Suggesting Visualisations for Published Data
Belgin Mutlu, Patrick Hoefler, Gerwald Tschinkel, Eduardo Enrique Veas, Vedran Sabol, Florian Stegmaier, Michael Granitzer · 2014
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.