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Subject: [ E-CFP ] 1st CfP: DeRiVE 2013: 3rd Workshop on Events in the Semantic Web @ ISWC 2013
From: <marieke.van.erp_(on)_vu.nl>
Date received: 28 Apr 2013
Deadline: 12 Jul 2013
Start date: -

**Apologies for cross-posting**

3rd International Workshop on Detection, Representation, and
Exploitation of Events in the Semantic Web (DeRiVE 2013)

Workshop Web Site: http://derive2013.wordpress.com/ EasyChair:
http://www.easychair.org/conferences/?conf=derive2013 E-mail
address: derive2013_(at)_easychair.org Twitter Hashtag: #derive2013

*Important Dates*
- Deadline for paper submission: Friday, 12 July 2013, 23:59
  (Hawaiian time)
- Notification of acceptance/rejection: Friday, 9 August 2013
- Deadline for camera-ready version: Friday, 30 August 2013

*Workshop Summary* Events are at the heart of many of our daily
information sources, being microposts, newswire, calendar
information or sensor data. For detecting, representing and
exploiting events in these sources, different research
communities are each trying to resolve a small part of this
puzzle. The goal of this workshop is to bring together those
different areas in the recent surge of research on the use of
events as a key concept for representing and organising knowledge
on the Web. The workshop invites contributions to two central
questions and its goal is to formulate answers to these questions
that advance and reflect the current state of understanding and
application of events. Each submission will be expected to
address at least one question explicitly, if possible including a
system demonstration. This year, we have also made available a
challenge dataset based on sensor data and we specifically invite
contributions that link events in sensor data such as social web
and multimedia data using semantic web technologies. The most
substantial contributions to the workshop will be presented
orally (and if possible with a demo) in sessions organised
according to the questions addressed, with time allocated for
deep discussion.

* Motivation* In recent years, researchers in several communities
  involved in aspects of information science have begun to
  realise the potential benefits of assigning an important role
  to events in the representation and organisation of knowledge
  and media benefits which can be compared to those of
  representing entities such as persons or locations instead of
  just dealing with more superficial objects such as proper names
  and geographical coordinates. While a good deal of relevant
  research for example, on the modeling of events has been done
  in the semantic web community, much complementary research has
  been done in other, partially overlapping communities, such as
  those involved in multimedia processing, information
  extraction, sensor processing and information retrieval
  research. However, these areas often deal with events with a
  different perspective. The attendance of DeRiVE 2011 and DeRiVE
  2012 proved that there is a great interest from many different
  communities in the role of events. The results presented in
  there also indicated that dealing with events is still an
  emerging topic. The goal of this workshop is to advance
  research on the role of events within the semantic web
  community, both building on existing work and integrating
  results and methods from other areas, while focusing on issues
  of special importance for the semantic web.

*Topics* We have defined questions for the two main directions
that characterise current research into events on the semantic
web. Orthogonal to that, we have identified a number of
application domains in which we will actively seek contributions.

Question 1: How can events be detected and extracted for the
semantic web?
 - How can events be detected, extracted and/or summarized in
   particular types of content on the web, such as calendars of
   public events, social media, semantic wikis, and regular web
 - What is the quality and veracity of events extracted from
   noisy data such as microblogging sites?
 - How can a system recognise a complex event that comprises
   several sub-events?
 - How can a system recognise duplicate events?

Question 2: How can events be modelled and represented in the
semantic web?
 - How are events currently represented on the Web? In
   particular, how deployed is the schema.org Event class? To
   what extent can the many different event infoboxes of
   Wikipedia be reconciled?
 - How can existing event representations developed in other
   communities be adapted to the needs of the semantic web?
 - To what extent can/should a unified event model be employed
   for different types of events?
 - How do social contexts (Facebook, Twitter, etc.) change the
   implicit content semantics?

