Web 3.0 and medicine
TL;DR: In this paper, the authors compare the features of web 2.0 and 3.0, and conclude that the latter will be a more mature web where better paths for information retrieval will be created, and a greater capacity for cognitive processing of information will be built.
Abstract: This time last Christmas, medical blogs and RSS feeds were the hot technology topics, and we were debating the merits of newer models of scholarly publishing in web 2.0, such as open access and medical wikis.1 Can web 3.0 be here already?
Recently, a neurologist devised an apt medical metaphor for web 3.0. He suggested that, “The development of the graphical web from its early days in 1995 to the social web of late 2007 is comparable to the developing brain.” He went on to say that, “Whereas web 1.0 and 2.0 were embryonic, formative technologies, web 3.0 promises to be a more mature web where better ‘pathways’ for information retrieval will be created, and a greater capacity for cognitive processing of information will be built.” (Personal communication, A Wong, 2007.)
So what is web 3.0, and why is it called the semanticweb (table(table)?)? Although both terms are used interchangeably, they convey slightly different, if complementary, views of the new web. The web 3.0 label is often used as a marketing ploy for “the next big thing.” An important feature of web 3.0 is that it enables computers to talk to each other so that they can perform the tasks necessary for us to do our work. However, a primary feature of web 3.0 is that it uses metadata—data about data. This will transform the web into a giant database, and organise it along the lines of PubMed, or one of our trusted medical library catalogues.2
At a glance: Comparison of the features of web 2.0 and 3.0
Somehow, the term semantic web has escaped the reproach of web 3.0, perhaps because it was coined by the respected web expert Sir Tim Berners-Lee in his landmark paper in Scientific American.3 His ideas continue to have tremendous salience. Berners-Lee’s view is that we need to use semantic annotation to express the meaning latent in web documents, by drawing out inferences in documents deep within the web. As a pioneer in search technology, and director of the World Wide Web Consortium, Berners-Lee maintains that access to a global “web of data”—what weaves the entire web together into a coherent whole—should help to solve humankind’s most complex problems.4
To understand why we need web 3.0, let’s examine the current state of the web. Currently, access to endless reams of unorganised information in web 2.0 shifts the online habits of doctors to searching, not finding. Consequently, medical librarians believe that it is necessary to build better mechanisms for information retrieval.5 6 As a colleague said to me recently, “we need findengines, not search engines.”
In medicine, finding the best evidence has become increasingly difficult, even for librarians. Despite its constant accessibility, Google’s search results are emblematic of an approaching crisis with information overload, and this is duplicated by Yahoo and other search engines. Consequently, medical librarians are leading doctors back to trusted sources, such as PubMed, Clinical Evidence, and the Cochrane Library, and even taking them to their library bookshelves instead. Unless better channels of information are created in web 3.0, we can expect the information glut to continue.
Web 3.0 is likely to have a big effect on medicine in 2008. In bioinformatics, it will become more common to process ever larger amounts of data. In fact, experts in bioinformatics already search for data from disparate systems, and they have started to build rich semantic relations into information tools for knowledge discovery. Finally, greater capacity for creating knowledge in medicine will be possible if we have the will to publish clinical data openly and transparently, and subject it to scrutiny.7
Developing a more personalised healthcare system will be an important challenge for doctors in web 3.0. In an era of greater personalisation, treating patients’ health problems according to their genetic profiles will depend on using the latest information technologies.8 Even the treatment of new diseases and warning systems for natural disasters will benefit from the merging of epidemiological datasets with virtual, three dimensional tools like Google Earth. Making the search for health information efficient and responsive to patients’ needs will also help reduce the costs of medical treatment.
Social software enthusiasts may well find that the new web will be fertile ground for the creation of knowledge. Although already popular, wikis may well serve as platforms for the exploration of web 3.0. One innovative wiki—Wikiproteins—is already using semantic technologies. In contrast to other wikis, Wikiproteins imports data mined from several of the world’s leading biomedical databases, such as PubMed, UniProt, and the National Library of Medicine. Its integrated entries are a useful combination of genetic information and scientific literature. Notably, the confluence of databases in Wikiproteins yields more than two million factual associations for data mining and over five billion associated pairs.9
Each new version of the web should be a better iteration of its predecessor, and web 3.0 should be no exception. In medicine, we should focus on the ability to locate trusted clinical information, while creating the means to produce new knowledge. Information retrieval in web 3.0 should be based less on keywords than on intelligent ontological frameworks, such as the National Library of Medicine’s Unified Medical Language System, Medline’s trusted MeSH vocabulary, or some other tool. The National Library of Medicine is working on automated indexing, which may be part of the solution for searching the biomedical web.10 Finally, as we move further into the digital age, our trusted print libraries must continue to be well funded and should not be forgotten in the midst of the intelligent web.
