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{{orphan|date=February 2015}}'''Health Web Science''' (HWS) is a sub-discipline of [[Web science|Web Science]] that examines the interplay between health sciences, health and well-being and the Web. It assumes that each domain influences the others. HWS thus complements and overlaps with [[Health 2.0|Medicine 2.0]] (medicine enabled by emerging technologies).<ref>McHattie LS, Cumming G, French T. Transforming Patient Experience: Health Web Science Meets Medicine 2.0 Med 2.0 2014;3(1):e2 URL:http://www.medicine20.com/2014/1/e2 DOI: 10.2196/med20.3128.</ref> Research has uncovered [[emergent properties]] that arise as individuals interact with each other, with healthcare providers and with the Web itself.
{{orphan|date=February 2015}}'''Health Web Science''' (HWS) is a sub-discipline of [[Web science|Web Science]] that examines the interplay between health sciences, health and well-being and the Web. It assumes that each domain influences the others. HWS thus complements and overlaps with [[Health 2.0|Medicine 2.0]] (medicine enabled by emerging technologies).<ref>McHattie LS, Cumming G, French T. Transforming Patient Experience: Health Web Science Meets Medicine 2.0 Med 2.0 2014;3(1):e2 URL:http://www.medicine20.com/2014/1/e2 DOI: 10.2196/med20.3128.</ref> Research has uncovered [[emergent properties]] that arise as individuals interact with each other, with healthcare providers and with the Web itself.
==History==
==History==
HWS began at the Web Science Curriculum meeting in the summer of 2010 at the University of Southampton where approximately forty scholars came together to discuss the subject. That was followed by a foundational Workshop in Koblenz 2011 under the aegis of [[Association for Computing Machinery|ACM]].<ref>Brooks, E. H., Cumming, G. P., & Luciano, J. S. Health web science: application of web science to the area of health education and health care. In Proceedings of the second international workshop on Web science and information exchange in the medical web (pp. 11-14). ACM; 2011.http://dl.acm.org/citation.cfm?id=2064741.2064746&coll=DL&dl=ACM&CFID=442852636&CFTOKEN=32594658</ref><ref>{{Cite web|url=http://www.acm.org/|title=ACM|last=|first=|date=|website=|publisher=|access-date=}}</ref>
HWS began at the Web Science Curriculum meeting in the summer of 2010 at the University of Southampton where approximately forty scholars came together to discuss the subject. That was followed by a foundational Workshop in Koblenz 2011 under the aegis of [[Association for Computing Machinery|ACM]].<ref>{{Cite journal|last=Brooks|first=Elizabeth H.|last2=Cumming|first2=Grant P.|last3=Luciano|first3=Joanne S.|date=2011-01-01|title=Health Web Science: Application of Web Science to the Area of Health Education and Health Care|url=http://doi.acm.org/10.1145/2064741.2064746|journal=Proceedings of the Second International Workshop on Web Science and Information Exchange in the Medical Web|series=MedEx '11|location=New York, NY, USA|publisher=ACM|pages=11–14|doi=10.1145/2064741.2064746|isbn=9781450309509}}</ref><ref>{{Cite web|url=http://www.acm.org/|title=ACM|last=|first=|date=|website=|publisher=|access-date=}}</ref>


