2,712 research outputs found

    A knowledge hub to enhance the learning processes of an industrial cluster

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    Industrial clusters have been defined as ?networks of production of strongly interdependent firms (including specialised suppliers), knowledge producing agents (universities, research institutes, engineering companies), institutions (brokers, consultants), linked to each other in a value adding production chain? (OECD Focus Group, 1999). The industrial clusters distinctive mode of production is specialisation, based on a sophisticated division of labour, that leads to interlinked activities and need for cooperation, with the consequent emergence of communities of practice (CoPs). CoPs are here conceived as groups of people and/or organisations bound together by shared expertise and propensity towards a joint work (Wenger and Suyden, 1999). Cooperation needs closeness for just-in-time delivery, for communication, for the exchange of knowledge, especially in its tacit form. Indeed the knowledge exchanges between the CoPs specialised actors, in geographical proximity, lead to spillovers and synergies. In the digital economy landscape, the use of collaborative technologies, such as shared repositories, chat rooms and videoconferences can, when appropriately used, have a positive impact on the development of the CoP exchanges process of codified knowledge. On the other end, systems for the individuals profile management, e-learning platforms and intelligent agents can trigger also some socialisation mechanisms of tacit knowledge. In this perspective, we have set-up a model of a Knowledge Hub (KH), driven by the Information and Communication Technologies (ICT-driven), that enables the knowledge exchanges of a CoP. In order to present the model, the paper is organised in the following logical steps: - an overview of the most seminal and consolidated approaches to CoPs; - a description of the KH model, ICT-driven, conceived as a booster of the knowledge exchanges of a CoP, that adds to the economic benefits coming from geographical proximity, the advantages coming from organizational proximity, based on the ICTs; - a discussion of some preliminary results that we are obtaining during the implementation of the model.

    OntoMathPROOntoMath^{PRO} Ontology: A Linked Data Hub for Mathematics

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    In this paper, we present an ontology of mathematical knowledge concepts that covers a wide range of the fields of mathematics and introduces a balanced representation between comprehensive and sensible models. We demonstrate the applications of this representation in information extraction, semantic search, and education. We argue that the ontology can be a core of future integration of math-aware data sets in the Web of Data and, therefore, provide mappings onto relevant datasets, such as DBpedia and ScienceWISE.Comment: 15 pages, 6 images, 1 table, Knowledge Engineering and the Semantic Web - 5th International Conferenc

    CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

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    After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

    Semantic learning webs

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    By 2020, microprocessors will likely be as cheap and plentiful as scrap paper,scattered by the millions into the environment, allowing us to place intelligent systems everywhere. This will change everything around us, including the nature of commerce, the wealth of nations, and the way we communicate, work, play, and live. This will give us smart homes, cars, TVs , jewellery, and money. We will speak to our appliances, and they will speak back. Scientists also expect the Internet will wire up the entire planet and evolve into a membrane consisting of millions of computer networks, creating an “intelligent planet.” The Internet will eventually become a “Magic Mirror” that appears in fairy tales, able to speak with the wisdom of the human race. Michio Kaku, Visions: How Science Will Revolutionize the Twenty - First Century, 1998 If the semantic web needed a symbol, a good one to use would be a Navaho dream-catcher: a small web, lovingly hand-crafted, [easy] to look at, and rumored to catch dreams; but really more of a symbol than a reality. Pat Hayes, Catching the Dreams, 2002 Though it is almost impossible to envisage what the Web will be like by the end of the next decade, we can say with some certainty that it will have continued its seemingly unstoppable growth. Given the investment of time and money in the Semantic Web (Berners-Lee et al., 2001), we can also be sure that some form of semanticization will have taken place. This might be superficial - accomplished simply through the addition of loose forms of meta-data mark-up, or more principled – grounded in ontologies and formalised by means of emerging semantic web standards, such as RDF (Lassila and Swick, 1999) or OWL (Mc Guinness and van Harmelen, 2003). Whatever the case, the addition of semantic mark-up will make at least part of the Web more readily accessible to humans and their software agents and will facilitate agent interoperability. If current research is successful there will also be a plethora of e-learning platforms making use of a varied menu of reusable educational material or learning objects. For the learner, the semanticized Web will, in addition, offer rich seams of diverse learning resources over and above the course materials (or learning objects) specified by course designers. For instance, the annotation registries, which provide access to marked up resources, will enable more focussed, ontologically-guided (or semantic) search. This much is already in development. But we can go much further. Semantic technologies make it possible not only to reason about the Web as if it is one extended knowledge base but also to provide a range of additional educational semantic web services such as summarization, interpretation or sense-making, structure-visualization, and support for argumentation

    Advanced Knowledge Technologies at the Midterm: Tools and Methods for the Semantic Web

