Mon May 5 10:37:01 CEST 2014

Dear Colleagues,

Please consider contributing to the event below, of interest to anyone 
working on time-stamped data sets,
and aimed at fostering interdisciplinary scientific exchanges.
Best regards,
J.Y Blaise



16-17 September 2014, in conjunction with i-KNOW 2014 Graz, Austria,
14th International Conference on Knowledge Technologies and Data-driven 

::::::::::::::: Deadlines EXTENDED :::::::::::::::

- Submission deadline: May 15, 2014
- Notifications: May 26, 2014
- Camera-ready version: June 7, 2014
- Workshop 16-17 September 2014


web site:

::::::::::::::: Context and motivation

In a number of application fields, pieces of data and information need 
to be modelled and visualised so as to analyse patterns of change over 
time, or so as to pinpoint time-related causal chains. Briefly said, 
understanding facts often implies understanding processes that lead to 
facts, or that derive from facts – and reasoning on processes implies 
mastering the time parameter.
However, coping with dirty time-oriented data (inaccurate, incomplete, 
erroneous, contradictory, etc.) remains, by and large, an open issue. If 
scientists and practitioners are to foster the emergence of effective 
solutions, it is of great importance they get an opportunity to confront 
their approaches, ideas, experiences and methods.
The workshop’s ambition is to foster interdisciplinary scientific 
exchanges both on theoretical or technological aspects and on practical 
cases/feedbacks stemming from a wide range of application fields.

::::::::::::::: Topics of interest

Handling “dirty” time-oriented data is naturally a key issue in human 
sciences, yet the issue is more generally raised in all activities where 
unreliable and/or incomplete and/or inaccurate temporal data sets have 
to be dealt with. The workshop wishes to host contributions covering a 
wide range of application fields, of scientific practices, and of 
theoretical or methodological approaches (historical sciences, 
environmental sciences, geosciences, conceptual modelling, health 
sciences, monitoring and planning activities, etc.). Accordingly, we 
welcome submissions related to (but not limited to) the handling of 
imperfect time-stamped information sets in the following research areas:

Knowledge Representation, Visual Analytics & Information Visualisation
• Temporal knowledge discovery, databases.
• Temporal logic, temporal representation and reasoning.
• Uncertainty modelling, data and information quality.
• Information visualisation, visual representations and interaction 
• Visualisation of temporal or spatio-temporal data.
• Process and workflow visualisation.

• Geovisualisation, geovisual analytics.
• Simulation, multi-agent systems.
• Geography, geomatics, time geography, mobility, flows, etc.
• Urban planning, landscape analysis & monitoring, etc.
• Risk assessment, climate research.

Historical Sciences, Health Sciences, Social Sciences
• Archaeology, environmental archaeology, paleoethnobotany.
• Ethnology, ethnography, linguistics, etc.
• History, history of art and architecture, etc.
• ITC in health services.
• Intelligence, social networks, etc.
• Business intelligence.

::::::::::::::: Location

Graz, Austria, (Messe Congress Graz , <>);
in conjunction with i-KNOW 2014 , Graz University of Technology, Know 
Center <>

::::::::::::::: Submissions

Submissions are invited on the above topics, either as short papers (4 
pages) - position papers, test cases -
or as regular contributions (8 pages).
Submissions will be reviewed by the workshop's Programme Committee in an 
interdisciplinary approach
(cross-examination from the application field point of view and from a 
KR perspective).

All  selected  papers  will  be  published  in  the  workshop  notes,  
either  in
conjunction with the conference proceedings or online as part of an Open 
Access peer-reviewed journal.
Formatting guidelines here : <>.
Submission page: <>.

- Submission deadline: May 15, 2014
- Notifications: May 26, 2014
- Camera-ready version: June 7, 2014

::::::::::::::: Event format and expected outcomes

The event will combine a “traditional” workshop format - keynotes 
focusing on dirty time-oriented data as such and talks focusing either 
on theoretical or technological aspects or on feedbacks from a variety 
of application fields - and a collective initiative aimed at pulling 
together test cases and resources (interdisciplinary references on one 
hand, and on the other hand test benches freely usable by the community 
in its subsequent work). Expected outcomes of this workshop accordingly 
include a better acquaintance with relevant work across scientific 
domains and application fields as well as the emergence of ad-hoc 
metrics – an attempt to ease the task of cross-examining responses to 
data quality issues.
Ultimately, the initiative wishes to contribute to the strengthening of 
the community of analysts dealing with quality issues in the context of 
temporal data and information sets.

::::::::::::::: Programme Committee

F. Bertoncello - CNRS, France
A. Bertone -Technical University Dresden, Germany
P. Buono - University of Bari, Italy
P.A. Davoine – University of Grenoble, France
J. Kehrer - Vienna University of Technology, Austria
C. Kinkeldey - HafenCity University Hamburg, Germany
O. Klein - CEPS, Luxembourg
E. Leclercq – University of Burgundy, France
J. Ma - University of Greenwich, United Kingdom
N. Mahmood- KICT, IIU, Malaysia
H. Mathian – CNRS, France
K. Matoušek - Czech Technical University, Czech Republic
T. Nocke - Potsdam Institute for Climate Research, Germany
D. O'Sullivan - University of California, Berkeley, USA
T. Pellegrini - St. Poelten University of Applied Sciences, Austria
A. Raffaetà - University of Venice, Italy
C. Renso - CNR, Italy
V. Sabol – TU Graz, Know-Center, Austria
H. Senaratne - University of Konstanz, Germany
C. Stasch - University of Muenster, Germany
M. Streit - JKU Linz, Austria

::::::::::::::: Organisers

W. Aigner, St. Poelten University of Applied Sciences, Austria
J.Y. Blaise, I. Dudek, CNRS (UMR 3495 CNRS/MCC MAP), France
T. Gschwandtner, Vienna University of Technology, Austria

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