Features for Killer Apps from a Semantic Web Perspective

There are certain features that that distinguish killer apps from other ordinary applications. This chapter examines those features in the context of the semantic web, in the hope that a better understanding of the characteristics of killer apps might encourage their consideration when developing semantic web applications. Killer apps are highly tranformative technologies that create new e-commerce venues and widespread patterns of behaviour. Information technology, generally, and the Web, in particular, have benefited from killer apps to create new networks of users and increase its value. The semantic web community on the other hand is still awaiting a killer app that proves the superiority of its technologies. The authors hope that this chapter will help to highlight some of the common ingredients of killer apps in e-commerce, and discuss how such applications might emerge in the semantic web

Knowledge society arguments revisited in the semantic technologies era

In the light of high profile governmental and international efforts to realise the knowledge society, I review the arguments made for and against it from a technology standpoint. I focus on advanced knowledge technologies with applications on a large scale and in open- ended environments like the World Wide Web and its ambitious extension, the Semantic Web. I argue for a greater role of social networks in a knowledge society and I explore the recent developments in mechanised trust, knowledge certification, and speculate on their blending with traditional societal institutions. These form the basis of a sketched roadmap for enabling technologies for a knowledge society

Graph-RAT: Combining data sources in music recommendation systems

The complexity of music recommendation systems has increased rapidly in recent years, drawing upon different sources of information: content analysis, web-mining, social tagging, etc. Unfortunately, the tools to scientifically evaluate such integrated systems are not readily available; nor are the base algorithms available. This article describes Graph-RAT (Graph-based Relational Analysis Toolkit), an open source toolkit that provides a framework for developing and evaluating novel hybrid systems. While this toolkit is designed for music recommendation, it has applications outside its discipline as well. An experiment—indicative of the sort of procedure that can be configured using the toolkit—is provided to illustrate its usefulness

A Survey of Semantic Metadata Management Models for the Social Web

12Social systems are a new generation of Web 2.0 applications, characterized by their primarily user-driven content and the ability to mediate personal and social information across communities, such as teams, communities, and organizations. The recent growth and adaptation of social systems for personal and social information management has created new opportunities for users to be producers as well as consumers of information. This paper aims at studying the different models that have been proposed to better connect resources, annotations and users and their usage in the social Web. The paper aims to answer questions like: \textit{What are the existing models that allow to semantically describe resources, users and tags in the social Web? What are the characteristics of such models? What are the differences between those models?} The final objective is to provide an understandable study and comparison of some of the existing models to help researchers, and developers, to make their decision whenever there is a need to use a semantic meta-data model in the social Web. More concretely, this work aims to be a reference guide for different professionals in order to accelerate the adoption of such technologies in the Social Web

Semantic modelling of user interests based on cross-folksonomy analysis

The continued increase in Web usage, in particular participation in folksonomies, reveals a trend towards a more dynamic and interactive Web where individuals can organise and share resources. Tagging has emerged as the de-facto standard for the organisation of such resources, providing a versatile and reactive knowledge management mechanism that users find easy to use and understand. It is common nowadays for users to have multiple profiles in various folksonomies, thus distributing their tagging activities. In this paper, we present a method for the automatic consolidation of user profiles across two popular social networking sites, and subsequent semantic modelling of their interests utilising Wikipedia as a multi-domain model. We evaluate how much can be learned from such sites, and in which domains the knowledge acquired is focussed. Results show that far richer interest profiles can be generated for users when multiple tag-clouds are combine

Internet based molecular collaborative and publishing tools

The scientific electronic publishing model has hitherto been an Internet based delivery of electronic articles that are essentially replicas of their paper counterparts. They contain little in the way of added semantics that may better expose the science, assist the peer review process and facilitate follow on collaborations, even though the enabling technologies have been around for some time and are mature. This thesis will examine the evolution of chemical electronic publishing over the past 15 years. It will illustrate, which the help of two frameworks, how publishers should be exploiting technologies to improve the semantics of chemical journal articles, namely their value added features and relationships with other chemical resources on the Web. The first framework is an early exemplar of structured and scalable electronic publishing where a Web content management system and a molecular database are integrated. It employs a test bed of articles from several RSC journals and supporting molecular coordinate and connectivity information. The value of converting 3D molecular expressions in chemical file formats, such as the MOL file, into more generic 3D graphics formats, such as Web3D, is assessed. This exemplar highlights the use of metadata management for bidirectional hyperlink maintenance in electronic publishing. The second framework repurposes this metadata management concept into a Semantic Web application called SemanticEye. SemanticEye demonstrates how relationships between chemical electronic articles and other chemical resources are established. It adapts the successful semantic model used for digital music metadata management by popular applications such as iTunes. Globally unique identifiers enable relationships to be established between articles and other resources on the Web and SemanticEye implements two: the Document Object Identifier (DOI) for articles and the IUPAC International Chemical Identifier (InChI) for molecules. SemanticEye’s potential as a framework for seeding collaborations between researchers, who have hitherto never met, is explored using FOAF, the friend-of-a-friend Semantic Web standard for social networks

