Spatial Perception for Structured and Unstructured Data In topological Data Analysis

Yoshitake Kitanishi, Fumio Ishioka, Masaya Iizuka, Koji Kurihara

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Recent years have witnessed the accumulation of vast amounts of data and information. It is difficult to capture the characteristics of these data spatially or visualize them robustly and stably with respect to data updates and increases using conventional methods. The purpose of this study is to systematically visualize the relationships among drugs using diverse information. While studies have conducted visualization research using structured data, such as chemical descriptors, research has not yet been performed from comprehensive viewpoints using unstructured data on efficacy, adverse events, and other phenomena. Therefore, we use a topological data analysis mapper and a spatial perception method to obtain and visualize data based on the integrated principal component score of quantitative and qualitative data. Consequently, a network composed of characteristic clusters according to drug class was shown. Findings show that heterogeneous compounds in the cluster may indicate the potential for drug repositioning. Our proposed method is an effective means of obtaining new knowledge of pharmaceuticals.

Original languageEnglish
Title of host publicationData Analysis and Rationality in a Complex World
EditorsTheodore Chadjipadelis, Berthold Lausen, Angelos Markos, Tae Rim Lee, Angela Montanari, Rebecca Nugent
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages9
ISBN (Print)9783030601034
Publication statusPublished - 2021
Event16th Conference of the International Federation of Classification Societies, IFCS 2019 - Thessaloniki, Greece
Duration: Aug 26 2019Aug 29 2019

Publication series

NameStudies in Classification, Data Analysis, and Knowledge Organization
ISSN (Print)1431-8814
ISSN (Electronic)2198-3321


Conference16th Conference of the International Federation of Classification Societies, IFCS 2019


  • Quantitative and qualitative data
  • Spatial perception
  • Structured and unstructured data
  • Topological data analysis
  • Topological data analysis mapper

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Analysis


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