525,700 research outputs found
Does social software support service innovation?
Recent Internet technologies and web-based applications, such as social software, are being increasingly applied in firms. Social software can be employed for knowledge management and for external communication enabling access to internal and external knowledge. Knowledge in turn constitutes one of the main inputs to service innovation. Hence, social software has the potential to support service innovation. Using data from 505 German Information- and Communication Technology (ICT) and knowledge-intensive service firms, this is the first paper which empirically analyses the question whether the use of social software applications triggers innovation. Thereby, it refers to a knowledge production function in which social software use constitutes the knowledge sourcing activity. The results reveal that there is a positive relationship between social software and service innovation. Since this result is robust when controlling for former innovative activities and the previous propensity to adopt new technologies and to change processes, the analysis suggests that the causality runs from social software to innovation. --Social software,web 2.0,service innovation,knowledge management
BigExcel: A Web-Based Framework for Exploring Big Data in Social Sciences
This paper argues that there are three fundamental challenges that need to be
overcome in order to foster the adoption of big data technologies in
non-computer science related disciplines: addressing issues of accessibility of
such technologies for non-computer scientists, supporting the ad hoc
exploration of large data sets with minimal effort and the availability of
lightweight web-based frameworks for quick and easy analytics. In this paper,
we address the above three challenges through the development of 'BigExcel', a
three tier web-based framework for exploring big data to facilitate the
management of user interactions with large data sets, the construction of
queries to explore the data set and the management of the infrastructure. The
feasibility of BigExcel is demonstrated through two Yahoo Sandbox datasets. The
first dataset is the Yahoo Buzz Score data set we use for quantitatively
predicting trending technologies and the second is the Yahoo n-gram corpus we
use for qualitatively inferring the coverage of important events. A
demonstration of the BigExcel framework and source code is available at
http://bigdata.cs.st-andrews.ac.uk/projects/bigexcel-exploring-big-data-for-social-sciences/.Comment: 8 page
Requirements for Provenance on the Web
From where did this tweet originate? Was this quote from the New York Times modified? Daily, we rely on data from the Web but often it is difficult or impossible to determine where it came from or how it was produced. This lack of provenance is particularly evident when people and systems deal with Web information or with any environment where information comes from sources of varying quality. Provenance is not captured pervasively in information systems. There are major technical, social, and economic impediments that stand in the way of using provenance effectively. This paper synthesizes requirements for provenance on the Web for a number of dimensions focusing on three key aspects of provenance: the content of provenance, the management of provenance records, and the uses of provenance information. To illustrate these requirements, we use three synthesized scenarios that encompass provenance problems faced by Web users toda
A lightweight web video model with content and context descriptions for integration with linked data
The rapid increase of video data on the Web has warranted an urgent need for effective representation, management and retrieval of web videos. Recently, many studies have been carried out for ontological representation of videos, either using domain dependent or generic schemas such as MPEG-7, MPEG-4, and COMM. In spite of their extensive coverage and sound theoretical grounding, they are yet to be widely used by users. Two main possible reasons are the complexities involved and a lack of tool support. We propose a lightweight video content model for content-context description and integration. The uniqueness of the model is that it tries to model the emerging social context to describe and interpret the video. Our approach is grounded on exploiting easily extractable evolving contextual metadata and on the availability of existing data on the Web. This enables representational homogeneity and a firm basis for information integration among semantically-enabled data sources. The model uses many existing schemas to describe various ontology classes and shows the scope of interlinking with the Linked Data cloud
A Critical Look at Decentralized Personal Data Architectures
While the Internet was conceived as a decentralized network, the most widely
used web applications today tend toward centralization. Control increasingly
rests with centralized service providers who, as a consequence, have also
amassed unprecedented amounts of data about the behaviors and personalities of
individuals.
Developers, regulators, and consumer advocates have looked to alternative
decentralized architectures as the natural response to threats posed by these
centralized services. The result has been a great variety of solutions that
include personal data stores (PDS), infomediaries, Vendor Relationship
Management (VRM) systems, and federated and distributed social networks. And
yet, for all these efforts, decentralized personal data architectures have seen
little adoption.
This position paper attempts to account for these failures, challenging the
accepted wisdom in the web community on the feasibility and desirability of
these approaches. We start with a historical discussion of the development of
various categories of decentralized personal data architectures. Then we survey
the main ideas to illustrate the common themes among these efforts. We tease
apart the design characteristics of these systems from the social values that
they (are intended to) promote. We use this understanding to point out numerous
drawbacks of the decentralization paradigm, some inherent and others
incidental. We end with recommendations for designers of these systems for
working towards goals that are achievable, but perhaps more limited in scope
and ambition
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