A community based approach for managing ontology alignments

The Semantic Web is rapidly becoming a defacto distributed repository for semantically represented data, thus leveraging on the added on value of the network effect. Various ontology mapping techniques and tools have been devised to facilitate the bridging and integration of distributed data repositories. Nevertheless, ontology mapping can benefitfrom human supervision to increase accuracy of results. The spread of Web 2.0 approaches demonstrate the possibility of using collaborative techniques for reaching consensus. While a number of prototypes for collaborative ontology construction are being developed, collaborative ontology mapping is not yet well investigated. In this paper, we describe a prototype that combines off-the-shelf ontology mapping tools with social software techniques to enable users to collaborate on mapping ontologies

FEMwiki: crowdsourcing semantic taxonomy and wiki input to domain experts while keeping editorial control: Mission Possible!

Highly specialized professional communities of practice (CoP) inevitably need to operate across geographically dispersed area - members frequently need to interact and share professional content. Crowdsourcing using wiki platforms provides a novel way for a professional community to share ideas and collaborate on content creation, curation, maintenance and sharing. This is the aim of the Field Epidemiological Manual wiki (FEMwiki) project enabling online collaborative content sharing and interaction for field epidemiologists around a growing training wiki resource. However, while user contributions are the driving force for content creation, any medical information resource needs to keep editorial control and quality assurance. This requirement is typically in conflict with community-driven Web 2.0 content creation. However, to maximize the opportunities for the network of epidemiologists actively editing the wiki content while keeping quality and editorial control, a novel structure was developed to encourage crowdsourcing – a support for dual versioning for each wiki page enabling maintenance of expertreviewed pages in parallel with user-updated versions, and a clear navigation between the related versions. Secondly, the training wiki content needs to be organized in a semantically-enhanced taxonomical navigation structure enabling domain experts to find information on a growing site easily. This also provides an ideal opportunity for crowdsourcing. We developed a user-editable collaborative interface crowdsourcing the taxonomy live maintenance to the community of field epidemiologists by embedding the taxonomy in a training wiki platform and generating the semantic navigation hierarchy on the fly. Launched in 2010, FEMwiki is a real world service supporting field epidemiologists in Europe and worldwide. The crowdsourcing success was evaluated by assessing the number and type of changes made by the professional network of epidemiologists over several months and demonstrated that crowdsourcing encourages user to edit existing and create new content and also leads to expansion of the domain taxonomy

Mind the Gap: From Desktop to App

In this article we present a new mobile game, edugames4all MicrobeQuest!, that covers core learning objectives from the European curriculum on microbe transmission, food and hand hygiene, and responsible antibiotic use. The game is aimed at 9 to 12 year olds and it is based on the desktop version of the edugames4all platform games. We discuss the challenges and lessons learned transitioning from a desktop based game to a mobile app. We also present the seamless evaluation obtained by integrating the assessment of educa- tional impact of the game into the game mechanics

Ontology For Europe's Space Situational Awareness Program

This paper presents an ontology architecture concept for the European Space Agency‘s (ESA) Space Situational Awareness (SSA) Program. It incorporates the author‘s domain ontology, The Space Situational Awareness Ontology and related ontology work. I summarize computational ontology, discuss the segments of ESA SSA, and introduce an option for a modular ontology framework reflecting the divisionsof the SSA program. Among other things, ontologies are used for data sharing and integration. By applying ontology to ESA data, the ESA may better achieve its integration and innovation goals, while simultaneously improving the state of peaceful SSA

A Semantic Grid Oriented to E-Tourism

With increasing complexity of tourism business models and tasks, there is a clear need of the next generation e-Tourism infrastructure to support flexible automation, integration, computation, storage, and collaboration. Currently several enabling technologies such as semantic Web, Web service, agent and grid computing have been applied in the different e-Tourism applications, however there is no a unified framework to be able to integrate all of them. So this paper presents a promising e-Tourism framework based on emerging semantic grid, in which a number of key design issues are discussed including architecture, ontologies structure, semantic reconciliation, service and resource discovery, role based authorization and intelligent agent. The paper finally provides the implementation of the framework.Comment: 12 PAGES, 7 Figure

Language technologies and the evolution of the semantic web

The availability of huge amounts of semantic markup on the Web promises to enable a quantum leap in the level of support available to Web users for locating, aggregating, sharing, interpreting and customizing information. While we cannot claim that a large scale Semantic Web already exists, a number of applications have been produced, which generate and exploit semantic markup, to provide advanced search and querying functionalities, and to allow the visualization and management of heterogeneous, distributed data. While these tools provide evidence of the feasibility and tremendous potential value of the enterprise, they all suffer from major limitations, to do primarily with the limited degree of scale and heterogeneity of the semantic data they use. Nevertheless, we argue that we are at a key point in the brief history of the Semantic Web and that the very latest demonstrators already give us a glimpse of what future applications will look like. In this paper, we describe the already visible effects of these changes by analyzing the evolution of Semantic Web tools from smart databases towards applications that harness collective intelligence. We also point out that language technology plays an important role in making this evolution sustainable and we highlight the need for improved support, especially in the area of large-scale linguistic resources