Supporting public decision making in policy deliberations: An ontological approach

This is the post-print version of the Paper. The official published version can be accessed from the link below - Copyright @ 2011 SpringerSupporting public decision making in policy deliberations has been a key objective of eParticipation which is an emerging area of eGovernment. EParticipation aims to enhance citizen involvement in public governance activities through the use of information and communication technologies. An innovative approach towards this objective is exploiting the potentials of semantic web technologies centred on conceptual knowledge models in the form of ontologies. Ontologies are generally defined as explicit human and computer shared views on the world of particular domains. In this paper, the potentials and benefits of using ontologies for policy deliberation processes are discussed. Previous work is then extended and synthesised to develop a deliberation ontology. The ontology aims to define the necessary semantics in order to structure and interrelate the stages and various activities of deliberation processes with legal information, participant stakeholders and their associated arguments. The practical implications of the proposed framework are illustrated.This work is funded by the European Commission under the 2006/1 eParticipation call

Semantic Interoperability Middleware – Enabling collaborative networks in public sector

Electronic Government initiatives, such as seamless public services delivered at one-stop government portals, require establishing collaborative networks among public- and private-sector organizations. However, semantic interoperability problems emerge as these organizations may differ in the terms and meanings they use to communicate, express their needs and describe resources they make available to each other. This paper describes typical semantic interoperability problems and presents a middleware solution to address them, called Semantic Interoperability Middleware (SIM). The paper illustrates the problems through three case studies in a collaborative network for the delivery of welfare benefits. Subsequently, the requirements for SIM are presented, and the architecture and design of the solution are specified using UML. SIM assumes organizations have agreed on ontologies that reflect the meaning of terms they use in communicating. It comprises three services: Mediation – resolves differences in terms and meaning; Validation – detects inconsistent terms and meaning; and Discovery – mediates and matches need with resource descriptions. Finally, the case studies are resolved applying SIM.Workshop de Ingeniería de Software y Bases de Datos (WISBD)Red de Universidades con Carreras en Informática (RedUNCI

IRS-III: A broker-based approach to semantic Web services

A factor limiting the take up of Web services is that all tasks associated with the creation of an application, for example, finding, composing, and resolving mismatches between Web services have to be carried out by a software developer. Semantic Web services is a combination of semantic Web and Web service technologies that promise to alleviate these problems. In this paper we describe IRS-III, a framework for creating and executing semantic Web services, which takes a semantic broker based approach to mediating between service requesters and service providers. We describe the overall approach and the components of IRS-III from an ontological and architectural viewpoint. We then illustrate our approach through an application in the eGovernment domain

An Intelligent Knowledge Management System from a Semantic Perspective

Knowledge Management Systems (KMS) are important tools by which organizations can better use information and, more importantly, manage knowledge. Unlike other strategies, knowledge management (KM) is difficult to define because it encompasses a range of concepts, management tasks, technologies, and organizational practices, all of which come under the umbrella of the information management. Semantic approaches allow easier and more efficient training, maintenance, and support knowledge. Current ICT markets are dominated by relational databases and document-centric information technologies, procedural algorithmic programming paradigms, and stack architecture. A key driver of global economic expansion in the coming decade is the build-out of broadband telecommunications and the deployment of intelligent services bundling. This paper introduces the main characteristics of an Intelligent Knowledge Management System as a multiagent system used in a Learning Control Problem (IKMSLCP), from a semantic perspective. We describe an intelligent KM framework, allowing the observer (a human agent) to learn from experience. This framework makes the system dynamic (flexible and adaptable) so it evolves, guaranteeing high levels of stability when performing his domain problem P. To capture by the agent who learn the control knowledge for solving a task-allocation problem, the control expert system uses at any time, an internal fuzzy knowledge model of the (business) process based on the last knowledge model.knowledge management, fuzzy control, semantic technologies, computational intelligence

