Authors:
Belgin Mutlu
1
;
Patrick Hoefler
1
;
Gerwald Tschinkel
1
;
Eduardo Veas
1
;
Vedran Sabol
2
;
Florian Stegmaier
3
and
Michael Granitzer
3
Affiliations:
1
Know-Center, Austria
;
2
Know Center GmbH and Graz University of Technology, Austria
;
3
University of Passau, Germany
Keyword(s):
Linked Data, RDF Data Cube, Visualisation, Visual Mapping, Research Data.
Related
Ontology
Subjects/Areas/Topics:
Abstract Data Visualization
;
Computer Vision, Visualization and Computer Graphics
;
General Data Visualization
;
Interactive Visual Interfaces for Visualization
;
Knowledge-Assisted Visualization
;
Scientific Visualization
;
Spatial Data Visualization
;
Visual Data Analysis and Knowledge Discovery
Abstract:
Research papers are published in various digital libraries, which deploy their own meta-models and technologies
to manage, query, and analyze scientific facts therein. Commonly they only consider the meta-data
provided with each article, but not the contents. Hence, reaching into the contents of publications is inherently
a tedious task. On top of that, scientific data within publications are hardcoded in a fixed format (e.g. tables).
So, even if one manages to get a glimpse of the data published in digital libraries, it is close to impossible
to carry out any analysis on them other than what was intended by the authors. More effective querying and
analysis methods are required to better understand scientific facts. In this paper, we present the web-based
CODE Visualisation Wizard, which provides visual analysis of scientific facts with emphasis on automating
the visualisation process, and present an experiment of its application. We also present the entire analytical
process and the
corresponding tool chain, including components for extraction of scientific data from publications,
an easy to use user interface for querying RDF knowledge bases, and a tool for semantic annotation of
scientific data sets.
(More)