Literature DB >> 29657560

Analyzing user interactions with biomedical ontologies: A visual perspective.

Maulik R Kamdar1, Simon Walk1, Tania Tudorache1, Mark A Musen1.   

Abstract

Biomedical ontologies are large: Several ontologies in the BioPortal repository contain thousands or even hundreds of thousands of entities. The development and maintenance of such large ontologies is difficult. To support ontology authors and repository developers in their work, it is crucial to improve our understanding of how these ontologies are explored, queried, reused, and used in downstream applications by biomedical researchers. We present an exploratory empirical analysis of user activities in the BioPortal ontology repository by analyzing BioPortal interaction logs across different access modes over several years. We investigate how users of BioPortal query and search for ontologies and their classes, how they explore the ontologies, and how they reuse classes from different ontologies. Additionally, through three real-world scenarios, we not only analyze the usage of ontologies for annotation tasks but also compare it to the browsing and querying behaviors of BioPortal users. For our investigation, we use several different visualization techniques. To inspect large amounts of interaction, reuse, and real-world usage data at a glance, we make use of and extend PolygOnto, a visualization method that has been successfully used to analyze reuse of ontologies in previous work. Our results show that exploration, query, reuse, and actual usage behaviors rarely align, suggesting that different users tend to explore, query and use different parts of an ontology. Finally, we highlight and discuss differences and commonalities among users of BioPortal.

Entities:  

Keywords:  data visualization; knowledge exploration; log analysis; ontology exploration; ontology reuse; user behavior

Year:  2017        PMID: 29657560      PMCID: PMC5895104          DOI: 10.1016/j.websem.2017.12.002

Source DB:  PubMed          Journal:  Web Semant        ISSN: 1570-8268            Impact factor:   1.897


  23 in total

1.  How Ontologies are Made: Studying the Hidden Social Dynamics Behind Collaborative Ontology Engineering Projects.

Authors:  Markus Strohmaier; Simon Walk; Jan Pöschko; Daniel Lamprecht; Tania Tudorache; Csongor Nyulas; Mark A Musen; Natalya F Noy
Journal:  Web Semant       Date:  2013-05       Impact factor: 1.897

2.  BiOnIC: A Catalog of User Interactions with Biomedical Ontologies.

Authors:  Maulik R Kamdar; Simon Walk; Tania Tudorache; Mark A Musen
Journal:  Semant Web ISWC       Date:  2017-10-04

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5.  The Ontology Lookup Service, a lightweight cross-platform tool for controlled vocabulary queries.

Authors:  Richard G Côté; Philip Jones; Rolf Apweiler; Henning Hermjakob
Journal:  BMC Bioinformatics       Date:  2006-02-28       Impact factor: 3.169

6.  The NHGRI GWAS Catalog, a curated resource of SNP-trait associations.

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Journal:  Nucleic Acids Res       Date:  2013-12-06       Impact factor: 16.971

7.  AmiGO: online access to ontology and annotation data.

Authors:  Seth Carbon; Amelia Ireland; Christopher J Mungall; ShengQiang Shu; Brad Marshall; Suzanna Lewis
Journal:  Bioinformatics       Date:  2008-11-25       Impact factor: 6.937

8.  Sample size and statistical power calculation in genetic association studies.

Authors:  Eun Pyo Hong; Ji Wan Park
Journal:  Genomics Inform       Date:  2012-06-30

9.  An "Electronic Fluorescent Pictograph" browser for exploring and analyzing large-scale biological data sets.

Authors:  Debbie Winter; Ben Vinegar; Hardeep Nahal; Ron Ammar; Greg V Wilson; Nicholas J Provart
Journal:  PLoS One       Date:  2007-08-08       Impact factor: 3.240

10.  Visualization and analysis of microarray and gene ontology data with treemaps.

Authors:  Eric H Baehrecke; Niem Dang; Ketan Babaria; Ben Shneiderman
Journal:  BMC Bioinformatics       Date:  2004-06-28       Impact factor: 3.169

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  1 in total

1.  Ontology-Based Interactive Visualization of Patient-Generated Research Questions.

Authors:  David Borland; Laura Christopherson; Charles Schmitt
Journal:  Appl Clin Inform       Date:  2019-06-05       Impact factor: 2.342

  1 in total

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