Deploying Semantic Web Services-Based Applications in the e-Government Domain

Joining up services in e-Government usually implies governmental agencies acting in concert without a central control regime. This requires to the sharing scattered and heterogeneous data. Semantic Web Service (SWS) technology can help to integrate, mediate and reason between these datasets. However, since a few real-world applications have been developed, it is still unclear which are the actual benefits and issues of adopting such a technology in the e-Government domain. In this paper, we contribute to raising awareness of the potential benefits in the e-Government communityby analyzing motivations, requirements and expected results, before proposing a reusable SWS-based framework. We demonstrate the application of this framework by showing how integration and interoperability emerge from this model through a cooperative and multi-viewpoint methodology. Finally, we illustrate added values and lessons learned by two compelling case studies: a change of circumstances notification system and a GIS-based emergency planning system, and describe key challenges which remain to be addressed

Unidata's Common Data Model mapping to the ISO 19123 Data Model

Access to real-time distributed Earth and Space Science (ESS) information is essential for enabling critical Decision Support Systems (DSS). Thus, data model interoperability between the ESS and DSS communities is a decisive achievement for enabling cyber-infrastructure which aims to serve important societal benefit areas. The ESS community is characterized by a certain heterogeneity, as far as data models are concerned. Recent spatial data infrastructures implement international standards for the data model in order to achieve interoperability and extensibility. This paper presents well-accepted ESS data models, introducing a unified data model called the Common Data Model (CDM). CDM mapping into the corresponding elements of the international standard coverage data model of ISO 19123 is presented and discussed at the abstract level. The mapping of CDM scientific data types to the ISO coverage model is a first step toward interoperability of data systems. This mapping will provide the abstract framework that can be used to unify subsequent efforts to define appropriate conventions along with explicit agreed-upon encoding forms for each data type. As a valuable case in point, the content mapping rules for CDM grid data are discussed addressing a significant example

Semantic Interoperability Middleware – Enabling collaborative networks in public sector

Electronic Government initiatives, such as seamless public services delivered at one-stop government portals, require establishing collaborative networks among public- and private-sector organizations. However, semantic interoperability problems emerge as these organizations may differ in the terms and meanings they use to communicate, express their needs and describe resources they make available to each other. This paper describes typical semantic interoperability problems and presents a middleware solution to address them, called Semantic Interoperability Middleware (SIM). The paper illustrates the problems through three case studies in a collaborative network for the delivery of welfare benefits. Subsequently, the requirements for SIM are presented, and the architecture and design of the solution are specified using UML. SIM assumes organizations have agreed on ontologies that reflect the meaning of terms they use in communicating. It comprises three services: Mediation – resolves differences in terms and meaning; Validation – detects inconsistent terms and meaning; and Discovery – mediates and matches need with resource descriptions. Finally, the case studies are resolved applying SIM.Workshop de Ingeniería de Software y Bases de Datos (WISBD)Red de Universidades con Carreras en Informática (RedUNCI

An Intelligent Knowledge Management System from a Semantic Perspective

Knowledge Management Systems (KMS) are important tools by whichorganizations can better use information and, more importantly, manageknowledge. Unlike other strategies, knowledge management (KM) is difficult todefine because it encompasses a range of concepts, management tasks,technologies, and organizational practices, all of which come under the umbrella ofthe information management. Semantic approaches allow easier and more efficienttraining, maintenance, and support knowledge. Current ICT markets are dominatedby relational databases and document-centric information technologies, proceduralalgorithmic programming paradigms, and stack architecture. A key driver of globaleconomic expansion in the coming decade is the build-out of broadbandtelecommunications and the deployment of intelligent services bundling. This paperintroduces the main characteristics of an Intelligent Knowledge ManagementSystem as a multiagent system used in a Learning Control Problem (IKMSLCP),from a semantic perspective. We describe an intelligent KM framework, allowingthe observer (a human agent) to learn from experience. This framework makes thesystem dynamic (flexible and adaptable) so it evolves, guaranteeing high levels ofstability when performing his domain problem P. To capture by the agent who learnthe control knowledge for solving a task-allocation problem, the control expertsystem uses at any time, an internal fuzzy knowledge model of the (business)process based on the last knowledge model