7,251 research outputs found

    Privacy Issues of the W3C Geolocation API

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    The W3C's Geolocation API may rapidly standardize the transmission of location information on the Web, but, in dealing with such sensitive information, it also raises serious privacy concerns. We analyze the manner and extent to which the current W3C Geolocation API provides mechanisms to support privacy. We propose a privacy framework for the consideration of location information and use it to evaluate the W3C Geolocation API, both the specification and its use in the wild, and recommend some modifications to the API as a result of our analysis

    Expanding JavaScript\u27s metaobject protocol

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    Towards MKM in the Large: Modular Representation and Scalable Software Architecture

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    MKM has been defined as the quest for technologies to manage mathematical knowledge. MKM "in the small" is well-studied, so the real problem is to scale up to large, highly interconnected corpora: "MKM in the large". We contend that advances in two areas are needed to reach this goal. We need representation languages that support incremental processing of all primitive MKM operations, and we need software architectures and implementations that implement these operations scalably on large knowledge bases. We present instances of both in this paper: the MMT framework for modular theory-graphs that integrates meta-logical foundations, which forms the base of the next OMDoc version; and TNTBase, a versioned storage system for XML-based document formats. TNTBase becomes an MMT database by instantiating it with special MKM operations for MMT.Comment: To appear in The 9th International Conference on Mathematical Knowledge Management: MKM 201

    Identifying Key Steps for Developing Mobile Applications and Mobile Websites for Libraries

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    Mobile applications and mobile websites (MAMW) represent information systems that are increasingly being developed by libraries to better serve their patrons. Due to a lack of in-house IT skills and the knowledge necessary to develop MAMW, a majority of libraries are forced to rely on external IT professionals, who may or may not help libraries meet patron needs but instead may deplete libraries’ scarce financial resources. This paper applies a system analysis and design perspective to analyze the experience and advice shared by librarians and IT professionals engaged in developing MAMW. This paper identifies key steps and precautions to take while developing MAMW for libraries. It also advises library and information science (LIS) graduate programs to equip their students with the specific skills and knowledge needed to develop and implement MAMW

    BEAT: An Open-Source Web-Based Open-Science Platform

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    With the increased interest in computational sciences, machine learning (ML), pattern recognition (PR) and big data, governmental agencies, academia and manufacturers are overwhelmed by the constant influx of new algorithms and techniques promising improved performance, generalization and robustness. Sadly, result reproducibility is often an overlooked feature accompanying original research publications, competitions and benchmark evaluations. The main reasons behind such a gap arise from natural complications in research and development in this area: the distribution of data may be a sensitive issue; software frameworks are difficult to install and maintain; Test protocols may involve a potentially large set of intricate steps which are difficult to handle. Given the raising complexity of research challenges and the constant increase in data volume, the conditions for achieving reproducible research in the domain are also increasingly difficult to meet. To bridge this gap, we built an open platform for research in computational sciences related to pattern recognition and machine learning, to help on the development, reproducibility and certification of results obtained in the field. By making use of such a system, academic, governmental or industrial organizations enable users to easily and socially develop processing toolchains, re-use data, algorithms, workflows and compare results from distinct algorithms and/or parameterizations with minimal effort. This article presents such a platform and discusses some of its key features, uses and limitations. We overview a currently operational prototype and provide design insights.Comment: References to papers published on the platform incorporate
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