135,553 research outputs found

    ARIANA: Adaptive Robust and Integrative Analysis for finding Novel Associations

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    The effective mining of biological literature can provide a range of services such as hypothesis-generation, semantic-sensitive information retrieval, and knowledge discovery, which can be important to understand the confluence of different diseases, genes, and risk factors. Furthermore, integration of different tools at specific levels could be valuable. The main focus of the dissertation is developing and integrating tools in finding network of semantically related entities. The key contribution is the design and implementation of an Adaptive Robust and Integrative Analysis for finding Novel Associations. ARIANA is a software architecture and a web-based system for efficient and scalable knowledge discovery. It integrates semantic-sensitive analysis of text-data through ontology-mapping with database search technology to ensure the required specificity. ARIANA was prototyped using the Medical Subject Headings ontology and PubMed database and has demonstrated great success as a dynamic-data-driven system. ARIANA has five main components: (i) Data Stratification, (ii) Ontology-Mapping, (iii) Parameter Optimized Latent Semantic Analysis, (iv) Relevance Model and (v) Interface and Visualization. The other contribution is integration of ARIANA with Online Mendelian Inheritance in Man database, and Medical Subject Headings ontology to provide gene-disease associations. Empirical studies produced some exciting knowledge discovery instances. Among them was the connection between the hexamethonium and pulmonary inflammation and fibrosis. In 2001, a research study at John Hopkins used the drug hexamethonium on a healthy volunteer that ended in a tragic death due to pulmonary inflammation and fibrosis. This accident might have been prevented if the researcher knew of published case report. Since the original case report in 1955, there has not been any publications regarding that association. ARIANA extracted this knowledge even though its database contains publications from 1960 to 2012. Out of 2,545 concepts, ARIANA ranked “Scleroderma, Systemic”, “Neoplasms, Fibrous Tissue”, “Pneumonia”, “Fibroma”, and “Pulmonary Fibrosis” as the 13th, 16th, 38th, 174th and 257th ranked concept respectively. The researcher had access to such knowledge this drug would likely not have been used on healthy subjects.In today\u27s world where data and knowledge are moving away from each other, semantic-sensitive tools such as ARIANA can bridge that gap and advance dissemination of knowledge

    Towards a re-engineering method for web services architectures

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    Recent developments in Web technologies – in particular through the Web services framework – have greatly enhanced the flexible and interoperable implementation of service-oriented software architectures. Many older Web-based and other distributed software systems will be re-engineered to a Web services-oriented platform. Using an advanced e-learning system as our case study, we investigate central aspects of a re-engineering approach for the Web services platform. Since our aim is to provide components of the legacy system also as services in the new platform, re-engineering to suit the new development paradigm is as important as re-engineering to suit the new architectural requirements

    The future of technology enhanced active learning – a roadmap

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    The notion of active learning refers to the active involvement of learner in the learning process, capturing ideas of learning-by-doing and the fact that active participation and knowledge construction leads to deeper and more sustained learning. Interactivity, in particular learnercontent interaction, is a central aspect of technology-enhanced active learning. In this roadmap, the pedagogical background is discussed, the essential dimensions of technology-enhanced active learning systems are outlined and the factors that are expected to influence these systems currently and in the future are identified. A central aim is to address this promising field from a best practices perspective, clarifying central issues and formulating an agenda for future developments in the form of a roadmap

    Italian center for Astronomical Archives publishing solution: modular and distributed

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    The Italian center for Astronomical Archives tries to provide astronomical data resources as interoperable services based on IVOA standards. Its VO expertise and knowledge comes from active participation within IVOA and VO at European and international level, with a double-fold goal: learn from the collaboration and provide inputs to the community. The first solution to build an easy to configure and maintain resource publisher conformant to VO standards proved to be too optimistic. For this reason it has been necessary to re-think the architecture with a modular system built around the messaging concept, where each modular component speaks to the other interested parties through a system of broker-managed queues. The first implemented protocol, the Simple Cone Search, shows the messaging task architecture connecting the parametric HTTP interface to the database backend access module, the logging module, and allows multiple cone search resources to be managed together through a configuration manager module. Even if relatively young, it already proved the flexibility required by the overall system when the database backend changed from MySQL to PostgreSQL+PgSphere. Another implementation test has been made to leverage task distribution over multiple servers to serve simultaneously: FITS cubes direct linking, cubes cutout and cubes positional merging. Currently the implementation of the SIA-2.0 standard protocol is ongoing while for TAP we will be adapting the TAPlib library. Alongside these tools a first administration tool (TASMAN) has been developed to ease the build up and maintenance of TAP_SCHEMA-ta including also ObsCore maintenance capability. Future work will be devoted at widening the range of VO protocols covered by the set of available modules, improve the configuration management and develop specific purpose modules common to all the service components.Comment: SPIE Astronomical Telescopes + Instrumentation 2018, Software and Cyberinfrastructure for Astronomy V, pre-publishing draft proceeding (reduced abstract

    Ontology technology for the development and deployment of learning technology systems - a survey

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    The World-Wide Web is undergoing dramatic changes at the moment. The Semantic Web is an initiative to bring meaning to the Web. The Semantic Web is based on ontology technology – a knowledge representation framework – at its core. We illustrate the importance of this evolutionary development. We survey five scenarios demonstrating different forms of applications of ontology technologies in the development and deployment of learning technology systems. Ontology technologies are highly useful to organise, personalise, and publish learning content and to discover, generate, and compose learning objects

    Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

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    Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page
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