AIM@SHAPE: Research Advantages and Future Contributions B. Falcidieno, M. Spagnuolo, M. Pitikakis, G. Vasilakis, A. Garcia-Rojas, L. Papaleo  representation of digital shapes. Knowledge conceptualization Abstract— Searching for multi-dimensional media is gradually using ontologies provides the means to map terms to concepts, becoming one of those intriguing research topics that have the and not only to associate meaning to the user query but also to potential to shape how users will access and interact with the reason on the knowledge space and deduce potential implied internet in the years to come. Multi-dimensional media, however, are generally related to complex objects, and, moreover, to the information that is not directly associated with queries. This different semantics that different applications and tools use while puts an entirely new perspective on the process of modelling, dealing with them. In the AIM@SHAPE Network of Excellence accessing and retrieving digital shapes. [1], one of the main objectives is to deal with the knowledge that There are obvious advantages in semantic searching like is either explicitly or implicitly associated to digital shapes and to improving the relevance of the retrieved resources and formalize the underlying semantics through the use of ontologies. enabling us to explore resources that are indirectly related to Modelling the semantics of shape objects constitutes a concrete step in developing an effective semantics-oriented search the query. mechanism for 3D resources. This mechanism is part of the Digital Shape Workbench infrastructure within AIM@SHAPE. II. THE AIM@SHAPE APPROACH In this context, the main objective of the Network of I. INTRODUCTION Excellence AIM@SHAPE is twofold. On the one hand to T HE Web provides a means to share information and resources among user communities (scientists, enterprises, etc.) and the wider public in general. As such, it provides easy develop tools and methods to extract morphological structures from low-level geometry and to capture the implicit semantic information of digital shapes. On the other hand to formalize access to a huge amount of information. Due to the sheer the domain knowledge into context-dependent ontologies and amount of available 3D shapes and the growing complexity of introduce knowledge management techniques in shape the resources being made available, it has become increasingly modelling, with the aim of making explicit and sharable the important to effectively manage digital shape resources and knowledge embedded in digital shapes. information (i.e., multi-dimensional media characterized by a AIM@SHAPE aims to address the need of a new approach visual appearance in a space of 2, 3, or more dimensions). to store and retrieve shapes, tools and publications related to This has motivated the development of the first prototypes the field of shape modelling. The proposed framework relies of 3D shape retrieval mechanisms that are currently based on the Digital Shape Workbench (DSW) and on a mainly on geometric matching techniques, with rather limited conceptualization of applications domains of shape modelling results [2],[3]. techniques, providing a characterization of the relevant Recent developments in the Semantic Web provide the resources and their related knowledge in order to retrieve means for making the shift towards a semantically enabled them with a sufficient expressiveness. The DSW consists of the resources repositories (the Shape Repository, the Tools Repository and the Digital Library), a knowledge This work was supported by the EC under the FP6 IST NoE 506766. management system that handles metadata and ontologies, and B. Falcidieno is the Director of the Institute of Applied Mathematics and Information Technology, CNR, Via De Marini 6, IT-16149 Genova, Italy (e- a number of different ways of discovering, searching and mail: bianca.falcidieno@ge.imati.cnr.it). browsing shape resources. M. Spagnuolo, is a Senior Researcher with the Institute of Applied The primary goal of the DSW is the formalization and Mathematics and Information Technology, CNR, Via De Marini 6, IT-16149 Genova, Italy (e-mail: michela.spagnuolo@ge.imati.cnr.it). sharing of knowledge about digital shapes and their M. Pitikakis is an Associate Researcher with the Informatics and applications. The main objectives of the DSW are: Telematics Institute, CERTH, 1st Km Thermi-Panorama Road, GR-57001 1) To build the necessary framework (Search Engine) for Thessaloniki, Greece (e-mail: pitikak@iti.gr). reasoning, searching and interacting with the semantic G. Vasilakis is an Associate Researcher with the Informatics and Telematics Institute, CERTH, 1st Km Thermi-Panorama Road, GR-57001 content related to the context-dependent domain Thessaloniki, Greece (e-mail: vasilak@iti.gr). knowledge (ontologies). A. Garcia-Rojas is a PhD student with the EPFL, Virtual Reality Lab, 2) To improve current content-based methods for retrieving Station 14, CH-1015 Lausanne, Switzerland (e-mail: alejandra.garciarojas@epfl.ch). shapes on the Web, and 3D media in particular, coupling L. Papaleo is a Researcher with DISI, Università di Genova, Via advanced geometric techniques with semantic criteria on Dodecaneso, 35, IT-16146 Genova, Italy (e-mail: papaleo@disi.unige.it). the metadata associated with shape resources (ontology- domain ontologies and the DSW. driven metadata information organized in domain 4) Integrate and validate the ontologies and the ontologies). corresponding metadata. Due to the intrinsic complexity of shapes, ontology-driven Ontology development in the network has been mainly metadata are necessary in order to reach a sufficient level of focused on three different areas: Virtual Humans, Shape expressiveness and to be able to search efficiently for shapes. Acquisition and Processing, and Product Design. These metadata represent different levels of sophistication, The Virtual Humans ontology [4] aims at organizing the describing and characterizing a shape resource. For example, a knowledge and data related to research and applications in the search could be conducted presenting as criteria the geometric field of virtual environments and humans : the modelling and aspect of the shape, its structure or its semantics. analysis of virtual human body, and their animation and Some possible query categories include the following: interaction with virtual objects. 1) Concept based search (ontology-driven). The Shape Acquisition and Processing ontology [5] intends 2) Search for a shape with specific geometric characteristics to formalize the knowledge pertaining the development, usage (e.g., manifold models, models without self- and sharing of hardware and software tools and shape data by intersections), format (e.g. wrl or off), application context researchers and experts in the field of shape acquisition and (e.g., CAD, human models, furniture), name, produced by processing [6]. a specific tool, history etc. The objective of the Product Design ontology is to guide 3) Search for a shape that resembles, globally or partially, a researchers and experts in the development of tools and given shape. methods for: supporting industrial product design and 4) Search for tools dealing with a specific application engineering analysis, dealing with knowledge concerning context (e.g., similarity, remeshing), name, input or shape processing methods and algorithms, and knowledge output format, specific performance requirements etc. about processes and workflows regarding product 5) Search for a methodology (e.g. similarity, remeshing). In development phases. this case both tools and scientific papers dealing with that Concepts that are shared by all domain ontologies have lead methodology can be retrieved. also to the creation of two common ontologies, one related to 6) Range-based search e.g. “Give me the shapes having a shapes and one to shape processing tools, as a first attempt for number of polygons between 100 and 150”. a unified multi-dimensional media ontology framework. Our 7) Search for a specific user/researcher/publication. goal is to create higher-level ontologies which can be The fundamental goal of the Search Engine framework is extended by the domain ontologies to express metadata for not simply searching for and retrieving multi-dimensional each domain ontology. objects. Rather, we are interested in searching for every aspect The common ontologies aim to capture and integrate all the of knowledge that is inherent to the representation of shapes. metadata information from the Shape Repository, and the Tool However, for a user to be able to take full advantage of the Repository. These information are shared by all the domain search facilities it should be clear how the domain knowledge ontologies because they all deal with the same kind of has been conceptualized and structured according to some information (e.g., geometrical information). ontology specification. ACKNOWLEDGMENT III. ONTOLOGY DEVELOPMENT IN AIM@SHAPE The authors would like to express their gratitude to all The motivation behind the development of ontologies in AIM@SHAPE partners. 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