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Short information on the Network of Excellence Advanced and Innovative Models and Tools
for the development of semantic-based systems
for Handling, Acquiring, and Processing knowledge embedded in multidimensional digital
objects.
Started January 1, 2004
Call FP6/2002/IST/1
Key action 2.3.1.7. Semantic-based Knowledge System
Download:
1st newsletter (June 2004)
2nd newsletter (October 2004)
3rd newsletter (June 2005)
4th newsletter (November 2005)
5th newsletter (June 2006)
6th newsletter (November 2006)
7th newsletter (Juner 2007)
8th newsletter (November 2007)
Project summary
The multimedia world can be classified into one-dimensional media like
text and sound, and multi-dimensional media. Among the latter, those that
are characterised by a visual appearance in a space of 2, 3, or more dimensions
are called shapes. Examples of shapes are pictures, sketches, images, 3D
models of solid objects, videos (disregarding the sound track), 4D (=3D+Time)
animations, etc. Shapes are expected to take a central role in the Semantic
Web in the next years, with high potential impact in several key areas.
Consumer PCs are now all equipped with high-performance 3D graphics hardware.
Considering that most of these PCs are connected to the Internet, it seems
clear that in the near future 3D data will represent a huge amount of traffic
and data stored in the Internet. It has been predicted that geometry is
poised to become the fourth wave of digital multimedia communication, where
the first three waves were sound in the 1970s, images in the '80s, and
video in the '90s. So if the principal use of PCs is currently related
to 2D image processing and visualization (if one restricts to multimedia
content), the next step is to add new dimensions (3D geometry, 4D, i.e.
time-dependent, geometry) to this information content and endow it with
knowledge (semantics).
The mission of AIM@SHAPE is to advance research in the direction of
semantic-based shape representations and semantic-oriented tools to acquire,
build, transmit, and process shapes with their associated knowledge. We
foresee a generation of shapes in which knowledge is explicitly represented
and, therefore, can be retrieved, processed, shared, and exploited to construct
new knowledge.
This new approach in shape research is to be created by:
the formalisation of shape knowledge and the definition of shape ontologies
in specific contexts
the definition of shape behaviours which formalise the interoperability
between shapes
the delineation of methods for knowledge-based design of shapes
the definition of tools for semantics-dependent mapping of shapes.
This scientific goal of AIM@SHAPE is ambitious, and it can be achieved
only by establishing the infrastructures necessary for growing a new multidisciplinary
research field, where excellence in Computer Graphics and Vision, Computational
Mathematics, Geometric Modelling, Computer Science, CAD and Engineering,
joins state-of-the-art Knowledge Technologies.
The scientific innovation sought by AIM@SHAPE will be high in terms
of the new methodological approach to model digital shapes. Current information
systems may handle the geometric representation of digital shapes, but
not their semantics (meaning or functionality) in a given context. Scientific
innovation will be also high in terms of proposing and developing ontologies
for modelling digital shapes and their semantics in key applied sectors.
Up to now, the efforts in this direction only touch the visual appearance
of 3D objects (geometry) but not the meaning of the shape in a specific
sector.
Technological innovation will be high in terms of tools for the automated
semantic annotation of digital shapes, as well as tools for accounting
for the semantics while digitising, modelling, and sharing shape data.
The innovation will be measured against the existence of a coherent and
integrated Digital Shape Workbench (DSW) and its use as an e-Science framework
of tools and services for modelling, processing and interpreting digital
shapes.
The AIM@SHAPE consortium of 14 excellent research institutions in foundational
and applied fields of shape modelling will pursue lasting integration both
at the foundational level, by initiating a new Theory of Digital Shapes,
and at the component level, by developing a Digital Shape Workbench as
a common platform for shape models and software tools. Integrating activities
will include the design of a common shape ontology and a program for human
capital mobility and training. Spreading of excellence activities will
include an international forum, an industrial users' group and regular
conferences.
Project objectives
AIM@SHAPE is aimed at coordinating research on representing, modelling
and processing knowledge related to digital shapes, where by shape it is
meant any individual object having a visual appearance which exists in
some (two-, three- or higher- dimensional) space (e.g., pictures, sketches,
images, 3D objects, videos, 4D animations, etc.). Digital shapes are digital
representations of either physically existing objects or virtual objects
that can be processed by computer applications. Digital shapes occur and
are used in many different environments such as: Industrial Design (e.g.,
CAD models of products, laser-scanned prototypes), Medical Applications
(e.g., tomography or X-rays), Entertainment (e.g., computer animations,
virtual actors), Personal Environments (e.g., pictures or videos), Geographical
Information Systems (e.g., maps or three-dimensional models of terrains),
and many more. The concept of digital shape therefore encompasses all instances
of objects which can be represented in a digital context, irrespectively
of their format, use, dimension, provided that they have a geometric nature,
that is, they are primarily characterised by their form or spatial extent.
What is common to all shapes is that they all have a geometry (the
spatial extent of the object), they can be described by structures (object
features and part-whole decomposition), they have attributes (colours,
textures, names, attached to an object, its parts and/or its features),
they have a semantics (meaning, purpose), and they may also have interaction
with time (e.g., history, shape morphing, animation, video).