The dialogue to more precisely define HWS as a sub-discipline of Web Science began among Web-oriented investigators at the 2012 Medicine 2.0 Conference<ref>{{Cite web|url=http://www.medicine20congress.com/ocs/index.php/med/med2012|title=Medicine 2.0'12 (Boston, USA)|website=www.medicine20congress.com|access-date=2016-03-08}}</ref><ref>Luciano JS, Cumming GP, Wilkinson MD, Kahana E. The Emergent Discipline of Health Web Science J Med Internet Res 2013;15(8):e166 URL:http://www.jmir.org/2013/8/e166 DOI: 10.2196/jmir.2499 PMID 23968998 PMCID: PMC3758025</ref> and was formalized in 2013.<ref>Luciano JS, Cumming GP, Wilkinson MD, Kahana E The Emergent Discipline of Health Web Science. J Med Internet Res 2013;15(8):e166 URL:http://www.jmir.org/2013/8/e166 DOI: 10.2196/jmir.2499 PMID 23968998 PMCID: PMC3758025.</ref> This nascent discipline of Health Web Science is further described and developed in the monograph "Health Web Science".<ref>Luciano, J. S., Cumming, G. P., Kahana, E., Wilkinson, M. D., Brooks, E. H., Jarman, H., … Levine, M. S. (2014). Health Web Science. Foundations and Trends® in Web Science, 4(4), 269‐419. doi: http://dx.doi.org/10.1561/1800000019</ref>
The dialogue to more precisely define HWS as a sub-discipline of Web Science began among Web-oriented investigators at the 2012 Medicine 2.0 Conference<ref>{{Cite web|url=http://www.medicine20congress.com/ocs/index.php/med/med2012|title=Medicine 2.0'12 (Boston, USA)|website=www.medicine20congress.com|access-date=2016-03-08}}</ref><ref>{{Cite journal|last=Luciano|first=Joanne S.|last2=Cumming|first2=Grant P.|last3=Wilkinson|first3=Mark D.|last4=Kahana|first4=Eva|date=2013-01-01|title=The emergent discipline of health web science|url=http://www.ncbi.nlm.nih.gov/pubmed/23968998|journal=Journal of Medical Internet Research|volume=15|issue=8|pages=e166|doi=10.2196/jmir.2499|issn=1438-8871|pmc=3758025|pmid=23968998}}</ref> and was formalized in 2013.<ref>{{Cite journal|last=Luciano|first=Joanne S.|last2=Cumming|first2=Grant P.|last3=Wilkinson|first3=Mark D.|last4=Kahana|first4=Eva|date=2013-01-01|title=The emergent discipline of health web science|url=http://www.ncbi.nlm.nih.gov/pubmed/23968998|journal=Journal of Medical Internet Research|volume=15|issue=8|pages=e166|doi=10.2196/jmir.2499|issn=1438-8871|pmc=3758025|pmid=23968998}}</ref> This nascent discipline of Health Web Science is further described and developed in the monograph "Health Web Science".<ref>{{Cite journal|last=Luciano|first=Joanne S.|title=Health Web Science|url=http://www.nowpublishers.com/articles/foundations-and-trends-in-web-science/WEB-019|journal=Foundations and Trends® in Web Science|volume=4|issue=4|pages=269–419|doi=10.1561/1800000019}}</ref>


A call to action at the ACM Web Science workshop<ref>{{Cite web|url=http://www.websci13.org/workshops/wk9-life-web-science-workshop/|title=WK9 - Life Web Science Workshop - ACM Web Science 2013|website=www.websci13.org|access-date=2016-03-08}}</ref> asked the community to consider how to accelerate the discipline. In particular, beyond the available knowledge-gathering technologies (e.g. [[blogs]], social-medicine portals, experience mining, [[graph theory]], [[network analysis]], [[game theory]]), what additional is required to deal with the Health Web's emergent properties? For example, what is needed to curate, interrogate and visualize the combination of both '[[Big Data]]' – arising from the increasingly pervasive sources and sensors including "the [[Internet of Things|Internet of things]], the [[Quantified Self|quantified self]], [[smart cities]] and smart homes – and smaller-scale data arising from individual patient conversations, self-reporting and self-exploration? And how are small-scale innovations safely and efficiently scaled up to the size of the Web and scaled out to millions of patients?<ref>Gillam et al. (2009) The healthcare singularity and the age of semantic medicine. In The Fourth Paradigm Data-Intensive Scientific Discovery.Microsoft Research Washington. http://research.microsoft.com/en-us/collaboration/fourthparadigm/4th_paradigm_book_complete_lr.pdf</ref>
A call to action at the ACM Web Science workshop<ref>{{Cite web|url=http://www.websci13.org/workshops/wk9-life-web-science-workshop/|title=WK9 - Life Web Science Workshop - ACM Web Science 2013|website=www.websci13.org|access-date=2016-03-08}}</ref> asked the community to consider how to accelerate the discipline. In particular, beyond the available knowledge-gathering technologies (e.g. [[blogs]], social-medicine portals, experience mining, [[graph theory]], [[network analysis]], [[game theory]]), what additional is required to deal with the Health Web's emergent properties? For example, what is needed to curate, interrogate and visualize the combination of both '[[Big Data]]' – arising from the increasingly pervasive sources and sensors including "the [[Internet of Things|Internet of things]], the [[Quantified Self|quantified self]], [[smart cities]] and smart homes – and smaller-scale data arising from individual patient conversations, self-reporting and self-exploration? And how are small-scale innovations safely and efficiently scaled up to the size of the Web and scaled out to millions of patients?<ref>Gillam et al. (2009) [http://research.microsoft.com/en-us/collaboration/fourthparadigm/4th_paradigm_book_complete_lr.pdf The healthcare singularity and the age of semantic medicine]. In The Fourth Paradigm Data-Intensive Scientific Discovery.Microsoft Research Washington. </ref>