Semantic data mining and linked data for a recommender system in the AEC industry

Even though it can provide design teams with valuable performance insights and enhance decision-making, monitored building data is rarely reused in an effective feedback loop from operation to design. Data mining allows users to obtain such insights from the large datasets generated throughout the building life cycle. Furthermore, semantic web technologies allow to formally represent the built environment and retrieve knowledge in response to domain-specific requirements. Both approaches have independently established themselves as powerful aids in decision-making. Combining them can enrich data mining processes with domain knowledge and facilitate knowledge discovery, representation and reuse. In this article, we look into the available data mining techniques and investigate to what extent they can be fused with semantic web technologies to provide recommendations to the end user in performance-oriented design. We demonstrate an initial implementation of a linked data-based system for generation of recommendations

Collaborative recommendations with content-based filters for cultural activities via a scalable event distribution platform

Nowadays, most people have limited leisure time and the offer of (cultural) activities to spend this time is enormous. Consequently, picking the most appropriate events becomes increasingly difficult for end-users. This complexity of choice reinforces the necessity of filtering systems that assist users in finding and selecting relevant events. Whereas traditional filtering tools enable e.g. the use of keyword-based or filtered searches, innovative recommender systems draw on user ratings, preferences, and metadata describing the events. Existing collaborative recommendation techniques, developed for suggesting web-shop products or audio-visual content, have difficulties with sparse rating data and can not cope at all with event-specific restrictions like availability, time, and location. Moreover, aggregating, enriching, and distributing these events are additional requisites for an optimal communication channel. In this paper, we propose a highly-scalable event recommendation platform which considers event-specific characteristics. Personal suggestions are generated by an advanced collaborative filtering algorithm, which is more robust on sparse data by extending user profiles with presumable future consumptions. The events, which are described using an RDF/OWL representation of the EventsML-G2 standard, are categorized and enriched via smart indexing and open linked data sets. This metadata model enables additional content-based filters, which consider event-specific characteristics, on the recommendation list. The integration of these different functionalities is realized by a scalable and extendable bus architecture. Finally, focus group conversations were organized with external experts, cultural mediators, and potential end-users to evaluate the event distribution platform and investigate the possible added value of recommendations for cultural participation

The RQ-Tech Methodology: A New Paradigm for Conceptualizing Strategic Enterprise Architectures

The purpose of this research is to develop and apply a system-theoretic based methodology and corresponding model for Enterprise Architecture development. Enterprise Architectures can assist managers by illustrating the systemic relationships within an organization and the impact changes to the organization could make. Unfortunately, today\u27s modeling practices are proprietary, time-consuming, and generally ineffective as tools for understanding the consequences of strategic-level planning decisions across all levels of the enterprise. This research supports the conclusion that system-specific solutions produce islands of technology and can be prevented by employing better enterprise change planning. This research combined the practice of Enterprise Architectures with a modern perspective grounded in Systems Theory and the theory regarding the computer science-oriented Semantic Web to present a distinctive methodology for developing models. A review of literature in all three areas provided an illustration of the overlap common to all three domains. It provided support for critical thinking concerning how to enrich the Enterprise Architecture practice. This research was conducted to answer to two primary questions. The first research question investigated the most significant factors to consider when translating authoritative text and rich pictures into semantic models. The second research question qualitatively measured the extent to which models aligned to important organizational guidance are useful for representing the organization as a whole. Reusable Quality Technical Architectures (RQ-Tech) is the methodology developed from this research. It demonstrates that a complex system of systems organization that must creatively respond to a variety of events can be holistically represented using a dynamic model. RQ-Tech techniques provide ways to map and link the multitudes of scope-level authoritative business documents so that together they can effectively represent the nature and essence of the organization as one organic structure. The marriage of authorized enterprise documentation and the Semantic Web produces a model of the holistic enterprise. This model had previously only been experienced at a tacit level by those exceptionally well-trained in the depth and breadth of organizational culture, supporting laws, policies and related publications. This research effort provides the vision that encourages a paradigm shift away from the mechanistic approach toward organizational change to analogy of a socially connected, interdependent enterprise. New horizons for using the common language of the Semantic Web to capture an understanding of the many interactive systems of the enterprise are substantiated. The research concludes with identification of future research themes prompted by this investigation