700,517 research outputs found
Small-World File-Sharing Communities
Web caches, content distribution networks, peer-to-peer file sharing
networks, distributed file systems, and data grids all have in common that they
involve a community of users who generate requests for shared data. In each
case, overall system performance can be improved significantly if we can first
identify and then exploit interesting structure within a community's access
patterns. To this end, we propose a novel perspective on file sharing based on
the study of the relationships that form among users based on the files in
which they are interested.
We propose a new structure that captures common user interests in data--the
data-sharing graph-- and justify its utility with studies on three
data-distribution systems: a high-energy physics collaboration, the Web, and
the Kazaa peer-to-peer network. We find small-world patterns in the
data-sharing graphs of all three communities. We analyze these graphs and
propose some probable causes for these emergent small-world patterns. The
significance of small-world patterns is twofold: it provides a rigorous support
to intuition and, perhaps most importantly, it suggests ways to design
mechanisms that exploit these naturally emerging patterns
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MetaMorphosis+ - A social network of educational Web resources based on semantic integration of services and data
Past research aiming at interoperability within the Technology Enhanced Learning (TEL) field has led to a fragmented landscape of competing metadata schemas and interface mechanisms. So far, Web-scale integration of resources is not facilitated, mainly due to the lack of take-up of shared principles, datasets and schemas. On the other hand, the Linked Data approach has emerged as the de facto standard for sharing data on the Web. We propose MetaMorphosis+, a social educational application which adopts a general approach to exploit existing TEL data on the Web by allowing its exposure as Linked Data and by taking into account automated enrichment and interlinking techniques to provide rich and well-interlinked data for the educational domain
Relating geometry descriptions to its derivatives on the web
Sharing building information over the Web is becoming more popular, leading to advances in describing building models in a Semantic Web context. However, those descriptions lack unified approaches for linking geometry descriptions to building elements, derived properties and derived other geometry descriptions. To bridge this gap, we analyse the basic characteristics of geometric dependencies and propose the Ontology for Managing Geometry (OMG) based on this analysis. In this paper, we present our results and show how the OMG provides means to link geometric and non-geometric data in meaningful ways. Thus, exchanging building data, including geometry, on the Web becomes more efficient
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A linked data-driven & service-oriented architecture for sharing educational resources
The two fundamental aims of managing educational resources are to enable resources to be reusable and interoperable and to enable Web-scale sharing of resources across learning communities. Currently, a variety of approaches have been proposed to expose and manage educational resources and their metadata on the Web. These are usually based on heterogeneous metadata standards and schemas, such as IEEE LOM or ADL SCORM, and diverse repository interfaces such as OAI-PMH or SQI. Also, there is still a lack of usage of controlled vocabularies and available data sets that could replace the widespread use of unstructured text for describing resources. On the other hand, the Linked Data approach has proven that it offers a set of successful principles that have the potential to alleviate the aforementioned issues. In this paper, we introduce an architecture and prototype which is fundamentally based on (a) Linked Data principles and (b) Service-orientation to resolve the integration issues for sharing educational resources
Research Data Management and Sharing Practices in the Digital Humanities with a Focus on Publisher Support: A Case Study in the Field of Web Archive Studies
The research problem at the centre of this study is twofold. First, not enough Research Data Management studies have been conducted in either the humanities or the Digital Humanities that present a well-developed understanding of the nature of data in these fields, or the appropriate management thereof. Second, there is a critical lack of Research Data Management and data sharing support provided to researchers in these fields. While multiple stakeholders play roles in providing such support, this study focuses on the support provided to researchers by publishers. While the overarching study investigates data management and sharing in the Digital Humanities and how publishers support these practices, the specific case concerns the field of Web Archive Studies. The case study also gathers broader insights into Digital Humanities researchers, under which WAS is classified as a specialised field. The purpose of the study was to explore the nature of data, and current RDM and data sharing practices of Web Archive Studies researchers, with a focus on publishers' engagement with researchers and support for said practices. The aim was to uncover ways in which publishers might better support Web Archive Studies researchers in managing and sharing their data. The case study answered the following research questions: (1) âWhat kinds of data do Web Archive Studies researchers generate and work with?'; (2) âWhat RDM and data sharing practices do these researchers tend to use?'; (3) âWhat challenges and limitations do they encounter when collecting, managing, and sharing data?'; (4) âHow can publishers better support Web Archive Studies researchers in managing and sharing their data?'. The study is exploratory in nature and uses a convergent mixed-methods approach based within an interpretive paradigm. Three semi-structured interviews (using predominantly open-ended questions) and a questionnaire (including predominantly multiple-choice questions) were conducted. A content analysis approach was used to analyse qualitative data, while quantitative data were interpreted using inferential statistics. The populations sampled included publishers and Web Archive Studies researchers. The study found that Web Archive Studies researchers tend to manage their data proficiently. The biggest gaps in their current practices concern data sharing in formal repositories due to challenges like legal restrictions. Additional findings reveal a lack of funding for Research Data Management and data sharing in this field, as well as a lack of guidance and training from publishers for Web Archive Studies researchers. Information Classification: General Key recommendations include the following: (1) publishers should develop guidance specific to Web Archive Studies researchers' RDM and data sharing needs; (2) publishers should focus on sharing methodological processes, audit trails, and research instruments, rather than sharing data for Web Archive Studies and other humanities subjects. These actions would promote transparency in subject areas for which data sharing is often not possible due to legal restrictions, among other challenges
Graffiti Networks: A Subversive, Internet-Scale File Sharing Model
The proliferation of peer-to-peer (P2P) file sharing protocols is due to
their efficient and scalable methods for data dissemination to numerous users.