One research group argued for technologies that enable predictive, personalized, preventive participatory (P4) medicine.<ref>Hood, L., & Friend, S. H. (2011). Predictive, personalized, preventive, participatory (P4) cancer medicine. Nature Reviews Clinical Oncology, 8(3), 184-187.</ref> Other stated needs include an "Expert Patient" capable of making sense of online medical information in a personal context, tools to cope with information overload through e.g., [[text mining]] and semantic technologies, in particular through algorithm-aided decision making.
One research group argued for technologies that enable predictive, personalized, preventive participatory (P4) medicine.<ref>{{Cite journal|last=Hood|first=Leroy|last2=Friend|first2=Stephen H.|title=Predictive, personalized, preventive, participatory (P4) cancer medicine|url=http://www.nature.com/doifinder/10.1038/nrclinonc.2010.227|journal=Nature Reviews Clinical Oncology|volume=8|issue=3|pages=184–187|doi=10.1038/nrclinonc.2010.227}}</ref> Other stated needs include an "Expert Patient" capable of making sense of online medical information in a personal context, tools to cope with information overload through e.g., [[text mining]] and semantic technologies, in particular through algorithm-aided decision making.


=== Health web observatory ===
=== Health web observatory ===
At the Medicine 2.0 European meeting in 2014, the case was made for the need to design bespoke health web observatories. The Web Science Trust<ref>{{Cite web|url=http://webscience.org/|title=Web Science Trust|website=Web Science Trust|access-date=2016-03-08}}</ref> introduced the concept of a Web observatory<ref>{{Cite web|url=http://webscience.org/web-observatory/|title=Web Observatory|website=Web Science Trust|access-date=2016-03-08}}</ref> as an integrated collection of data sources and analysis tools that enables observation and experimentation for Web study<ref>Hall, Wendy and Tiropanis, Thanassis (2012) Web Evolution and Web Science. Computer Networks, 56, (18), 3859-3865. Eprints:http://eprints.soton.ac.uk/343770/
At the Medicine 2.0 European meeting in 2014, the case was made for the need to design bespoke health web observatories. The Web Science Trust<ref>{{Cite web|url=http://webscience.org/|title=Web Science Trust|website=Web Science Trust|access-date=2016-03-08}}</ref> introduced the concept of a Web observatory<ref>{{Cite web|url=http://webscience.org/web-observatory/|title=Web Observatory|website=Web Science Trust|access-date=2016-03-08}}</ref> as an integrated collection of data sources and analysis tools that enables observation and experimentation for Web study<ref>Hall, Wendy and Tiropanis, Thanassis (2012) Web Evolution and Web Science. Computer Networks, 56, (18), 3859-3865. Eprints:http://eprints.soton.ac.uk/343770/
</ref> and positioned it to bridge the gap between big data analytics and the data.<ref>Tiropanis, T, Hall, W, Shadbolt N, De Roure, David Contractor N, Hendler J. The Web Science Observatory 2013. http://wstweb1.ecs.soton.ac.uk/wp-content/uploads/2013/08/The-Web-Science-Observatory.pdf.</ref> A Health Web observatory therefore gathers and links health data on the Web (big data and broad data) in order to answer questions. This facilitates the 'Healthcare Singularity'<ref>Gillam et al.(2009)The healthcare singularity and the age of semantic medicine. In The Fourth Paradigm Data-Intensive Scientific Discovery. Microsoft Research Washington. http://research.microsoft.com/en-us/collaboration/fourthparadigm/4th_paradigm_book_complete_lr.pdf</ref> where bench-to-bedside and experiment-to-practice becomes instantaneous. HWS combines the axiom of 'first do no harm' ([[Hippocrates]]) with 'do no evil' ([[Google]]), paying specific attention to technology and safeguards.