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    The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.In a celebrated essay on the new electronic media, Marshall McLuhan wrote in 1962:Our private senses are not closed systems but are endlessly translated into each other in that experience which we call consciousness. Our extended senses, tools, technologies, through the ages, have been closed systems incapable of interplay or collective awareness. Now, in the electric age, the very instantaneous nature of co-existence among our technological instruments has created a crisis quite new in human history. Our extended faculties and senses now constitute a single field of experience which demands that they become collectively conscious. Our technologies, like our private senses, now demand an interplay and ratio that makes rational co-existence possible. As long as our technologies were as slow as the wheel or the alphabet or money, the fact that they were separate, closed systems was socially and psychically supportable. This is not true now when sight and sound and movement are simultaneous and global in extent. (McLuhan 1962, p.5, emphasis in original)Over forty years later, the seamless interplay that McLuhan demanded between our technologies is still barely visible. McLuhan’s predictions of the spread, and increased importance, of electronic media have of course been borne out, and the worlds of business, science and knowledge storage and transfer have been revolutionised. Yet the integration of electronic systems as open systems remains in its infancy.Advanced Knowledge Technologies (AKT) aims to address this problem, to create a view of knowledge and its management across its lifecycle, to research and create the services and technologies that such unification will require. Half way through its sixyear span, the results are beginning to come through, and this paper will explore some of the services, technologies and methodologies that have been developed. We hope to give a sense in this paper of the potential for the next three years, to discuss the insights and lessons learnt in the first phase of the project, to articulate the challenges and issues that remain.The WWW provided the original context that made the AKT approach to knowledge management (KM) possible. AKT was initially proposed in 1999, it brought together an interdisciplinary consortium with the technological breadth and complementarity to create the conditions for a unified approach to knowledge across its lifecycle. The combination of this expertise, and the time and space afforded the consortium by the IRC structure, suggested the opportunity for a concerted effort to develop an approach to advanced knowledge technologies, based on the WWW as a basic infrastructure.The technological context of AKT altered for the better in the short period between the development of the proposal and the beginning of the project itself with the development of the semantic web (SW), which foresaw much more intelligent manipulation and querying of knowledge. The opportunities that the SW provided for e.g., more intelligent retrieval, put AKT in the centre of information technology innovation and knowledge management services; the AKT skill set would clearly be central for the exploitation of those opportunities.The SW, as an extension of the WWW, provides an interesting set of constraints to the knowledge management services AKT tries to provide. As a medium for the semantically-informed coordination of information, it has suggested a number of ways in which the objectives of AKT can be achieved, most obviously through the provision of knowledge management services delivered over the web as opposed to the creation and provision of technologies to manage knowledge.AKT is working on the assumption that many web services will be developed and provided for users. The KM problem in the near future will be one of deciding which services are needed and of coordinating them. Many of these services will be largely or entirely legacies of the WWW, and so the capabilities of the services will vary. As well as providing useful KM services in their own right, AKT will be aiming to exploit this opportunity, by reasoning over services, brokering between them, and providing essential meta-services for SW knowledge service management.Ontologies will be a crucial tool for the SW. The AKT consortium brings a lot of expertise on ontologies together, and ontologies were always going to be a key part of the strategy. All kinds of knowledge sharing and transfer activities will be mediated by ontologies, and ontology management will be an important enabling task. Different applications will need to cope with inconsistent ontologies, or with the problems that will follow the automatic creation of ontologies (e.g. merging of pre-existing ontologies to create a third). Ontology mapping, and the elimination of conflicts of reference, will be important tasks. All of these issues are discussed along with our proposed technologies.Similarly, specifications of tasks will be used for the deployment of knowledge services over the SW, but in general it cannot be expected that in the medium term there will be standards for task (or service) specifications. The brokering metaservices that are envisaged will have to deal with this heterogeneity.The emerging picture of the SW is one of great opportunity but it will not be a wellordered, certain or consistent environment. It will comprise many repositories of legacy data, outdated and inconsistent stores, and requirements for common understandings across divergent formalisms. There is clearly a role for standards to play to bring much of this context together; AKT is playing a significant role in these efforts. But standards take time to emerge, they take political power to enforce, and they have been known to stifle innovation (in the short term). AKT is keen to understand the balance between principled inference and statistical processing of web content. Logical inference on the Web is tough. Complex queries using traditional AI inference methods bring most distributed computer systems to their knees. Do we set up semantically well-behaved areas of the Web? Is any part of the Web in which semantic hygiene prevails interesting enough to reason in? These and many other questions need to be addressed if we are to provide effective knowledge technologies for our content on the web

    Transforming a competency model to assessment items

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    The problem of comparing and matching different learners’ knowledge arises when assessment systems use a one-dimensional numerical value to represent “knowledge level”. Such assessment systems may measure inconsistently because they estimate this level differently and inadequately. The multi-dimensional competency model called COMpetence-Based learner knowledge for personalized Assessment (COMBA) is being developed to represent a learner’s knowledge in a multi-dimensional vector space. The heart of this model is to treat knowledge, not as possession, but as a contextualized space of capability either actual or potential. The paper discusses the automatic generation of an assessment from the COMBA competency model as a “guideon- the–side”

    Applications of semantic web technology to support learning content development

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    The Semantic Web is based on ontology technology – a knowledge representation framework – at its core to make meaning explicit and more accessible to automatic processing. We discuss the potential of this technology for the development of content for learning technology systems. We survey seven application types demonstrating different forms of applications of ontologies and the Semantic Web in the development of learning technology systems. Ontology technologies can assist developers, instructors, and learners to organise, personalise, and publish learning content and to discover, generate, and compose learning content. A conceptual content development and deployment architecture allows us to distinguish and locate the different applications and to dis-cuss and assess the potential of the underlying technologies
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