@inproceedings{154e8e4b96d2481db8e924dd58950e41,
title = "Elinda: Explorer for linked data",
abstract = "To realize the premise of the Semantic Web towards knowledgeable machines, one might often integrate an application with emerging RDF graphs. Nevertheless, capturing the content of a rich and open RDF graph by existing tools requires both time and expertise. We demonstrate eLinda-an explorer for Linked Data. The challenge addressed by eLinda is that of understanding the rich content of a given RDF graph. The core functionality is an exploration path, where each step produces a bar chart (histogram) that visualizes the distribution of classes in a set of nodes (URIs). In turn, each bar represents a set of nodes that can be further expanded through the bar chart in the path. We allow three types of explorations: subclass distribution, property distribution, and object distribution for a property of choice. To efficiently compute the exploration queries, we offer a query engine powered by a worst-case-optimal join algorithm.",
author = "Tal Yahav and Oren Kalinsky and Oren Mishali and Benny Kimelfeld",
note = "Publisher Copyright: {\textcopyright} 2018 Copyright held by the owner/author(s); 21st International Conference on Extending Database Technology, EDBT 2018 ; Conference date: 26-03-2018 Through 29-03-2018",
year = "2018",
doi = "https://doi.org/10.5441/002/edbt.2018.78",
language = "الإنجليزيّة",
series = "Advances in Database Technology - EDBT",
pages = "658--661",
editor = "Michael Bohlen and Reinhard Pichler and Norman May and Erhard Rahm and Shan-Hung Wu and Katja Hose",
booktitle = "Advances in Database Technology - EDBT 2018",
}