</ref> and positioned it to bridge the gap between big data analytics and the data.<ref>Tiropanis, T, Hall, W, Shadbolt N, De Roure, David Contractor N, Hendler J. [http://wstweb1.ecs.soton.ac.uk/wp-content/uploads/2013/08/The-Web-Science-Observatory.pdf The Web Science Observatory] 2013.</ref> A Health Web observatory therefore gathers and links health data on the Web (big data and broad data) in order to answer questions. This facilitates the 'Healthcare Singularity'<ref>Gillam et al.(2009) [http://research.microsoft.com/en-us/collaboration/fourthparadigm/4th_paradigm_book_complete_lr.pdf The healthcare singularity and the age of semantic medicine]. In The Fourth Paradigm Data-Intensive Scientific Discovery. Microsoft Research Washington.</ref> where bench-to-bedside and experiment-to-practice becomes instantaneous. HWS combines the axiom of 'first do no harm' ([[Hippocrates]]) with 'do no evil' ([[Google]]), paying specific attention to technology and safeguards.


== References ==
== References ==
{{Reflist}}
{{Reflist|30em}}




[[Category:Health websites]]
[[Category:Health websites]]

Revision as of 06:01, 8 March 2016

Health Web Science (HWS) is a sub-discipline of Web Science that examines the interplay between health sciences, health and well-being and the Web. It assumes that each domain influences the others. HWS thus complements and overlaps with Medicine 2.0 (medicine enabled by emerging technologies).[1] Research has uncovered emergent properties that arise as individuals interact with each other, with healthcare providers and with the Web itself.

History

HWS began at the Web Science Curriculum meeting in the summer of 2010 at the University of Southampton where approximately forty scholars came together to discuss the subject. That was followed by a foundational Workshop in Koblenz 2011 under the aegis of ACM.[2][3]

The dialogue to more precisely define HWS as a sub-discipline of Web Science began among Web-oriented investigators at the 2012 Medicine 2.0 Conference[4][5] and was formalized in 2013.[6] This nascent discipline of Health Web Science is further described and developed in the monograph "Health Web Science".[7]

A call to action at the ACM Web Science workshop[8] asked the community to consider how to accelerate the discipline. In particular, beyond the available knowledge-gathering technologies (e.g. blogs, social-medicine portals, experience mining, graph theory, network analysis, game theory), what additional is required to deal with the Health Web's emergent properties? For example, what is needed to curate, interrogate and visualize the combination of both 'Big Data' – arising from the increasingly pervasive sources and sensors including "the Internet of things, the quantified self, smart cities and smart homes – and smaller-scale data arising from individual patient conversations, self-reporting and self-exploration? And how are small-scale innovations safely and efficiently scaled up to the size of the Web and scaled out to millions of patients?[9]

One research group argued for technologies that enable predictive, personalized, preventive participatory (P4) medicine.[10] Other stated needs include an "Expert Patient" capable of making sense of online medical information in a personal context, tools to cope with information overload through e.g., text mining and semantic technologies, in particular through algorithm-aided decision making.

