On the Visualization of Semantic-based Mappings (original) (raw)

Ontology-Based Information Visualisation

2001

The Semantic Web is an extension of the current World Wide Web, based on the idea of exchanging information with explicit, formal and machine-accessible descriptions of meaning. Providing information with such semantics will enable the construction of applications that have an increased awareness of what is contained in the information they process and that can therefore operate more accurately. This has the potential of improving the way we deal with information in the broadest sense possible, e.g. better search engines, mobile agents for various tasks, or even applications yet unheard of. Rather than being merely a vision, the Semantic Web has significant backing from various institutes such as DARPA, the European Union and the W3C, which all have formed current and future Semantic Web activities.

Experiences of Knowledge Visualization in Semantic Web Applications

Advances in Intelligent and Soft Computing, 2011

There is an increasing need for usable tools to support knowledge elicitation, formalization and management. As an answer to this need, this paper describes fully integrated semantic web framework experiences, where users can represent and manage their data in a visual way, without the need of semantic web experts as intermediaries. These frameworks typically incorporate an ontology editor, a resource editor, reasoning capabilities and intuitive interaction and visualization facilities. The use of effective visualization techniques to graphically represent ontologies is investigated and the EasyOnto prototype is presented. In addition, different semantic web frameworks have been implemented as a result of research projects in different domains. In particular this paper presents the IRCS framework, an intelligent software to semantically index, search, and navigate the documentation used in water management plants, and the AWI environment, a collaborative environment aiming to collect and share knowledge of user communities, within the context of a digital factory.

Visualization and Management of Mappings in Ontology-based Data Access (Progress Report)

In this paper we present an in progress prototype for the graphical visualization and management of mappings for Ontology-based data access (OBDA). The tool supports the specification of expressive mappings linking a DL-Lite ontology to a relational source database, and allows the designer to graphically navigate them, according to various possible views, modify their textual representation, and validate their syntactic correctness. Furthermore, it gives preliminary support to the semantic analysis of the mappings, which aims to identify anomalies in the representation, like the specification of mapping queries that cannot return answers without contradicting the ontology. Such functionalities are currently being enhanced in our ongoing development of the tool.

VizThis: Rule-Based semantically assisted information visualization

Proceedings of the 3rd …, 2006

Information Visualization can be considered as the task of mapping data entities in a source file to representation artefacts in a target visualization format. As such, mapping plays a significant role in this process. The field of Ontology Mapping presents a wealth of work in the information mapping domain which we propose to exploit by applying it to Information Visualization for the Semantic Web. In this paper we describe a User Interface and a tool (VizThis) which demonstrates the proposed approach. We discuss the benefits which a mapping paradigm brings to Information Visualization, including automaticity and rule constraint. The system facilitates automatic mapping while still allowing users the ability to tweak the chosen mappings in order to improve the cognitive value of the visualizations. Additionally, the mapping choices available are constrained by rules governed by the characteristics of both the source and target format. A worked example is provided together with the results of a qualitative user evaluation of the resulting visualizations.

Visualization of mappings between schemas

Proceedings of the SIGCHI conference on Human factors in computing systems - CHI '05, 2005

In this paper we describe a novel approach to the visualization of the mapping between two schemas. Current approaches to visually defining such a mapping fail when the schemas or maps become large. The new approach uses various information visualization techniques to simplify the view, making it possible for users to effectively deal with much larger schemas and maps. A user study verifies that the new approach is useful, usable, and effective. The primary contribution is a demonstration of novel ways to effectively present highly complex information.

RROVT: A Proposed Visualization Tool for Semantic Web Technologies

Journal of Information Engineering …, 2012

Visualization is the graphical or semi-graphical representation of information that aids human comprehension of and reasoning about that information. Visualization tools are critically important for creating, querying, visualizing and validating Semantic Web Data. Semantic Web, an efficient infrastructure that enhances visibility of knowledge on the web, is often used more specifically to refer to the formats and technologies that enable it. These technologies include RDF, RDFS and OWL. However, lack of robust and efficient tools to visualize, analyze and represent these technologies within time and space constraint remains a big challenge. In this study, semantic web technologies and their visualization tools were reviewed. RROVT (RDF, RDFS, OWL Visualization Tool), a tool to evaluate and represent formal description of concepts, terms and relationships of data models within a given knowledge domain as well as manage time and space complexities for publishing contents of the semantic web more efficiently is developed and proposed. Performance of RROVT was investigated on samples of semantic web documents implementing RDF, RDFS and OWL technologies. The proposed tool showed remarkable improvement over the existing tools as it aids a better comprehension of the syntax and semantics of semantic web technologies investigated in this study.

Towards Self-explanatory Ontology Visualization with Contextual Verbalization

Databases and Information Systems, 2016

Ontologies are one of the core foundations of the Semantic Web. To participate in Semantic Web projects, domain experts need to be able to understand the ontologies involved. Visual notations can provide an overview of the ontology and help users to understand the connections among entities. However, the users first need to learn the visual notation before they can interpret it correctly. Controlled natural language representation would be readable right away and might be preferred in case of complex axioms, however, the structure of the ontology would remain less apparent. We propose to combine ontology visualizations with contextual ontology verbalizations of selected ontology (diagram) elements, displaying controlled natural language (CNL) explanations of OWL axioms corresponding to the selected visual notation elements. Thus, the domain experts will benefit from both the high-level overview provided by the graphical notation and the detailed textual explanations of particular elements in the diagram.

3 Ontology-based Information Visualization: Towards Semantic Web Applications

The Cluster Map visualization technique, developed by the Dutch software vendor Aduna 1 , bridges the gap between complex semantic structures and their simple, intuitive user-oriented presentation. It presents semantic data to end users that want to leverage the benefits of Semantic Web technology without being burdened with the 1

A Semantics-Based, End-User-Centered Information Visualization Process for Semantic Web Data

Human–Computer Interaction Series, 2013

Understanding and interpreting Semantic Web data is almost impossible for novices as skills in Semantic Web technologies are required. Thus, Information Visualization (InfoVis) of this data has become a key enabler to address this problem. However, convenient solutions are missing as existing tools either do not support Semantic Web data or require users to have programming and visualization skills. In this chapter, we propose a novel approach towards a generic InfoVis workbench called VizBoard, which enables users to visualize arbitrary Semantic Web data without expert skills in Semantic Web technologies, programming, and visualization. More precisely, we define a semantics-based, user-centered InfoVis workflow and present a corresponding workbench architecture based on the mashup paradigm, which actively supports novices in gaining insights from Semantic Web data, thus proving the practicability and validity of our approach.