Semantic based visualization: a first approach

Visualization is the process of mapping data into visual dimensions to create a visual representation to amplify cognition. Visual representations are essential aids to human cognitive tasks and are valued to the extent that they provide stable and external reference points upon which dynamic activities and thought processes may be calibrated and upon which models and theories can be tested and confirmed. The active use and manipulation of visual representations makes many complex and intensive cognitive tasks feasible. A visual representation is able to convey relationships among many elements in parallel and provides an individual with directly observable memory. A successful visualization allows the user to gain insight into the data, in other words to communicate different aspect of the data in an effective way. Even with today’s visualization systems that give the user a considerable control over the visualization process, it can be difficult to produce an effective visualization. To obtain useful results, a user had to know which questions to pose. Problems had to be framed in very precise terms. A strategy to improve this situation is to guide the user in the selection of the parameters involved in the visualization. Our research goal is the design of a visualization system that assist the user to do the work, by considering the semantic of the data together with the semantic of the stages through all the visualization process.Eje: Computación Gráfica, Visualización e ImágenesRed de Universidades con Carreras en Informática (RedUNCI

Semantics-based visualization

Visualization is the process of mapping data into visual dimensions to create a visual representation to amplify cognition. Visual representations are essential aids to human cognitive tasks. They are valued to the extent that they provide stable and external reference points upon which dynamic activities and thought processes may be calibrated and upon which models and theories can be tested and confirmed. The active use and manipulation of visual representations makes many complex and intensive cognitive tasks feasible. A visual representation is able to convey relationships among many elements in parallel and provides an individual with directly observable memory. A successful visualization allows the user to gain insight into the data, i.e. to communicate different aspect of the data in an effective way. Even with today’s visualization systems that give the user a considerable control over the visualization process, it can be difficult to produce an effective visualization. To obtain useful results, a user had to know which questions to pose; problems had to be framed in very precise terms. A strategy to improve this situation is to guide the user in the selection of the parameters involved in the visualization. Our research goal is the design of a visualization system that assist the user in the construction of the visualization, by considering the semantic of the data, the semantic of the stages through all the visualization process and the semantic of the external elements affecting the visualization.Presentado en el Encuentro de Tesistas de PostgradoRed de Universidades con Carreras en Informática (RedUNCI

A common ontology for multi-dimensional shapes

In recent years, digital shapes have become more and more widespread and have been made available in a plethora of online repositories. A systematic and formal approach for capturing and representing shape-related information is needed to facilitate its reuse and enable the demonstration of useful cross-domain usage scenarios. In this paper we present an ontology for digital shapes, called the Common Shape Ontology (CSO). We discuss the rationale, the requirements and the scope of this ontology, we present in detail its structure and describe the most relevant choices related to its development. Finally, we show how the CSO conceptualization is used in domain-specific application scenarios

Semantics-based visualization

Visualization is the process of mapping data into visual dimensions to create a visual representation to amplify cognition. Visual representations are essential aids to human cognitive tasks. They are valued to the extent that they provide stable and external reference points upon which dynamic activities and thought processes may be calibrated and upon which models and theories can be tested and confirmed. The active use and manipulation of visual representations makes many complex and intensive cognitive tasks feasible. A visual representation is able to convey relationships among many elements in parallel and provides an individual with directly observable memory. A successful visualization allows the user to gain insight into the data, i.e. to communicate different aspect of the data in an effective way. Even with today’s visualization systems that give the user a considerable control over the visualization process, it can be difficult to produce an effective visualization. To obtain useful results, a user had to know which questions to pose; problems had to be framed in very precise terms. A strategy to improve this situation is to guide the user in the selection of the parameters involved in the visualization. Our research goal is the design of a visualization system that assist the user in the construction of the visualization, by considering the semantic of the data, the semantic of the stages through all the visualization process and the semantic of the external elements affecting the visualization.Presentado en el Encuentro de Tesistas de PostgradoRed de Universidades con Carreras en Informática (RedUNCI