Research into detection (question 1) and representation (question
2) of events is being implemented in various application domains.
We encourage submissions about the visualization of events,
search and browsing of event data, and interaction with event
data within a particular domain. This will contribute to a
discussion on the possibly different requirements of models and
tools in these domains. Known application domains that we target
 - Personal events
 - Cultural and sports events
 - Events in sensor data and streaming data
 - Events in news and other media, historic events

*Data Challenge* With the data challenge, we would like to
stimulate participants to see to what extent sensor data can be
augmented with information from multiple sources, including LOD
datasets, social networks and websites. In particular, we would
like to see how situational awareness of maritime operators, such
as coastguards, can be improved by providing new actionable
information. The participants will be provided with a large data
set of AIS messages and a number of additional data sets, such as
a set of banned ships, all represented in RDF. The challenge is
to extend this data set with additional semantics derived from
the Web and the Linked Open Data cloud and to answer any number
of the following questions:

Questions about increasing situational awareness:
 - Which vessel has made the most sea miles?
 - What is the largest cruise ship in view?
 - What is the ownership graph of a vessel in view?
 - Can the vessels be categorized based on e.g. their behavioural
   patterns, their communication, their history, or their crew?

Questions about providing actionable information:
 - Which vessels in view could be hiding their identity, i.e.,
   provide information that is inconsistent with other sources?
 - If you were the coast guard and had the resources to inspect
   five vessels, which vessels would you investigate and for what
   reason? Reasons can vary from a history of smuggling and
   pollution to a Twitter message, and from an abnormal
   behavioural pattern to owners from a country under UN embargo.

Event is a critical entity for documenting information within in
wireless sensor network domain. Wireless sensor networks have
been widely deployed to provide scientists with valuable data
that measures and records information about our environment.
Hence, huge collections of wireless sensor data streams for
scientific research, together with the interdisciplinary nature
of scientific research lead to the following challenges:
 - How to derive from low-level sensor observations a high-level
   understanding of environmental, ecological, biological, human
   factors and their impacts?
 - How to utilize semantic web technologies to achieve integrated
   sensor data sources, especially when information from
   different sources is heavily heterogeneous and even
 - How to utilize semantic web technologies to handle large
   volumes of sensor observations which are spatial and temporal?
 - How to semantically link public sensor observations to
   scientific measurements produced by technical sensors or
   forecasting models?
 - How to incorporate insights from knowledge engineering, data
   mining, environmental science, ecological science, semantic
   sensor web, and biomedical science into general solutions for
   representing and understanding high level events?
 - How to incorporate domain expert knowledge to infer high level
   events and their relationships?
 - How to prevent undesirable activities (collisions, smuggling,
   environmental pollution) using the events extracted from the
   combined data sources?

*Submissions* Submissions should not exceed 10 pages and are to
be formatted according to Springer LNCS guidelines
(http://www.springer.com/computer/lncs?SGWID=0-164-7-72376-0) and
submitted to
https://www.easychair.org/conferences/?conf=derive2013. Papers
should be submitted in PDF format. The workshop proceedings will
be published online through CEUR-WS.

*Chairs* Marieke van Erp, VU University Amsterdam Laura Hollink,
VU University Amsterdam RaphaIl Troncy, EURECOM Willem Robert van
Hage, SynerScope B.V. PiIrre van de Laar, TNO David A. Shamma,
Yahoo! Lianli Gao, University of Queensland

*Program Committee* Jans Aasman, Franz Inc., USA Eneko Agirre,
University of the Basque Country, Spain Pramod Anantharam,
Knoesis, USA Michael Compton, CSIRO, Australia Christian Hirsch,
University of Auckland, New Zealand Jane Hunter, University of
Queensland, Australia Pavan Kapanipathi, Knoesis, USA Azam Khan,
Autodesk Research, Canada Jan Laarhuis, Thales, The Netherlands
Erik Mannens, Ghent University - IBBT, Belgium Ingrid Mason,
Intersect, Australia Diana Maynard, University of Sheffield, UK
Giuseppe Rizzo, EURECOM, France Matthew Rowe, Lancaster
University, UK Ryan Shaw, University of North Carolina at Chapel
Hill, USA Thomas Steiner, Google Inc, Germany Kerry Taylor, CSIRO
& Australian National University, Australia

Computational Lexicology & Terminology Lab (CLTL) The Network
Institute, VU University Amsterdam

Room 11A-26, De Boelelaan 1105 1081 HV Amsterdam, The Netherlands
http://www.mariekevanerp.com http://www.newsreader-project.eu

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