628 research outputs found

    Ontologies on the semantic web

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    As an informational technology, the World Wide Web has enjoyed spectacular success. In just ten years it has transformed the way information is produced, stored, and shared in arenas as diverse as shopping, family photo albums, and high-level academic research. The “Semantic Web” was touted by its developers as equally revolutionary but has not yet achieved anything like the Web’s exponential uptake. This 17 000 word survey article explores why this might be so, from a perspective that bridges both philosophy and IT

    ImageJ2: ImageJ for the next generation of scientific image data

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    ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys contributions from non-programmers, amateur programmers, and professional developers alike. Enabling such a diversity of contributors has resulted in a large community that spans the biological and physical sciences. However, a rapidly growing user base, diverging plugin suites, and technical limitations have revealed a clear need for a concerted software engineering effort to support emerging imaging paradigms, to ensure the software's ability to handle the requirements of modern science. Due to these new and emerging challenges in scientific imaging, ImageJ is at a critical development crossroads. We present ImageJ2, a total redesign of ImageJ offering a host of new functionality. It separates concerns, fully decoupling the data model from the user interface. It emphasizes integration with external applications to maximize interoperability. Its robust new plugin framework allows everything from image formats, to scripting languages, to visualization to be extended by the community. The redesigned data model supports arbitrarily large, N-dimensional datasets, which are increasingly common in modern image acquisition. Despite the scope of these changes, backwards compatibility is maintained such that this new functionality can be seamlessly integrated with the classic ImageJ interface, allowing users and developers to migrate to these new methods at their own pace. ImageJ2 provides a framework engineered for flexibility, intended to support these requirements as well as accommodate future needs

    A new generation of cyberinfrastructure and data services for earth system science education and research

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    International audienceA revolution is underway in the role played by cyberinfrastructure and modern data services in the conduct of research and education. We live in an era of an unprecedented data volume from diverse sources, multidisciplinary analysis and synthesis, and active, learner-centered education emphasis. Complex environmental problems such as global change and water cycle transcend disciplinary and geographic boundaries, and their solution requires integrated earth system science approaches. Contemporary education strategies recommend adopting an Earth system science approach for teaching the geosciences, employing pedagogical techniques such as enquiry-based learning. The resulting transformation in geoscience education and research creates new opportunities for advancement and poses many challenges. The success of the scientific enterprise depends heavily on the availability of a state-of-the-art, robust, and flexible cyberinfrastructure, and on the timely access to quality data, products, and tools to process, manage, analyze, integrate, publish, and visualize those data. Concomittantly, rapid advances in computing, communication, and information technologies have revolutionized the provision and use of data, tools and services. The profound consequences of Moore's Law and the explosive growth of the Internet are well known. On the other hand, how other technological trends have shaped the development of data services is less well understood. For example, the advent of digital libraries, web services, open standards and protocols have been important factors in shaping a new generation of cyberinfrastructure for solving key scientific and educational problems. This paper presents a broad overview of these issues, along with a survey of key information technology trends, and discuses how those trends are enabling new approaches to applying data services for solving geoscientific problems

    A Semantic Web approach to ontology-based system: integrating, sharing and analysing IoT health and fitness data

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    With the rapid development of fitness industry, Internet of Things (IoT) technology is becoming one of the most popular trends for the health and fitness areas. IoT technologies have revolutionised the fitness and the sport industry by giving users the ability to monitor their health status and keep track of their training sessions. More and more sophisticated wearable devices, fitness trackers, smart watches and health mobile applications will appear in the near future. These systems do collect data non-stop from sensors and upload them to the Cloud. However, from a data-centric perspective the landscape of IoT fitness devices and wellness appliances is characterised by a plethora of representation and serialisation formats. The high heterogeneity of IoT data representations and the lack of common accepted standards, keep data isolated within each single system, preventing users and health professionals from having an integrated view of the various information collected. Moreover, in order to fully exploit the potential of the large amounts of data, it is also necessary to enable advanced analytics over it, thus achieving actionable knowledge. Therefore, due the above situation, the aim of this thesis project is to design and implement an ontology based system to (1) allow data interoperability among heterogeneous IoT fitness and wellness devices, (2) facilitate the integration and the sharing of information and (3) enable advanced analytics over the collected data (Cognitive Computing). The novelty of the proposed solution lies in exploiting Semantic Web technologies to formally describe the meaning of the data collected by the IoT devices and define a common communication strategy for information representation and exchange

    IAO-Intel: An Ontology of Information Artifacts in the Intelligence Domain

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    We describe on-going work on IAO-Intel, an information artifact ontology developed as part of a suite of ontologies designed to support the needs of the US Army intelligence community within the framework of the Distributed Common Ground System (DCGS-A). IAO-Intel provides a controlled, structured vocabulary for the consistent formulation of metadata about documents, images, emails and other carriers of information. It will provide a resource for uniform explication of the terms used in multiple existing military dictionaries, thesauri and metadata registries, thereby enhancing the degree to which the content formulated with their aid will be available to computational reasoning

    Current status of biomedical ontologies: developments in 2007

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    The goal of this paper is to survey existing biomedical ontologies and their developments in 2007. This paper discusses features of biomedical ontologies that allow true information integration in biomedical domain. The paper is a compilation of several biomedical ontologies like Gene Ontology, Protein Ontology, etc. that have developed serving primarily the purposes of information extraction from on-line biomedical literature and databases

    SIMDAT

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