Two-fold Semantic Web service matchmaking – applying ontology mapping for service discovery

Semantic Web Services (SWS) aim at the automated discovery and orchestration of Web services on the basis of comprehensive, machine-interpretable semantic descriptions. Since SWS annotations usually are created by distinct SWS providers, semantic-level mediation, i.e. mediation between concurrent semantic representations, is a key requirement for SWS discovery. Since semantic-level mediation aims at enabling interoperability across heterogeneous semantic representations, it can be perceived as a particular instantiation of the ontology mapping problem. While recent SWS matchmakers usually rely on manual alignments or subscription to a common ontology, we propose a two-fold SWS matchmaking approach, consisting of (a) a general-purpose semantic-level mediator and (b) comparison and matchmaking of SWS capabilities. Our semantic-level mediation approach enables the implicit representation of similarities across distinct SWS by grounding service descriptions in so-called Mediation Spaces (MS). Given a set of SWS and their respective grounding, a SWS matchmaker automatically computes instance similarities across distinct SWS ontologies and matches the request to the most suitable SWS. A prototypical application illustrates our approach

Multi-stakeholder involvement and urban green space performance

This study aimed to identify the main factors influencing urban green space performance. Therefore, a conceptual framework on the relations of multi-stakeholder involvement (MSI) and the performance was conducted by a mixed-method approach. The study covered all urban green space projects (UGSPs) published in international journals as its population which were obtained from three main databases: ISI Web of Knowledge, Scopus and Picarta. Using a few combinations of keywords, 29 relevant journals were identified, which included 42 UGSPs as the main units of analysis in this study. A content analysis was used to determine the contribution of MSI to the performance of urban green space. The main internal (state, private, society, planning/design, implementation, maintenance, input for management, and financial support) and external (regulation, good leadership and financial support) MSI indicators were further identified. The findings showed that the main indicators that significantly influence urban green space performance are 'state, society, implementation and regulation'. The study concluded that the state plays a critical role in the UGSPs' performance although it is not the only actor. The influential role of the state and society should also be considered since most of green space projects are non-profit oriented. 'Society' involvement also contributes to the performance and 'regulation' is also needed as a legal basis for green space development and management. To validate the conceptual framework and mixed-method approach developed here, it is recommended that more studies should be conducted to compare the relationship of the MSI and the UGSPs' performance in different categories

Conceptual Spaces in Object-Oriented Framework

The aim of this paper is to show that the middle level of mental representations in a conceptual spaces framework is consistent with the OOP paradigm. We argue that conceptual spaces framework together with vague prototype theory of categorization appears to be the most suitable solution for modeling the cognitive apparatus of humans, and that the OOP paradigm can be easily and intuitively reconciled with this framework. First, we show that the prototypebased OOP approach is consistent with Gärdenfors’ model in terms of structural coherence. Second, we argue that the product of cloning process in a prototype-based model is in line with the structure of categories in Gärdenfors’ proposal. Finally, in order to make the fuzzy object-oriented model consistent with conceptual space, we demonstrate how to define membership function in a more cognitive manner, i.e. in terms of similarity to prototype

Semantic business process management: a vision towards using semantic web services for business process management

Business process management (BPM) is the approach to manage the execution of IT-supported business operations from a business expert's view rather than from a technical perspective. However, the degree of mechanization in BPM is still very limited, creating inertia in the necessary evolution and dynamics of business processes, and BPM does not provide a truly unified view on the process space of an organization. We trace back the problem of mechanization of BPM to an ontological one, i.e. the lack of machine-accessible semantics, and argue that the modeling constructs of semantic Web services frameworks, especially WSMO, are a natural fit to creating such a representation. As a consequence, we propose to combine SWS and BPM and create one consolidated technology, which we call semantic business process management (SBPM

A study of effective evaluation models and practices for technology supported physical learning spaces (JELS)

The aim of the JELS project was to identify and review the tools, methods and frameworks used to evaluate technology supported or enhanced physical learning spaces. A key objective was to develop the sector knowledgebase on innovation and emerging practice in the evaluation of learning spaces, identifying innovative methods and approaches beyond traditional post-occupancy evaluations and surveys that have dominated this area to date. The intention was that the frameworks and guidelines discovered or developed from this study could inform all stages of the process of implementing a technology supported physical learning space. The study was primarily targeted at the UK HE sector and the FE sector where appropriate, and ran from September 2008 to March 2009

Evaluation of Public Housing Programmes in Nigeria: A Theoretical and Conceptual Approach

The aim of this paper is to develop and test a theoretical and conceptual framework for an alternative approach to evaluation of public housing programmes in Nigeria. It seeks to address limitations of existing approaches where one theory or discipline has the upper hand in evaluating public housing programmes. This paper proposes a broad-based framework for assessing relationships between input, output and outcomes of public housing programmes through a realistic approach to evaluation based on objective-oriented theory, theory-driven evaluation paradigm and conceptual issues. This approach allows for the use of logical framework to explain the complex connections between underlying programme theory and outcomes. The distinct features of this alternative evaluation approach include: an open-ended evaluation approach; housing providers and residents participation; broad-based and a multi-faceted data gathering approaches and analysis in distinguishing the outcome of different housing delivery strategies in public housing programmes

Discovering information flow using a high dimensional conceptual space

This paper presents an informational inference mechanism realized via the use of a high dimensional conceptual space. More specifically, we claim to have operationalized important aspects of G?rdenforss recent three-level cognitive model. The connectionist level is primed with the Hyperspace Analogue to Language (HAL) algorithm which produces vector representations for use at the conceptual level. We show how inference at the symbolic level can be implemented by employing Barwise and Seligmans theory of information flow. This article also features heuristics for enhancing HAL-based representations via the use of quality properties, determining concept inclusion and computing concept composition. The worth of these heuristics in underpinning informational inference are demonstrated via a series of experiments. These experiments, though small in scale, show that informational inference proposed in this article has a very different character to the semantic associations produced by the Minkowski distance metric and concept similarity computed via the cosine coefficient. In short, informational inference generally uncovers concepts that are carried, or, in some cases, implied by another concept, (or combination of concepts)