Methods Inf Med 2/2013 © Schattauer 2013 168 Focus Theme – Original Articles Health Webscience The Role of Taxonomies in Social Media and the Semantic Web for Health Education A Study of SNOMED CT Terms in YouTube Health Video Tags S. Konstantinidis 1 ; L. Fernandez-Luque 2 ; P. Bamidis 3 ; R. Karlsen 2,4 1 Aristotle University of Thessaloniki, Lab of Medical Informatics, Medical School, Thessaloniki, Greece; 2 Norut, Tromsø, Norway; 3 Aristotle University of Thessaloniki, Lab of Medical Informatics, Medical School, Thessaloniki, Greece; 4 University of Tromsø, Computer Science Department, Tromsø, Norway Keywords Heath video, tags, tag cloud, SNOMED CT, terms, Medical thesauri, linked data, linked medical data, educational metadata, learn- ing/content management system Summary Background: An increasing amount of health education resources for patients and professionals are distributed via social media channels. For example, thousands of health education videos are disseminated via You- Tube. Often, tags are assigned by the dis- seminator. However, the lack of use of stan- dardized terminologies in those tags and the presence of misleading videos make it par- ticularly hard to retrieve relevant videos. Objectives: i) Identify the use of standard- ized medical thesauri (SNOMED CT) in You- Tube Health videos tags from preselected YouTube Channels and demonstrate an infor- mation technology (IT) architecture for treat- ing the tags of these health (video) resources. ii) Investigate the relative percentage of the tags used that relate to SNOMED CT terms. As such resources may play a key role in educat- ing professionals and patients, the use of stan- dardized vocabularies may facilitate the shar- ing of such resources. iii) Demonstrate how such resources may be properly exploited within the new generation of semantically en- riched content or learning management sys- tems that allow for knowledge expansion through the use of linked medical data and numerous literature resources also described through the same vocabularies. Methods: We implemented a video portal in- tegrating videos from 500 US Hospital chan- nels. The portal integrated 4,307 YouTube videos regarding surgery as described by 64,367 tags. BioPortal REST services were used within our portal to match SNOMED CT terms with YouTube tags by both exact match and non-exact match. The whole architecture was complemented with a mechanism to en- rich the retrieved video resources with other educational material residing in other reposi- tories by following contemporary semantic web advances, in the form of Linked Open Data (LOD) principles. Results: The average percentage of YouTube tags that were expressed using SNOMED CT terms was about 22.5%, while one third of YouTube tags per video contained a SNOMED CT term in a loose search; this analogy be- came one tenth in the case of exact match. Retrieved videos were then linked further to other resources by using LOD compliant sys- tems. Such results were exemplified in the case of systems and technologies used in the mEducator EC funded project. Conclusion: YouTube Health videos can be searched for and retrieved using SNOMED CT terms with a high possibility of identifying health videos that users want based on their search criteria. Despite the fact that tagging of this information with SNOMED CT terms may vary, its availability and linked data ca- pacity opens the door to new studies for per- sonalized retrieval of content and linking with other knowledge through linked medi- cal data and semantic advances in (learning) content management systems. Correspondence to: Panagiotis D. Bamidis Lab of Medical Informatics Medical School Aristotle University of Thessaloniki, PO Box 323 54124, Thessaloniki Greece E-mail: bamidis@med.auth.gr Methods Inf Med 2013; 52: 168–179 doi: 10.3414/ME12-02-0005 received: March 4, 2012 accepted: February 3,2013 prepublished: February 28, 2013 For personal or educational use only. No other uses without permission. All rights reserved. Downloaded from www.methods-online.com on 2014-09-12 | IP: 193.156.105.143