Paper Info
Title
Spade: A Modular Framework for Analytical Exploration of RDF Graphs.
Abstract
RDF data is complex; exploring it is hard, and can be done through many different metaphors. We have developed and propose to demonstrate Spade, a tool helping users discover meaningful content of an RDF graph by showing them the results of aggregation (OLAP-style) queries automatically identified from the data. Spade chooses aggregates that are visually interesting, a property formally based on statistic properties of the aggregation query results. While well understood for relational data, such exploration raises multiple challenges for RDF: facts, dimensions and measures have to be identified (as opposed to known beforehand); as there are more candidate aggregates, assessing their interestingness can be very costly; finally, ontologies bring novel specific challenges but also novel opportunities, enabling ontology-driven exploration from an aggregate initially proposed by the system. Spade is a generic, extensible framework, which we instantiated with: (i) novel methods for enumerating candidate measures and dimensions in the vast space of possibilities provided by an RDF graph; (ii) a set of aggregate interestingness functions; (iii) ontology-based interactive exploration, and (iv) efficient early-stop techniques for estimating the interestingness of an aggregate query. The demonstration will comprise interactive scenarios on a variety of large, interesting RDF graphs.
Year
DOI
Venue
2019
10.14778/3352063.3352101
PVLDB
DocType
Volume
Issue
Journal
12
12
ISSN
Citations 
PageRank 
2150-8097
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Yanlei Diao12234108.95
Pawel Guzewicz221.78
Ioana Manolescu32630235.86
Mirjana Mazuran401.01