges is the contradictory information detection and resolution among policies. This papers reports on a semantic, knowledge-based approach for business policies representation, conflict detection and argumentation based resolution, leading to a justifiable conclusion. We also propose an architecture for enterprise-wide information system to integrate business policies about a given subject spanning across different information systems in an enterprise for decision making purposes

Web@IDSS – Argumentation-enabled Web-based IDSS for reasoning over incomplete and conflicting information

Over the past few decades, there has been a resurgence of interest in using high-level software intelligence for business intelligence (BI). The objective is to produce actionable information that is delivered at the right time, easily comprehendible and exportable to other software to assist business decisionmaking processes. Although the design and development of decision support systems (DSS) has been carried out for over 40 years, DSS still suffer from many limitations such as poor maintainability, poor flexibility and less reusability. The development of the Internet and WWW has helped information systems to overcome those limitations and Web DSS is now an active area of research in business intelligence,impacting significantly on the way information is exchanged and businesses are conducted. However, to remain competitive, companies rely on business intelligence (BI) to continually monitor and analyze the operating environment (both internal and external), to identify potential risks, and to devise competitive business strategies. However, the current Web DSS applications are not able to reason over information present across organizational boundaries which could be incomplete and conflicting. The use of an argumentation-based mechanism has not been explored to address such shortcomings in Web DSS. Argumentationis a kind of commonsense reasoning used by human beings to reach a justifiable conclusionwhen available information is incomplete and/or inconsistent among participants.In this paper, we propose and elaborate in detail a conceptual framework and formal argumentation-based semantics for Web enabled Intelligent DSS (Web@IDSS). We evaluate the use of argumentative reasoning in Web DSS with the help of a case study, prototype development and future directions. Applications built according to the proposed framework will provide more practical, understandable results to decision makers

Defeasible reasoning based argumentative web-IDSS for Virtual Team (VT)

The Web-based intelligent decision support system (Web-IDSS) is pivotal for a Virtual Team (VT) to successfully execute business-related tasks. The current generation of Web-IDSS built on top of semantic web technologies for VT lacks the capability to provide decision support when underlying information is incomplete and/or contradictory. In this article, we address this limitation of current Web-IDSS through defeasible logic based argumentation formalism. The proposed Web-IDSS uses a hybrid reasoning approach: forward chaining (data-driven) for the construction of arguments over incomplete information, and backward chaining (goal-driven) for conflict identification and resolution with explanation. The proposed Web-IDSS adheres to web standards and publishes the outcome of argumentative reasoning in Argument Interchange Format (AIF)