William Van Woensel

A semantics-based aspect-oriented approach to adaptation in web engineering

In the modern Web, users are accessing their favourite Web applications from any place, at any time and with any device. In this setting, they expect the application to user-tailor and personalize content access upon their particular needs. Exhibiting some kind of user- and context-dependency is thus crucial in Web Engineering. In this research, we focus on separating the adaptation engineering process from regular Web engineering by applying aspect-oriented techniques. We show how semantic information and metadata associated with the content can be exploited in our aspect-oriented approach. Furthermore, the approach allows the use of global (structural) properties of the Web application in adaptation specification. We thus obtain several advantages, which are demonstrated in this paper: to control adaptation specification) separate from (regular) Web Engineering oncerns in a richer, more consistent, robust and flexible way.

A Framework for Decentralized, Context-Aware Mobile Applications Using Semantic Web Technology

The recent evolution in mobile devices, combined with rapid advancements in identification techniques, has lead to new opportunities for mobile application developers: mobile applications that can be made aware of their environment and the objects in it. Additionally, by combining mobile devices and identification technology with the Web, mobile applications can be developed that exploit services and information associated with nearby objects. In this paper, we present an application framework that supports the development of such mobile applications, without having to rely on a central service to provide information on the users environment. Furthermore, by deploying Semantic Web technology, the integration of information from various information sources is facilitated, allowing for expressive and powerful personalized information delivery.

Applying semantic web technology in a mobile setting: the person matcher

In a mobile setting, users use, handle and search for online information in a different way. Two features typically desired by mobile users are tailored information delivery and context awareness. In this paper, we elaborate a demo application that is built upon the existing SCOUT framework, which supports mobile, context-aware applications. The application illustrates the use of intrinsic mobile features, such as context- and environmentawareness, and combines them with the use of Semantic Web technologies to integrate and tailor knowledge present in distributed data sources.

A Cross-Platform Benchmark Framework for Mobile Semantic Web Reasoning Engines

Semantic Web technologies are used in a variety of domains for their ability to facilitate data integration, as well as enabling expressive, standards-based reasoning. Deploying Semantic Web reasoning processes directly on mobile devices has a number of advantages, including robustness to connectivity loss, more timely results, and reduced infrastructure requirements. At the same time, a number of challenges arise as well, related to mobile platform heterogeneity and limited computing resources. To tackle these challenges, it should be possible to benchmark mobile reasoning performance across different mobile platforms, with rule- and datasets of varying scale and complexity and existing reasoning process flows. To deal with the current heterogeneity of rule formats, a uniform rule- and data-interface on top of mobile reasoning engines should be provided as well. In this paper, we present a cross-platform benchmark framework that supplies 1) a generic, standards-based Semantic Web layer on top of existing mobile reasoning engines; and 2) a benchmark engine to investigate and compare mobile reasoning performance.

A Comparison of Mobile Rule Engines for Reasoning on Semantic Web Based Health Data

Semantic Web technology is used extensively in the health domain, due to its ability to specify expressive, domain-specific data, as well as its capacity to facilitate data integration between heterogeneous, health-related sources. In the health domain, mobile devices are an essential part of patient self-management approaches, where local clinical decision support is applied to ensure that patients receive timely clinical findings. Currently, increases in mobile device capabilities have enabled the deployment of Semantic Web technologies on mobile platforms, enabling the consumption of rich, semantically described health data. To make this semantic health data available to local decision support as well, Semantic Web reasoning should be deployed on mobile platforms. However, there is currently a lack of software solutions and performance analysis of mobile, Semantic Web reasoning engines. This paper presents and compares the mobile benchmarks of 4 reasoning engines, applied on a dataset and rule set for patients with Atrial Fibrillation (AF). In particular, these benchmarks investigate the scalability of the mobile reasoning processes, and study reasoning performance for different process flows in decision support. For the purpose of these benchmarks, we extended a number of existing rule engines and RDF stores with Semantic Web reasoning capabilities.

