Visual comprehension and orientation into the COVID-19 CIDO ontology

Ling Zheng, Yehoshua Perl, Yongqun He, Christopher Ochs, James Geller, Hao Liu, Vipina K. Keloth

Research output: Contribution to journalArticlepeer-review

Abstract

The current intensive research on potential remedies and vaccinations for COVID-19 would greatly benefit from an ontology of standardized COVID terms. The Coronavirus Infectious Disease Ontology (CIDO) is the largest among several COVID ontologies, and it keeps growing, but it is still a medium sized ontology. Sophisticated CIDO users, who need more than searching for a specific concept, require orientation and comprehension of CIDO. In previous research, we designed a summarization network called “partial-area taxonomy” to support comprehension of ontologies. The partial-area taxonomy for CIDO is of smaller magnitude than CIDO, but is still too large for comprehension. We present here the “weighted aggregate taxonomy” of CIDO, designed to provide compact views at various granularities of our partial-area taxonomy (and the CIDO ontology). Such a compact view provides a “big picture” of the content of an ontology. In previous work, in the visualization patterns used for partial-area taxonomies, the nodes were arranged in levels according to the numbers of relationships of their concepts. Applying this visualization pattern to CIDO's weighted aggregate taxonomy resulted in an overly long and narrow layout that does not support orientation and comprehension since the names of nodes are barely readable. Thus, we introduce in this paper an innovative visualization of the weighted aggregate taxonomy for better orientation and comprehension of CIDO (and other ontologies). A measure for the efficiency of a layout is introduced and is used to demonstrate the advantage of the new layout over the previous one. With this new visualization, the user can “see the forest for the trees” of the ontology. Benefits of this visualization in highlighting insights into CIDO's content are provided. Generality of the new layout is demonstrated.

Original languageEnglish (US)
Article number103861
JournalJournal of Biomedical Informatics
Volume120
DOIs
StatePublished - Aug 2021

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Health Informatics

Keywords

  • Comprehension of an ontology
  • Coronavirus Infectious Disease Ontology
  • Ontology orientation
  • Ontology summarization
  • Ontology visualization
  • Summarization networks

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