11,613 research outputs found
Measuring internet activity: a (selective) review of methods and metrics
Two Decades after the birth of the World Wide Web, more than two billion people around the world are Internet users. The digital landscape is littered with hints that the affordances of digital communications are being leveraged to transform life in profound and important ways. The reach and influence of digitally mediated activity grow by the day and touch upon all aspects of life, from health, education, and commerce to religion and governance. This trend demands that we seek answers to the biggest questions about how digitally mediated communication changes society and the role of different policies in helping or hindering the beneficial aspects of these changes. Yet despite the profusion of data the digital age has brought upon us—we now have access to a flood of information about the movements, relationships, purchasing decisions, interests, and intimate thoughts of people around the world—the distance between the great questions of the digital age and our understanding of the impact of digital communications on society remains large. A number of ongoing policy questions have emerged that beg for better empirical data and analyses upon which to base wider and more insightful perspectives on the mechanics of social, economic, and political life online. This paper seeks to describe the conceptual and practical impediments to measuring and understanding digital activity and highlights a sample of the many efforts to fill the gap between our incomplete understanding of digital life and the formidable policy questions related to developing a vibrant and healthy Internet that serves the public interest and contributes to human wellbeing. Our primary focus is on efforts to measure Internet activity, as we believe obtaining robust, accurate data is a necessary and valuable first step that will lead us closer to answering the vitally important questions of the digital realm. Even this step is challenging: the Internet is difficult to measure and monitor, and there is no simple aggregate measure of Internet activity—no GDP, no HDI. In the following section we present a framework for assessing efforts to document digital activity. The next three sections offer a summary and description of many of the ongoing projects that document digital activity, with two final sections devoted to discussion and conclusions
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Multimedia delivery in the future internet
The term “Networked Media” implies that all kinds of media including text, image, 3D graphics, audio
and video are produced, distributed, shared, managed and consumed on-line through various networks,
like the Internet, Fiber, WiFi, WiMAX, GPRS, 3G and so on, in a convergent manner [1]. This white
paper is the contribution of the Media Delivery Platform (MDP) cluster and aims to cover the Networked
challenges of the Networked Media in the transition to the Future of the Internet.
Internet has evolved and changed the way we work and live. End users of the Internet have been confronted
with a bewildering range of media, services and applications and of technological innovations concerning
media formats, wireless networks, terminal types and capabilities. And there is little evidence that the pace
of this innovation is slowing. Today, over one billion of users access the Internet on regular basis, more
than 100 million users have downloaded at least one (multi)media file and over 47 millions of them do so
regularly, searching in more than 160 Exabytes1 of content. In the near future these numbers are expected
to exponentially rise. It is expected that the Internet content will be increased by at least a factor of 6, rising
to more than 990 Exabytes before 2012, fuelled mainly by the users themselves. Moreover, it is envisaged
that in a near- to mid-term future, the Internet will provide the means to share and distribute (new)
multimedia content and services with superior quality and striking flexibility, in a trusted and personalized
way, improving citizens’ quality of life, working conditions, edutainment and safety.
In this evolving environment, new transport protocols, new multimedia encoding schemes, cross-layer inthe
network adaptation, machine-to-machine communication (including RFIDs), rich 3D content as well as
community networks and the use of peer-to-peer (P2P) overlays are expected to generate new models of
interaction and cooperation, and be able to support enhanced perceived quality-of-experience (PQoE) and
innovative applications “on the move”, like virtual collaboration environments, personalised services/
media, virtual sport groups, on-line gaming, edutainment. In this context, the interaction with content
combined with interactive/multimedia search capabilities across distributed repositories, opportunistic P2P
networks and the dynamic adaptation to the characteristics of diverse mobile terminals are expected to
contribute towards such a vision.
Based on work that has taken place in a number of EC co-funded projects, in Framework Program 6 (FP6)
and Framework Program 7 (FP7), a group of experts and technology visionaries have voluntarily
contributed in this white paper aiming to describe the status, the state-of-the art, the challenges and the way
ahead in the area of Content Aware media delivery platforms
Next challenges for adaptive learning systems
Learning from evolving streaming data has become a 'hot' research topic in the last decade and many adaptive learning algorithms have been developed. This research was stimulated by rapidly growing amounts of industrial, transactional, sensor and other business data that arrives in real time and needs to be mined in real time. Under such circumstances, constant manual adjustment of models is in-efficient and with increasing amounts of data is becoming infeasible. Nevertheless, adaptive learning models are still rarely employed in business applications in practice. In the light of rapidly growing structurally rich 'big data', new generation of parallel computing solutions and cloud computing services as well as recent advances in portable computing devices, this article aims to identify the current key research directions to be taken to bring the adaptive learning closer to application needs. We identify six forthcoming challenges in designing and building adaptive learning (pre-diction) systems: making adaptive systems scalable, dealing with realistic data, improving usability and trust, integrat-ing expert knowledge, taking into account various application needs, and moving from adaptive algorithms towards adaptive tools. Those challenges are critical for the evolving stream settings, as the process of model building needs to be fully automated and continuous.</jats:p
When Things Matter: A Data-Centric View of the Internet of Things
With the recent advances in radio-frequency identification (RFID), low-cost
wireless sensor devices, and Web technologies, the Internet of Things (IoT)
approach has gained momentum in connecting everyday objects to the Internet and
facilitating machine-to-human and machine-to-machine communication with the
physical world. While IoT offers the capability to connect and integrate both
digital and physical entities, enabling a whole new class of applications and
services, several significant challenges need to be addressed before these
applications and services can be fully realized. A fundamental challenge
centers around managing IoT data, typically produced in dynamic and volatile
environments, which is not only extremely large in scale and volume, but also
noisy, and continuous. This article surveys the main techniques and
state-of-the-art research efforts in IoT from data-centric perspectives,
including data stream processing, data storage models, complex event
processing, and searching in IoT. Open research issues for IoT data management
are also discussed
Mapping Large Scale Research Metadata to Linked Data: A Performance Comparison of HBase, CSV and XML
OpenAIRE, the Open Access Infrastructure for Research in Europe, comprises a
database of all EC FP7 and H2020 funded research projects, including metadata
of their results (publications and datasets). These data are stored in an HBase
NoSQL database, post-processed, and exposed as HTML for human consumption, and
as XML through a web service interface. As an intermediate format to facilitate
statistical computations, CSV is generated internally. To interlink the
OpenAIRE data with related data on the Web, we aim at exporting them as Linked
Open Data (LOD). The LOD export is required to integrate into the overall data
processing workflow, where derived data are regenerated from the base data
every day. We thus faced the challenge of identifying the best-performing
conversion approach.We evaluated the performances of creating LOD by a
MapReduce job on top of HBase, by mapping the intermediate CSV files, and by
mapping the XML output.Comment: Accepted in 0th Metadata and Semantics Research Conferenc
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