Context as foundation for a semantic desktop

Adoption of semantic web technologies and principles presents an opportunity to change the conceptual model of desktop computing. Moving from a traditional position where the desktop is largely tied to a specific computational device, a semantic desktop could exist as a broad, networked space defined relative to the user. In this position paper we argue that personal, computing, and knowledge contexts are the appropriate means by which to define and shape the desktop space, and that collectively they provide the foundation for novel functionality in a semantic desktop

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

Detecting Mismatches between a User's and an Expert's Conceptualisations

The work presented in this paper is part of our ongoing research on applying commonsense reasoning to elicit and maintain models that represent users' conceptualisations. Such user models will enable taking into account the users' perspective of the world and will empower personalisation algorithms for the Semantic Web. A formal approach for detecting mismatches between a user's and an expert's conceptual model is outlined. The formalisation is used as the basis to develop algorithms to compare two conceptualisations defined in OWL. The algorithms are illustrated in a geographical domain using a space ontology developed at NASA, and have been tested by simulating possible user misconceptions

Assessment of socio-economic configuration of value chains : a proposed analysis framework to facilitate integration of small rural producers with global agribusiness

Value chain analysis is an important tool to assess and enhance the performance of agribusiness. This paper analyzes the empirical application of a conceptual framework known as the Rural Web to evaluate the socio-economic complexity of a specific agribusiness value chain. This can be used as a complementary approach to traditional value chain analysis. The proposed framework goes beyond linear descriptions of product flows and examines how supply chains are built, shaped and reproduced over time and space, while considering social, cultural, environmental and political aspects. The results demonstrate that the proposed framework is a suitable method for value chain analysis, principally for those whose early stages are based on small and medium-sized rural actors. The Rural Web analysis offers decision-makers a platform to identify key actors not traditionally considered in value chain analysis, as well as the social interrelationships that occur at different dimensions. It also enables the identification of corrective and preventive measures to enhance agribusiness value chains

Towards automated knowledge-based mapping between individual conceptualisations to empower personalisation of Geospatial Semantic Web

Geospatial domain is characterised by vagueness, especially in the semantic disambiguation of the concepts in the domain, which makes defining universally accepted geo- ontology an onerous task. This is compounded by the lack of appropriate methods and techniques where the individual semantic conceptualisations can be captured and compared to each other. With multiple user conceptualisations, efforts towards a reliable Geospatial Semantic Web, therefore, require personalisation where user diversity can be incorporated. The work presented in this paper is part of our ongoing research on applying commonsense reasoning to elicit and maintain models that represent users' conceptualisations. Such user models will enable taking into account the users' perspective of the real world and will empower personalisation algorithms for the Semantic Web. Intelligent information processing over the Semantic Web can be achieved if different conceptualisations can be integrated in a semantic environment and mismatches between different conceptualisations can be outlined. In this paper, a formal approach for detecting mismatches between a user's and an expert's conceptual model is outlined. The formalisation is used as the basis to develop algorithms to compare models defined in OWL. The algorithms are illustrated in a geographical domain using concepts from the SPACE ontology developed as part of the SWEET suite of ontologies for the Semantic Web by NASA, and are evaluated by comparing test cases of possible user misconceptions

Organising the knowledge space for software components

Software development has become a distributed, collaborative process based on the assembly of off-the-shelf and purpose-built components. The selection of software components from component repositories and the development of components for these repositories requires an accessible information infrastructure that allows the description and comparison of these components. General knowledge relating to software development is equally important in this context as knowledge concerning the application domain of the software. Both form two pillars on which the structural and behavioural properties of software components can be addressed. Form, effect, and intention are the essential aspects of process-based knowledge representation with behaviour as a primary property. We investigate how this information space for software components can be organised in order to facilitate the required taxonomy, thesaurus, conceptual model, and logical framework functions. Focal point is an axiomatised ontology that, in addition to the usual static view on knowledge, also intrinsically addresses the dynamics, i.e. the behaviour of software. Modal logics are central here – providing a bridge between classical (static) knowledge representation approaches and behaviour and process description and classification. We relate our discussion to the Web context, looking at Web services as components and the Semantic Web as the knowledge representation framewor

A Tool for Supporting Conceptual Design of Multiple State Mechanical Devices

Research into conceptual design of mechanical systems has evolved as an area of interest since last few decades. Conceptual design plays a significant role as an early stage of design to produce designs with higher quality by economically exploring a larger solution space. Several attempts have been made by researchers to automate the conceptual design synthesis process using computer support. However, most of that work has been focused on single state design problems. This paper deals with multiple state mechanical design problems and proposes a systematic method for synthesizing a larger solution space. A web-based tool is developed to guide designers through the step-by-step synthesis process by providing automated retrieval of initial solution proposals and modification rules

Four Lessons in Versatility or How Query Languages Adapt to the Web

Exposing not only human-centered information, but machine-processable data on the Web is one of the commonalities of recent Web trends. It has enabled a new kind of applications and businesses where the data is used in ways not foreseen by the data providers. Yet this exposition has fractured the Web into islands of data, each in different Web formats: Some providers choose XML, others RDF, again others JSON or OWL, for their data, even in similar domains. This fracturing stifles innovation as application builders have to cope not only with one Web stack (e.g., XML technology) but with several ones, each of considerable complexity. With Xcerpt we have developed a rule- and pattern based query language that aims to give shield application builders from much of this complexity: In a single query language XML and RDF data can be accessed, processed, combined, and re-published. Though the need for combined access to XML and RDF data has been recognized in previous work (including the W3C’s GRDDL), our approach differs in four main aspects: (1) We provide a single language (rather than two separate or embedded languages), thus minimizing the conceptual overhead of dealing with disparate data formats. (2) Both the declarative (logic-based) and the operational semantics are unified in that they apply for querying XML and RDF in the same way. (3) We show that the resulting query language can be implemented reusing traditional database technology, if desirable. Nevertheless, we also give a unified evaluation approach based on interval labelings of graphs that is at least as fast as existing approaches for tree-shaped XML data, yet provides linear time and space querying also for many RDF graphs. We believe that Web query languages are the right tool for declarative data access in Web applications and that Xcerpt is a significant step towards a more convenient, yet highly efficient data access in a “Web of Data”

Blending the physical and the digital through conceptual spaces

The rise of the Internet facilitates an ever increasing growth of virtual, i.e. digital spaces which co-exist with the physical environment, i.e. the physical space. In that, the question arises, how physical and digital space can interact synchronously. While sensors provide a means to continuously observe the physical space, several issues arise with respect to mapping sensor data streams to digital spaces, for instance, structured linked data, formally represented through symbolic Semantic Web (SW) standards such as OWL or RDF. The challenge is to bridge between symbolic knowledge representations and the measured data collected by sensors. In particular, one needs to map a given set of arbitrary sensor data to a particular set of symbolic knowledge representations, e.g. ontology instances. This task is particularly challenging due to the vast variety of possible sensor measurements. Conceptual Spaces (CS) provide a means to represent knowledge in geometrical vector spaces in order to enable computation of similarities between knowledge entities by means of distance metrics. We propose an approach which allows to refine symbolic concepts as CS and to ground ontology instances to so-called prototypical members which are vectors in the CS. By computing similarities in terms of spatial distances between a given set of sensor measurements and a finite set of CS members, the most similar instance can be identified. In that, we provide a means to bridge between the physical space, as observed by sensors, and the digital space made up of symbolic representations