The number of health-related websites is increasing day-by-day; however, their quality is variable and difficult to assess. Various “trust marks” and filtering portals have been created in order to assist consumers in retrieving quality medical information. Consumers are using search engines as the main tool to get health information; however, the major problem is that the meaning of the web content is not machine-readable in the sense that computers cannot understand words and sentences as humans can. In addition, trust marks are invisible to search engines, thus limiting their usefulness in practice. During the last five years there have been different attempts to use Semantic Web tools to label health-related web resources to help internet users identify trustworthy resources. This paper discusses how Semantic Web technologies can be applied in practice to generate machine-readable labels and display their content, as well as to empower end-users by providing them with the infrastructure for expressing and sharing their opinions on the quality of health-related web resources.
FergusonTFrydmanG. The first generation of e-patients. BMJ2004; 328: 1148–1149.
2.
MayerMALeisASarriasRRuízP. Web Médica Acreditada Guidelines: reliability and quality of health information on Spanish-language Websites. In: EngelbrechtR. (eds) Connecting Medical Informatics and Bioinformatics. Proceedings of the Medical Informatics Europe 2005; Vol. I (1), pp.1287–1292.
3.
PengZLoganR. Content Quality, Usability, Affective Evaluation, and Overall Satisfaction of Online Health Information. Paper presented at the annual meeting of the International Communication Association. New York, 25 May 2009.
4.
JansenBPoochU. A review of Web searching studies and a framework for futures research. JASIST2001; 52 (3): 235–246.
5.
FoxS. Online Health Search 2006: Most internet users start at a search engine when looking for health information online. Very few check the source and date of the information they find. Pew Internet & American Project, 29October2006.
6.
Pew Research Center. Internet health resources. Washington: Pew Internet and American Life Project, 2003, pp. 20–25, accessed October 2009).
7.
HalkiasDHarkiolakisNThurmanPCaracatsanisS. Internet use for health-related purposes among Greek consumers. Telemedicine and e-Health2008; 14 (3): 255–260.
8.
SoualmiaLFDarmoniSJDouyèreMThirionB. Modelisation of Consumer Health Information in a Quality-Controled gateway. In: BaudR. (eds) The New Navigators: from Professionals to Patients. IOS Press. Proceedings of the Medical Informatics Europe2003, pp. 701–706.
9.
NabaretteHRomaneixFBoyerCDarmoniSJRémyPLCaniardE. Certification des sites dédiés à la santé en France. Presse Med, August2009.
10.
WilsonP. How to find the good and avoid the bad or ugly: a short guide to tools for rating quality of health information on the Internet. BMJ2002; 324 (7337): 598–602.
11.
Health on the Net. Analysis of 9th HON Survey of Health and Medical Internet users. Winter 2004-2005. Available online at: http://www.hon.ch/Survey/Survey2005/res.html (accessed November 2009).
12.
RiceREKatzJE (eds). The Internet and Health communication. Experiences and Expectations. London: SAGE Publications, Inc. 2001.
13.
ArcherPFerrariEKarkaletsisVKonstantopoulosSKoukourikosAPeregoA. QUATRO Plus: Quality you can trust?Proceedings: Workshop on Trust and Privacy on the Social and Semantic Web (SPOT) 2009, 2009.
14.
Berners-LeeTHendlerJLassillaO. The semantic Web. Sci Am2001; 284 (5): 34–43.
15.
GiustiniD. Web 3.0 and medicine. BMJ2007; 335 (7633): 1273–1274.
16.
EysenbachGYihuneGLampeKCrossPBrickleyD. MedCERTAIN - MedPICS certification and rating of trustworthy and assessed health information on the net. Proceedings AMIA Symposium2000; 230–234.
17.
EysenbachGKohlerCYihuneGLampeKCrossPBrickleyD. A metadata vocabulary for self- and third-party labeling of health Web-sites: Health Information Disclosure, Description and Evaluation Language (HIDDEL). JAMIA (Suppl) 2001: 169–173.
18.
MayerMADarmoniSJFieneMKohlerRoth-BerghoferTREysenbachG. MedCIRCLE: Collaboration for Internet rating, certification, labelling and evaluation of health information on the World-Wide-Web. In: BaudR. (eds) The New Navigators: from Professionals to Patients. IOS Press: Proceedings of the Medical Informatics Europe2003, pp. 667–672.
19.
StamatakisKChandrinosKKarkaletsisVMayerMAGonzalesDVLabskyDV. AQUA, a system assisting labelling experts assess health Web resources. In: Proceedings of the 12th International Symposium for Health Information Management Research (iSHIMR2007), Sheffield, 18-20 July 2007, pp. 75–84.
20.
GriffithsKMTangTTHawkingDChristensenH. Automated assessment of the quality of depression Web sites. J Med Internet Res200530; 7 (5): e59.
21.
WangY andLiuZ. Automatic detecting indicators for quality of health information on the Web. Int J. Med Inform2007; 76 (8): 575–582.
22.
KarkaletsisVStamatakisKKarampiperisPLabskýMRuzickaMSvátekV. Management of Medical Web site Quality Labels via Web Mining. In: BerkaPRauchJAbdelkader ZighedD (eds) Data Mining and Medical Knowledge Management: Cases and Applications. USA: IGI Global Inc, 2009, pp. 206–226.