But many of these networks have no provisions to provide users with long term
access to files after the initial interest has diminished, nor are they able to
guarantee protection for users from malicious clients that wish to implicate
them in incriminating activities. As such, users may turn to supplementary
measures for storing and transferring data in P2P systems. We present a new
file sharing paradigm, called a Graffiti Network, which allows peers to harness
the potentially unlimited storage of the Internet as a third-party
intermediary. Our key contributions in this paper are (1) an overview of a
distributed system based on this new threat model and (2) a measurement of its
viability through a one-year deployment study using a popular web-publishing
platform. The results of this experiment motivate a discussion about the
challenges of mitigating this type of file sharing in a hostile network
environment and how web site operators can protect their resources
Rule-Based Application Development using Webdamlog
We present the WebdamLog system for managing distributed data on the Web in a
peer-to-peer manner. We demonstrate the main features of the system through an
application called Wepic for sharing pictures between attendees of the sigmod
conference. Using Wepic, the attendees will be able to share, download, rate
and annotate pictures in a highly decentralized manner. We show how WebdamLog
handles heterogeneity of the devices and services used to share data in such a
Web setting. We exhibit the simple rules that define the Wepic application and
show how to easily modify the Wepic application.Comment: SIGMOD - Special Interest Group on Management Of Data (2013
Survey of tools for collaborative knowledge construction and sharing
The fast growth and spread of Web 2.0 environments have demonstrated the great willingness of general Web users to contribute and share various type of content and information. Many very successful web sites currently exist which thrive on the wisdom of the crowd, where web users in general are the sole data providers and curators. The Semantic Web calls for knowledge to be semantically represented using ontologies to allow for better access and sharing of data. However, constructing ontologies collaboratively is not well supported by most existing ontology and knowledge-base editing tools. This has resulted in the recent emergence of a new range of collaborative ontology construction tools with the aim of integrating some Web 2.0 features into the process of structured knowledge construction. This paper provides a survey of the start of the art of these tools, and highlights their significant features and capabilities
The Research Object Suite of Ontologies: Sharing and Exchanging Research Data and Methods on the Open Web
Research in life sciences is increasingly being conducted in a digital and
online environment. In particular, life scientists have been pioneers in
embracing new computational tools to conduct their investigations. To support
the sharing of digital objects produced during such research investigations, we
have witnessed in the last few years the emergence of specialized repositories,
e.g., DataVerse and FigShare. Such repositories provide users with the means to
share and publish datasets that were used or generated in research
investigations. While these repositories have proven their usefulness,
interpreting and reusing evidence for most research results is a challenging
task. Additional contextual descriptions are needed to understand how those
results were generated and/or the circumstances under which they were
concluded. Because of this, scientists are calling for models that go beyond
the publication of datasets to systematically capture the life cycle of
scientific investigations and provide a single entry point to access the
information about the hypothesis investigated, the datasets used, the
experiments carried out, the results of the experiments, the people involved in
the research, etc. In this paper we present the Research Object (RO) suite of
ontologies, which provide a structured container to encapsulate research data
and methods along with essential metadata descriptions. Research Objects are
portable units that enable the sharing, preservation, interpretation and reuse
of research investigation results. The ontologies we present have been designed
in the light of requirements that we gathered from life scientists. They have
been built upon existing popular vocabularies to facilitate interoperability.
Furthermore, we have developed tools to support the creation and sharing of
Research Objects, thereby promoting and facilitating their adoption.Comment: 20 page
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