Information visualization: conceptualizing new paths for filtering and navigate in scientific knowledge objects

Abstract

More than 6,849.32 new research journal articles are published every day! Who has time to read every article or document that’s relevant to their research? Access to the right and relevant information is paramount for scientific discoveries. Filtering relevant information has become a fundamental challenge in the actual scientific deluge panorama. As information glut grows ever worse, understanding and visualizing the science social behavior may become our only hope for handling a growing deluge of scientific information. It is therefore fundamental to analyze and interactively visualize the science social space. This paper theoretically conceptualizes an approach aimed at the filtering and navigation of relevant Scientific Knowledge Objects (SKOs) based on a symbiosis between different sub-disciplines domains. We present two main contributions, a comparison among several projects with some relevant use of information visualization in scholarly scientific navigation; and an architecture which will be in line with the most recent international standards and good practices for Open Data, especially those related to Linked Open Data capable to perform an innovative information visualization of relevant SKOs. These contributions are relevant to scholarly and to practitioner’s communities and to who want to access and navigate in relevant SKOs.