Efficient Querying of Distributed RDF Sources in Mobile Settings based on a Source Index Model

Abstract Recent technological developments in the area of mobile devices in combination with the ubiquity of mobile connectivity have turned handheld devices into rich mobile web clients. On the other hand, we witness an increased number of web resources that are no longer only available in HTML but also in RDF format. In order to access relevant information in a mobile setting, we often want to query a subset of this large amount of heterogeneous RDF resources based on various context factors. We present a semantic technology-based client-side solution for efficient querying of large sets of distributed RDF sources without query endpoints. Our solution continuously extracts metadata from distributed RDF sources and manages this metadata in a local Source Index Model (SIM). When a new query has to be processed, the SIM is consulted to identify, assemble and query only potentially relevant resources. We do not plan to replace existing mobile query engines, but rather build on them to efficiently and transparently query large sets of distributed online RDF sources. The evaluation of our enhanced query handler reveals significant improvements in the overall query execution time based on the proposed SIM.

Assisting mobile web users: client-side injection of context-sensitive cues into websites

In a mobile setting, the user often browses the Web to consult information related to his current context and environment: e.g., reviews of nearby restaurants, or tourist information on visited monuments. On the other hand, the limitations of mobile devices (e.g., limited screen) and the peculiarities of mobile Web usage (e.g., walking around, driving a car) make it cumbersome to extensively browse a Web page for such useful information. In this paper, we present a client-side approach that aims to assist the mobile user in his browsing session, by correlating the Web pages content with the mobile users context, and subsequently emphasizing and enriching relevant content with so-called context-sensitive cues. To achieve this, we utilize the SCOUT framework for mobile applications to model and access the users context, and RDFa annotations present on existing Web pages to identify Web page elements suitable to enrich with context-sensitive cues. The cues themselves are injected using existing adaptation techniques, borrowed from the field of Adaptive Hypermedia.

A generic approach for on-the-fly adding of context-aware features to existing websites

More and more, mobile devices act as personal information managers and are able to obtain rich contextual information on the users environment. Mobile, context-aware web applications can exploit this information to better address the needs of mobile users. Currently, such websites are either developed separately from their associated desktop-oriented version, or both versions are created simultaneously by employing methodologies that support multi-platform context-aware websites, requiring an extensive engineering effort. While these approaches provide a solution for developing new websites, they go past the plethora of existing websites. To address this issue, we present an approach for enhancing existing websites on-the-fly with context-aware features. We first discuss the requirements for such an adaptation process, and identify applicable adaptation methods to realize context-aware features. Next, we explain our generic approach, which is grounded in the use of semantic information extracted from existing websites. Finally, we present a concrete application of our approach that is based on the SCOUT framework for mobile and context-aware application development.

Aspect-oriented adaptation specification in web information systems: a semantics-based approach

By tailoring content access, presentation, and functionality to the users location, device, personal preferences, and needs, Web Information Systems (WISs) have become increasingly user and context-dependent. In order to realize such adaptive behavior, Web engineers are thus faced with an additional challenge: engineering the required adaptation concerns. In this article, we present, in the context of a WIS design method, an adaptation engineering process that is separated from the regular Web design process. Our approach is based on the use of two key elements: (1) aspect-oriented techniques to achieve the separation of (adaptation) concerns; and (2) the exploitation of semantic information and metadata associated with the content, for enhanced expressivity and flexibility. By combining these key elements, we demonstrate a robust, rich, consistent, and flexible way to specify adaptation in WISs.

A semantic web-based approach to plausible reasoning for improving clinical knowledge engineering

In this paper, we present a semantic web based knowledge engineering approach to extend the coverage of medical knowledge-based systems in order to solve complex medical queries that demand the integration of deterministic and plausible knowledge. We leverage plausible reasoning mechanisms, which exploit associations between the underlying domain-specific data, as well as tentative domain knowledge, to extend the coverage of a medical knowledge base. We demonstrate that Semantic Web technologies, due to their efficient solutions for federated data management and built-in DL-based inferencing methods, offer useful opportunities to support plausible reasoning for medical decision support tasks. We evaluated our multi-strategy medical reasoning approach using real-world medical data. Our results illustrate that plausible reasoning improved the knowledge coverage of the original medical knowledge base by 10-12%, and in turn helped to solve complex disease diagnostic queries.