VOLT: A Provenance-Producing, Transparent SPARQL Proxy for the On-Demand Computation of Linked Data & its Application to Spatiotemporally Dependent Data thumbnail
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VOLT: A Provenance-Producing, Transparent SPARQL Proxy for the On-Demand Computation of Linked Data & its Application to Spatiotemporally Dependent Data

Published on Jul 28, 20161491 Views

The Linked Data paradigm has changed how data on the Web is published, retrieved, and interlinked, thereby enabling modern question answering systems and contributing to the spread of open data. Wi

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Chapter list

VOLT: A Provenance-Producing, Transparent SPARQL Proxy for the On-Demand Computation of Linked Data & its Application to Spatiotemporally Dependent Data00:00
Motivation00:50
Linked data00:51
Problem01:21
Solution02:02
Need for computation02:29
Dependent data - 103:01
Dependent data - 203:41
Dependent data - 303:49
Good job04:00
About: Nagasaki - 104:01
About: Nagasaki - 204:09
About: Nagasaki - 304:25
About: Nagasaki - 404:26
SPARQL - 104:43
SPARQL - 205:04
Framework05:36
Framework don’ts05:49
Frameworks ideals06:43
Cake example - 107:22
Cake example - 207:27
Cake example - 307:32
Cake example - 407:37
Transparent proxy07:42
Man in the middle... support07:43
SPARQL as an api08:21
The VOLT ontology09:43
Transparency of procedures10:26
Reproducibility11:05
Cardinal Directions12:25
Diversity12:38
Statistics13:40
Accuracy14:18
Strategy14:54
On-demand computation15:39
Generalizing16:49
Extending volt16:52
POSTGIS17:13
Using GEOSPARQL17:57
Untitled18:44
Sum of places19:43
Conclusions19:51
Recap19:54
Questions?21:01