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      <title-group>
        <article-title>X-Media: Large Scale Knowledge Acquisition, Sharing and Reuse across-Media</article-title>
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      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Fabio Ciravegna</string-name>
          <email>f.ciravegna@dcs.shef.ac.uk</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Steffen Staab</string-name>
          <email>staab@uni-koblenz.de</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>F. Ciravegna is with the Department of Computer Science of the University of Sheffield</institution>
          ,
          <addr-line>Regent Court, 211 Portobello Street, S1 4DP, Sheffield</addr-line>
          ,
          <country country="UK">UK</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>- X-Media is an integrated Project funded by the European Commission, which addresses the issue of knowledge management in complex distributed environments. It will study, develop and implement large scale methodologies and techniques for knowledge management able to support sharing and reuse of knowledge that is distributed across different media (images, documents and data) and repositories (data bases, knowledge bases, document repositories, etc.). The project started in March 2006 and will last for 4 years.</p>
      </abstract>
      <kwd-group>
        <kwd>Cross Media Knowledge Acquisition</kwd>
        <kwd>Crossmedia Knowledge Sharing</kwd>
        <kwd>Architectures for Knowledge Management</kwd>
      </kwd-group>
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      <title>I. INTRODUCTION</title>
      <p>Warchives used to be the only resources for knowledge
hile in the past, medium size, mainly textual, centralized
management, nowadays large companies handle very
large quantities of multimedia information in distributed
archives. Their intranets connect thousands of computers and
reach sizes of dozens of millions of documents. In addition, the
increased use of the WWW as a source of information has
made the boundary between intra- and inter-net very thin. This
dramatically increases the size of the information space.
Moreover, databases and archives are used to store huge
amounts of information that is vital for the organization life,
such as data on products, financial information, etc. Collecting
and aggregating multimedia knowledge is of fundamental
importance in order to gain competitiveness and to reduce
costs. For example thousands of documents are produced
during the design and manufacturing of a class of jet engines.
During service, a single engine produces about 1Gbyte of
vibration data per flight; if irregularities are found, part of the
data is stored. Every time an engine is serviced, financial
information is produced. If problems are found, pictures are
taken, reports are written. Each individual engine has a
potential “folder” of information describing the whole lifecycle
of the engine that can easily sum up to several Gigabytes of
information, potentially Terabytes, and contains highly
interrelated information stored in different media.</p>
      <p>The growing size and the multi-media nature of the archives
have serious implication on the way knowledge management
can be implemented. There are a number of dimensions along
which the complexity arises:
x Cross-Media: evidence is often distributed in different
media; it is possible that knowledge expressed in just one
medium does not carry enough evidence. Connecting
information in more than one medium is often required.
x Knowledge integration: large distributed archives require
the ability to map the distribution of information, to weight
every single source and to distribute searches carefully; this
is very difficult and often search is performed just in some of
the archives, disregarding others that can bring very useful
information;
x Focusing: large amount of information implies that
managing knowledge becomes more complex and needs
powerful focusing methodologies. Focus of searching
changes in time and from user to user, and requires a
balanced mixture of exploration and searching;
x Uncertainty and Dynamicity: information is often
ambiguous, incomplete, or referring to a specific context
therefore archives can contain noise and imprecision, as well
as obsolete information; each piece of knowledge must
therefore be judged based on provenance, evidence, etc.
x Infrastructure: different media cannot easily be shared. A
folder of text documents may be sent via email, but a folder
of images may not, and may instead require a shared image
repository. For 10 GByte of data remote access to the
underlying data base is to be considered.</p>
      <p>Current knowledge management technologies and practises
cannot cope with such new situation, as they mainly provide
simple mechanisms (e.g. keyword searching) for supporting
knowledge workers manually pierce together the information
from different sources.</p>
    </sec>
    <sec id="sec-2">
      <title>II. X-MEDIA</title>
      <p>X-Media addresses the issue of knowledge management in
complex distributed environments. It studies, develops and
implements large scale methodologies and techniques for
knowledge management able to support sharing and reuse of
knowledge that is distributed in different media (images,
documents and data) and repositories (data bases, knowledge
bases, document repositories, etc.).</p>
      <p>X-Media studies, designs and develops:
1) Robust and scalable knowledge acquisition and data
analysis tools operating across media boundaries (text,
images and data) to automatically cross-relate and annotate
text and images with metadata.
2) Novel and cutting-edge knowledge fusion methods to
support knowledge workers in making decisions when
confronted with – possibly contradicting – knowledge
derived from different resources;
3) Effective and efficient new paradigms for knowledge
retrieval, sharing and reuse working across media which
enable users to define and parameterize views on the
available knowledge according to their needs.