Health web observatory

At the Medicine 2.0 European meeting in 2014, the case was made for the need to design bespoke health web observatories. The Web Science Trust[11] introduced the concept of a Web observatory[12] as an integrated collection of data sources and analysis tools that enables observation and experimentation for Web study[13] and positioned it to bridge the gap between big data analytics and the data.[14] A Health Web observatory therefore gathers and links health data on the Web (big data and broad data) in order to answer questions. This facilitates the 'Healthcare Singularity'[15] where bench-to-bedside and experiment-to-practice becomes instantaneous. HWS combines the axiom of 'first do no harm' (Hippocrates) with 'do no evil' (Google), paying specific attention to technology and safeguards.

References

  1. ^ McHattie LS, Cumming G, French T. Transforming Patient Experience: Health Web Science Meets Medicine 2.0 Med 2.0 2014;3(1):e2 URL:http://www.medicine20.com/2014/1/e2 DOI: 10.2196/med20.3128.
  2. ^ Brooks, Elizabeth H.; Cumming, Grant P.; Luciano, Joanne S. (2011-01-01). "Health Web Science: Application of Web Science to the Area of Health Education and Health Care". Proceedings of the Second International Workshop on Web Science and Information Exchange in the Medical Web. MedEx '11. New York, NY, USA: ACM: 11–14. doi:10.1145/2064741.2064746. ISBN 9781450309509.
  3. ^ "ACM".
  4. ^ "Medicine 2.0'12 (Boston, USA)". www.medicine20congress.com. Retrieved 2016-03-08.
  5. ^ Luciano, Joanne S.; Cumming, Grant P.; Wilkinson, Mark D.; Kahana, Eva (2013-01-01). "The emergent discipline of health web science". Journal of Medical Internet Research. 15 (8): e166. doi:10.2196/jmir.2499. ISSN 1438-8871. PMC 3758025. PMID 23968998.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  6. ^ Luciano, Joanne S.; Cumming, Grant P.; Wilkinson, Mark D.; Kahana, Eva (2013-01-01). "The emergent discipline of health web science". Journal of Medical Internet Research. 15 (8): e166. doi:10.2196/jmir.2499. ISSN 1438-8871. PMC 3758025. PMID 23968998.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  7. ^ Luciano, Joanne S. "Health Web Science". Foundations and Trends® in Web Science. 4 (4): 269–419. doi:10.1561/1800000019.
  8. ^ "WK9 - Life Web Science Workshop - ACM Web Science 2013". www.websci13.org. Retrieved 2016-03-08.
  9. ^ Gillam et al. (2009) The healthcare singularity and the age of semantic medicine. In The Fourth Paradigm Data-Intensive Scientific Discovery.Microsoft Research Washington.
  10. ^ Hood, Leroy; Friend, Stephen H. "Predictive, personalized, preventive, participatory (P4) cancer medicine". Nature Reviews Clinical Oncology. 8 (3): 184–187. doi:10.1038/nrclinonc.2010.227.
  11. ^ "Web Science Trust". Web Science Trust. Retrieved 2016-03-08.
  12. ^ "Web Observatory". Web Science Trust. Retrieved 2016-03-08.
  13. ^ Hall, Wendy and Tiropanis, Thanassis (2012) Web Evolution and Web Science. Computer Networks, 56, (18), 3859-3865. Eprints:http://eprints.soton.ac.uk/343770/
  14. ^ Tiropanis, T, Hall, W, Shadbolt N, De Roure, David Contractor N, Hendler J. The Web Science Observatory 2013.
  15. ^ Gillam et al.(2009) The healthcare singularity and the age of semantic medicine. In The Fourth Paradigm Data-Intensive Scientific Discovery. Microsoft Research Washington.
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