While the technological advances in terms of hardware and software
have made available plenty of tools for using and interacting with the
geometry of shapes, the interaction with the semantic content of digital
shapes is still far from being satisfactory. While we have tools for viewing
digital shapes even in much unspecialised web contexts (e.g. browser plug-ins
like SVG or VRML for 3D shapes), we miss tools for interacting with the
semantics of digital shapes. It is not possible, for example, to search
digital shapes by their semantic meaning. This is partly due to the lack
of methods for the automatic extraction of the semantic content of digital
shapes (semantic annotation) and partly to the evolution of research on
shape modelling which had to be highly focused, in the past years, on the
geometric aspects of shapes. The shift from a purely geometric to a semantic-aware
level of representation of digital shapes is the ultimate scientific objective
of AIM@SHAPE. For the next generation of semantic-enabled systems and services,
we foresee a generation of shape models in which knowledge/semantics is
explicitly represented and, therefore, can be effectively retrieved, shared,
exploited, and used to construct new knowledge.
The scientific objective will be achieved by growing a new multi-disciplinary
research field, which deeply integrates Computer Graphics and Vision with
Knowledge Technologies. The core of the integration will reside in the
homogenisation of the approach to modelling shapes and their associated
semantics using knowledge formalisation mechanisms, in particular metadata
and ontologies which will provide the rules for linking semantics to shape
or shape parts. Through a common formalization framework, it will be possible
to build a shared conceptualisation of a multi-layered architecture for
shape models, where the simple geometry is organized in different levels
of increasing abstraction: geometric, structural and semantic layers.
Network Interested Researcher Group (NIRG)
AIM@SHAPE is open to researchers’ partnerships through the Network Interested Researcher Group (NIRG) (See http://www.aimatshape.net/get_involved/NIRG/). Current subscribers are from Brazil, China, Italy, Spain and The Netherlands, making it a truly world-wide initiative.
Advantages in becoming a NIRG member are:
- Opportunities for integration of research activities with 14 prestigious research institutes
- Facilitated access to common resources (Shape and Software Repositories) and the possibility to include your papers in the AIM@SHAPE Digital Library
- Regular update on the new developments in the AIM@SHAPE Network Of Excellence (newsletter)
- Participation to AIM@SHAPE training activities
- Link to your EU project directly from the AIM@SHAPE web portal (if applicable) to increase project's visibility and clustering of research
- Opportunities for organizing joint workshops and official AIM@SHAPE presentations.
Join the NIRG Initiative!
To know how to join the AIM@SHAPE research community check out the NIRG web page on the AIM@Shape portal http://www.aimatshape.net/get_involved/NIRG/ and contact the following network members:
Bianca Falcidieno (Project Coordinator)
bianca.falcidieno@ge.imati.cnr.it
Giuliana Ucelli (NIRG Responsible)
giuliana.ucelli@graphitech.it.
The Network Industrial Group (NIG)
Companies interested in the Network outcomes form the NIG.
These companies will be regularly informed about the ongoing actions.
Their expertise will be used to:
identify industrial open problems related to shape issues
tune the research activities to address industrial needs
evaluate the research outcomes.
Members of the NIG will be called upon to act as industrial advisors
to support the Managing Board and advise the General Assembly whenever
needed, especially in matters concerning possible industrial exploitation
of network results.
The continuous communication among AIM@SHAPE and NIG Partners will
improve the set-up of targeted Research and Development projects, supported
at national or international level, and possibly co-funded by the companies
themselves. NIG companies will also play an important role in the development
of new curricula for master and PhD students within the network, since
they will provide facilities for short "stages"). This will offer a twofold
advantage:
for the students it provides an industrial experience which will
help them in their job decision,
for the companies it gives an opportunity for the recruitment of
people with the desired skill and know-how.
Participants
| Participant name |
Participant short name |
Country |
| C.N.R. - Istituto di Matematica Applicata e Tecnologie
Informatiche - Dept. of Genova |
CNR-IMATI-GE (Coordinator) |
Italy |
| Università di Genova - Dipartimento di Informatica
e Scienze dell'Informazione |
DISI |
Italy |
| École Polytechnique Federale de Lausanne |
EPFL |
Switzerland |
Fraunhofer Institut für Graphische Datenverarbeitung
Fondazione Graphitech |
FhG/IGD
GT |
Germany
Italy |
| Institut National Polytechnique de Grenoble |
INPG |
France |
| Institut National de Recherche en Informatique et Automatique |
INRIA |
France |
| Informatics and Telematics Institut - Center for Research
and Technology Hellas |
ITI-CERTH |
Greece |
| Université de Genève |
UNIGE |
Switzerland |
| Max-Planck-Institutfür Informatik |
MPII |
Germany |
| Stiftelsen for industriell og teknisk forskning ved
Norges Tekniske Høgskole |
SINTEF |
Norway |
| Technion - Israel Institute of Technology |
TECHNION |
Israel |
| Technische Universität Darmstadt |
TUD |
Germany |
| Utrecht University |
UU |
Netherlands |
| Weizmann Institute of Science |
WEIZMANN |
Israel |
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