4) Techniques able to represent and manage (i) uncertainty,
(ii) trust and provenance as well as (iii) dynamic aspects of
knowledge;
5) A methodology and a technical infrastructure able to
deliver knowledge from across media to the knowledge
workers, taking into account the complexity of managing
different media with different size of data.
6) A generic and flexible architecture allowing end users to
easily customize it and integrate it with their KM practices
or needs as well as a mainly open source reference
implementation and libraries which technology providing
companies can reuse.</p>
      <p>Technologies will be able to support knowledge workers in an
effective way, (i) hiding the complexity of the underlying
search/retrieval process, (ii) resulting in a natural access to
knowledge, (iii) allowing interoperability between
heterogeneous information resources and (iv) including
heterogeneity of data type (data, image, texts). The expected
impact on organizations is to dramatically improve access to,
sharing of and use of information by humans and between
machines. Expected benefits are a dramatic reduction of
management costs and increasing feasibility of complex
knowledge management tasks. The project plan is structured
along the four areas described below.</p>
      <sec id="sec-2-1">
        <title>Area 1: knowledge sharing and reuse</title>
        <p>X-Media studies and implements technologies and
methodologies for easy and intelligent access to and reuse of
formalized and non formalized knowledge. The reuse takes
into consideration the user context to help focus searches and
reuse. Reuse and sharing is enabled via cross-media ontology
supported automatic indexing. The technology works in a
largely automated way, but it is centered on supporting users’
work, rather than replacing them. This is because the activity
of a knowledge worker is complex and humans are
irreplaceable agents in this process.</p>
        <p>In this context, we are studying, designing and developing:
(1) Effective and efficient new paradigms for knowledge
retrieval, sharing and reuse which enable users to define and
parameterize views on the available knowledge according to
their needs.
(2) Novel and cutting-edge knowledge fusion methods to
support knowledge workers in making decisions when
confronted with – possibly contradicting – knowledge
derived from different resources.
(3) techniques able to represent and manage (i) uncertainty, (ii)
trust and provenance as well as (iii) dynamic aspects of
knowledge.</p>
      </sec>
      <sec id="sec-2-2">
        <title>Area 2: automated knowledge acquisition from documents, images and raw data</title>
        <p>Functional to the methodologies for knowledge sharing
investigated in Area 1, is the ability to acquire knowledge
across media in a rich, semantically-oriented way. X-Media
develops a set of tools able to support sharing methodologies
in a seamless and automatic way. Media addressed are raw
data, texts and images (e.g. results or parameters in
experiments, raw images, textual documents, etc.). The
outcome of the acquisition technologies will be a semantic
representation of the content (conceptualization) to be used for
knowledge management purposes. Enrichment of multimedia
documents with additional layers of automatically generated
annotation is the main medium of associating
conceptualizations to resources. Current technology focuses on
single medium technologies to acquire knowledge in multi
media environments; this means that retrieval methods use
mainly one medium (e.g. text) even in multimedia
environments. X-Media designs and develops technologies for
information extraction that work truly cross media and that can
be used in cases where information in one medium is necessary
to understand the information in the other.</p>
      </sec>
      <sec id="sec-2-3">
        <title>Area 3: Infrastructure</title>
        <p>A knowledge acquisition, integration and sharing environment
is defined. Since X-Media is an application-oriented
integrated project, integration is required on the
implementation as well as on the conceptual level. The main
outcome of this area of activity will be a methodology and a
technical infrastructure able to deliver knowledge from across
media to the knowledge workers, taking into account the
complexity of managing media with different size of data.</p>
      </sec>
      <sec id="sec-2-4">
        <title>Area 4: Application and Testing</title>
        <p>The technology above is used to define showcases and
prototype applications. Two main testbeds are defined by the
two industrial users (Rolls Royce and Fiat). They concern
competitor analysis in the car industry and product lifecycle
monitoring in aerospace. System trials with final users will
showcase the technology and pave the way to further
exploitation.</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>III. CONSORTIUM</title>
      <p>Partners: University of Sheffield (coordinator, UK),
University of Koblenz (D), ITC-Irst (I), University of
Ljubljana (Slovenia) University of Freiburg (D), CERTH (G),
Labri (F), University of Karlsruhe (D) and the Open
University (UK). Quinary (I), Ontoprise (D), Solcara (UK),
CognIT (N), Rolls Royce (UK) and Centro Ricerche Fiat (I).</p>
    </sec>
    <sec id="sec-4">
      <title>ACKNOWLEDGMENT X-Media is funded by the European Commission as part of Framework 6 of IST, contract no FP6-26978. Project web page: http://www.x-media-project.org.</title>
    </sec>
    <sec id="sec-5">
      <title>For information: Prof. Fabio</title>
      <p>xmedia-coordinator@dcs.shef.ac.uk</p>
    </sec>
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