Semantic based visualization: a first approach

Visualization is the process of mapping data into visual dimensions to create a visual representation to amplify cognition. Visual representations are essential aids to human cognitive tasks and are valued to the extent that they provide stable and external reference points upon which dynamic activities and thought processes may be calibrated and upon which models and theories can be tested and confirmed. The active use and manipulation of visual representations makes many complex and intensive cognitive tasks feasible. A visual representation is able to convey relationships among many elements in parallel and provides an individual with directly observable memory. A successful visualization allows the user to gain insight into the data, in other words to communicate different aspect of the data in an effective way. Even with today’s visualization systems that give the user a considerable control over the visualization process, it can be difficult to produce an effective visualization. To obtain useful results, a user had to know which questions to pose. Problems had to be framed in very precise terms. A strategy to improve this situation is to guide the user in the selection of the parameters involved in the visualization. Our research goal is the design of a visualization system that assist the user to do the work, by considering the semantic of the data together with the semantic of the stages through all the visualization process.Eje: Computación Gráfica, Visualización e ImágenesRed de Universidades con Carreras en Informática (RedUNCI

Semantic Modelling of Interactive 3D Content with Domain-specific Ontologies

AbstractThe creation of interactive 3D presentations is typically a complex process involving activities related to various aspects of the content such as geometry, structure, space, appearance, logic and behaviour. However, widespread dissemination of interactive 3D content on the web requires flexible and efficient methods of content creation. In this paper, an approach to semantic modelling of 3D content is proposed. The proposed solution enables creation of content components and properties - reflecting different aspects of the content - with domain-specific ontologies and knowledge bases. The use of domain-specific knowledge liberates authors from going into details that are specific to 3D modelling, allows for content representation at different levels of abstraction and permits content creation by domain experts, who are not required to be IT-professionals

Semantics-based color assignment in visualization

The active use and manipulation of visual representations makes many complex and intensive cognitive tasks feasible. A visual representation is able to convey relationships among many elements in parallel and it provides an individual with directly observable memory. A successful visualization allows the user to gain insight into the data, that is, to communicate different aspects of the data in an effective way. Even with today's visualization systems that give the user a considerable control over the visualization process, it can be difficult to produce an effective visualization. To obtain useful results, a user has to interrogate the visualization very precisely. A strategy to improve this situation is to guide the user with the selection of the parameters involved in the visualization. This paper presents the initial effort dedicated to achieve a visualization system that assists the user in the configuration and preparation of the visualization by considering both the semantic of the data and the semantic of the stages through all the visualization process. In this article we present a visualization system for file hierarchies where color assignment is made by a reasoning process through the use of an ontology. This work sets the way forward to integrate the visualization process with a reasoning process and configure a visualization based on the reasoner s results.Facultad de Informátic

TREE-D-SEEK: A Framework for Retrieving Three-Dimensional Scenes

In this dissertation, a strategy and framework for retrieving 3D scenes is proposed. The strategy is to retrieve 3D scenes based on a unified approach for indexing content from disparate information sources and information levels. The TREE-D-SEEK framework implements the proposed strategy for retrieving 3D scenes and is capable of indexing content from a variety of corpora at distinct information levels. A semantic annotation model for indexing 3D scenes in the TREE-D-SEEK framework is also proposed. The semantic annotation model is based on an ontology for rapid prototyping of 3D virtual worlds. With ongoing improvements in computer hardware and 3D technology, the cost associated with the acquisition, production and deployment of 3D scenes is decreasing. As a consequence, there is a need for efficient 3D retrieval systems for the increasing number of 3D scenes in corpora. An efficient 3D retrieval system provides several benefits such as enhanced sharing and reuse of 3D scenes and 3D content. Existing 3D retrieval systems are closed systems and provide search solutions based on a predefined set of indexing and matching algorithms Existing 3D search systems and search solutions cannot be customized for specific requirements, type of information source and information level. In this research, TREE-D-SEEK—an open, extensible framework for retrieving 3D scenes—is proposed. The TREE-D-SEEK framework is capable of retrieving 3D scenes based on indexing low level content to high-level semantic metadata. The TREE-D-SEEK framework is discussed from a software architecture perspective. The architecture is based on a common process flow derived from indexing disparate information sources. Several indexing and matching algorithms are implemented. Experiments are conducted to evaluate the usability and performance of the framework. Retrieval performance of the framework is evaluated using benchmarks and manually collected corpora. A generic, semantic annotation model is proposed for indexing a 3D scene. The primary objective of using the semantic annotation model in the TREE-D-SEEK framework is to improve retrieval relevance and to support richer queries within a 3D scene. The semantic annotation model is driven by an ontology. The ontology is derived from a 3D rapid prototyping framework. The TREE-D-SEEK framework supports querying by example, keyword based and semantic annotation based query types for retrieving 3D scenes