9,470 research outputs found

    From Artifacts to Aggregations: Modeling Scientific Life Cycles on the Semantic Web

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    In the process of scientific research, many information objects are generated, all of which may remain valuable indefinitely. However, artifacts such as instrument data and associated calibration information may have little value in isolation; their meaning is derived from their relationships to each other. Individual artifacts are best represented as components of a life cycle that is specific to a scientific research domain or project. Current cataloging practices do not describe objects at a sufficient level of granularity nor do they offer the globally persistent identifiers necessary to discover and manage scholarly products with World Wide Web standards. The Open Archives Initiative's Object Reuse and Exchange data model (OAI-ORE) meets these requirements. We demonstrate a conceptual implementation of OAI-ORE to represent the scientific life cycles of embedded networked sensor applications in seismology and environmental sciences. By establishing relationships between publications, data, and contextual research information, we illustrate how to obtain a richer and more realistic view of scientific practices. That view can facilitate new forms of scientific research and learning. Our analysis is framed by studies of scientific practices in a large, multi-disciplinary, multi-university science and engineering research center, the Center for Embedded Networked Sensing (CENS).Comment: 28 pages. To appear in the Journal of the American Society for Information Science and Technology (JASIST

    Citations and herding: why one article makes it and another doesn't

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    The purpose of this paper is to draw a link between citations and the choice overload paradigm and show that herding plays a role in citing behavior. In addition, parallel with an increase in the number of published papers, we observe an increase in the strength of herding in citation

    Digital Preservation, Archival Science and Methodological Foundations for Digital Libraries

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    Digital libraries, whether commercial, public or personal, lie at the heart of the information society. Yet, research into their long‐term viability and the meaningful accessibility of their contents remains in its infancy. In general, as we have pointed out elsewhere, ‘after more than twenty years of research in digital curation and preservation the actual theories, methods and technologies that can either foster or ensure digital longevity remain startlingly limited.’ Research led by DigitalPreservationEurope (DPE) and the Digital Preservation Cluster of DELOS has allowed us to refine the key research challenges – theoretical, methodological and technological – that need attention by researchers in digital libraries during the coming five to ten years, if we are to ensure that the materials held in our emerging digital libraries are to remain sustainable, authentic, accessible and understandable over time. Building on this work and taking the theoretical framework of archival science as bedrock, this paper investigates digital preservation and its foundational role if digital libraries are to have long‐term viability at the centre of the global information society.

    Copley Connects | Spring 2017

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    Copley Library Recognizes Banned Books Week | 1Dean’s Update | 2Announcing the 2017 Recipients of the Roy and Marian Holleman Copley Library Student Assistant Scholarship | 3Expand Your Audience with Digital USD | 4A Long-Term Relationship: Copley Library and the Kyoto Prize Symposium | 5Digital Initiatives Symposium | 6-7Department Update: Access and Outreach Services Professional Development | 8Faculty Scholarship at the Copley Library Fall 2017 Salon | 9New Faculty | 9Chance Encounter | 10Giving to Copley Library | 12https://digital.sandiego.edu/copley_connects/1008/thumbnail.jp

    Comparing explicit and implicit feedback techniques for web retrieval : TREC-10 interactive track report

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    In this paper we examine the extent to which implicit feedback (where the system attempts to estimate what the user may be interested in) can act as a substitute for explicit feedback (where searchers explicitly mark documents relevant). Therefore, we attempt to side-step the problem of getting users to explicitly mark documents relevant by making predictions on relevance through analysing the user's interaction with the system. Specifically, we hypothesised that implicit and explicit feedback were interchangeable as sources of relevance information for relevance feedback. Through developing a system that utilised each type of feedback we were able to compare the two approaches in terms of search effectiveness
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