Linked Open Data Visualization Revisited: A Survey by Oscar Peña, Unai Aguilera and Diego López-de-Ipiña.
Abstract:
Mass adoption of the Semantic Web’s vision will not become a reality unless the benefits provided by data published under the Linked Open Data principles are understood by the majority of users. As technical and implementation details are far from being interesting for lay users, the ability of machines and algorithms to understand what the data is about should provide smarter summarisations of the available data. Visualization of Linked Open Data proposes itself as a perfect strategy to ease the access to information by all users, in order to save time learning what the dataset is about and without requiring knowledge on semantics.
This article collects previous studies from the Information Visualization and the Exploratory Data Analysis fields in order to apply the lessons learned to Linked Open Data visualization. Datatype analysis and visualization tasks proposed by Ben Shneiderman are also added in the research to cover different visualization features.
Finally, an evaluation of the current approaches is performed based on the dimensions previously exposed. The article ends with some conclusions extracted from the research.
I would like to see a version of this article after it has had several good editing passes. From the abstract alone, “…benefits provided by data…” and “…without requiring knowledge on semantics…” strike me as extremely problematic.
Data, accessible or not, does not provide benefits. The results of processing data may, which may explain the lack of enthusiasm when large data dumps are made web accessible. In and of itself, it is just another large dump of data. The results of processing that data may be very useful, but that is another step in the process.
I don’t think “…without requiring knowledge of semantics…” is in line with the rest of the article. I suspect the authors meant the semantics of data sets could be conveyed to users without their researching them prior to using the data set. I think that is problematic but it has the advantage of being plausible.
The various theories of visualization and datatypes (pages 3-8) don’t seem to advance the discussion and I would either drop that content or tie it into the actual visualization suites discussed. It’s educational but its relationship to the rest of the article is tenuous.
The coverage of visualization suites is encouraging and useful, but with an overall tighter focus, more time could be spent on each one and their entries being correspondingly longer.
Hopefully we will see a later, edited version of this paper as a good summary/guide to visualization tools for linked data would be a useful addition to the literature.
I first saw this in a tweet by Marin Dimitrov.