文章基本信息

标题：SAGG: A NOVEL LINKED DATA VISUALIZATION APPROACH
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作者：NOEMI SCARPATO ; GIANFRANCO ALESSIO
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2017
卷号：95
期号：22
页码：6192
出版社：Journal of Theoretical and Applied
摘要：In this paper, we describe the Semi-automatic GUI Generator (SAGG), a knowledge-based visualization system able to create GUI in a semi-automatically way. Since the linked has been introduced their expressiveness made possible to provide users with a lot of useful information, visualize this information is a crucial issue in the realization of the semantic web principles. The objective of our approach is the induction of tailored GUI able to show the considered linked data in the better way. The key idea behind our approach is the exploitation of existing web pages to deduct visualization patterns for linked data. Our intent is to provide common users with a semi-automatic GUI generator, this system is able to visualize linked data without the necessity for the above-mentioned users to know semantic technologies for data visualization. Following, we present an introduction to linked data visualization systems, our solution to linked data visualization issue: the SAGG system, its architecture, the implemented algorithms to realize it and its user interaction mechanisms.
关键词：Linked Data Visualization; Semantic Web; Information Visualization; Knowledge Visualization; OWL; SPARQL