The question of whether http://del.icio.us and www.connotea.org—two popular social tagging sites—will be useful in web 3.0 remains doubtful.11 Social tagging or “indexing” has limitations because of poor control of synonyms, homonyms, spelling conventions, and other linguistic variations. Think about the myriad ways we describe a heart attack; these variations have enormous implications for searching and require control to optimise retrieval. A smarter medical web is coming. Its two most exciting features will be the better organisation of documents and a deeper use of the knowledge base in medicine. In terms of searching, the semantic web should resemble a library catalogue, where documents are described and given meaningful access points for easy retrieval. However, in getting to web 3.0, let’s aim for something better than the current web, not the incoherent mess of web 2.0. Logically, web 3.0 should bring order to the 21st century web in the same way that Dr John Shaw Billings’s Index Medicus brought order to medical research back in the 19th century.12 As a medical librarian, I sincerely hope that web 3.0 will return us to some of the time honoured principles of my profession.
Glossary
Data mining—a process of knowledge discovery or retrieval of hidden information from data banks and clusters of databases
Mashup—a web application or site that mixes content from multiple sources
RSS (really simple syndication)—a format for sharing content between different websites
Semantic web—a project that intends to create a universal medium for information exchange from 2008 and beyond by putting documents with computer processable meaning (semantics) on the world wide web
Semantics—a term derived from the Greek to give signs, meaning, or to make significant. Semantics refers to aspects of meaning as expressed in language or other systems of signs
Social tagging—the application of freely chosen labels, or tags, to web documents, web pages, and photo sharing sites, such as www.flikr.com
Web 3.0—a term used to describe the evolution of the web, and our responses to it, in finding and organising new information
Wiki—a website or similar online resource that allows users to add and edit medical information collectively
Citations
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TL;DR: This paper aims to establish a clear definition for Medicine 2.0 and delineate literature that is specific to the field and establishes a literature base and delineates key topics for future research into Medicine 2,0, distinct to that of eHealth.
Abstract: Background: The term Web 2.0 became popular following the O’Reilly Media Web 2.0 conference in 2004; however, there are difficulties in its application to health and medicine. Principally, the definition published by O’Reilly is criticized for being too amorphous, where other authors claim that Web 2.0 does not really exist. Despite this skepticism, the online community using Web 2.0 tools for health continues to grow, and the term Medicine 2.0 has entered popular nomenclature.
Objective: This paper aims to establish a clear definition for Medicine 2.0 and delineate literature that is specific to the field. In addition, we propose a framework for categorizing the existing Medicine 2.0 literature and identify key research themes, underdeveloped research areas, as well as the underlying tensions or controversies in Medicine 2.0’s diverse interest groups.
Methods: In the first phase, we employ a thematic analysis of online definitions, that is, the most important linked papers, websites, or blogs in the Medicine 2.0 community itself. In a second phase, this definition is then applied across a series of academic papers to review Medicine 2.0’s core literature base, delineating it from a wider concept of eHealth.
Results: The terms Medicine 2.0 and Health 2.0 were found to be very similar and subsume five major salient themes: (1) the participants involved (doctors, patients, etc); (2) its impact on both traditional and collaborative practices in medicine; (3) its ability to provide personalized health care; (4) its ability to promote ongoing medical education; and (5) its associated method- and tool-related issues, such as potential inaccuracy in enduser-generated content. In comparing definitions of Medicine 2.0 to eHealth, key distinctions are made by the collaborative nature of Medicine 2.0 and its emphasis on personalized health care. However, other elements such as health or medical education remain common for both categories. In addition, this emphasis on personalized health care is not a salient theme within the academic literature. Of 2405 papers originally identified as potentially relevant, we found 56 articles that were exclusively focused on Medicine 2.0 as opposed to wider eHealth discussions. Four major tensions or debates between stakeholders were found in this literature, including (1) the lack of clear Medicine 2.0 definitions, (2) tension due to the loss of control over information as perceived by doctors, (3) the safety issues of inaccurate information, and (4) ownership and privacy issues with the growing body of information created by Medicine 2.0.
Conclusion: This paper is distinguished from previous reviews in that earlier studies mainly introduced specific Medicine 2.0 tools. In addressing the field’s definition via empirical online data, it establishes a literature base and delineates key topics for future research into Medicine 2.0, distinct to that of eHealth. [J Med Internet Res 2008;10(3):e23]
236 citations
Cites background from "Web 3.0 and medicine"
...Field’s existence Various Guistini [56]...
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...0 tools such as social bookmarking will become redundant [56]....
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TL;DR: In this article, a comprehensive literature search across the Academic Search Premier, Education Research Complete, ERIC, and PsycINFO databases was conducted to discuss evidence-based pedagogical approaches related to the use of Web 2.0 technologies in both K-12 and higher education settings.
208 citations
Cites background from "Web 3.0 and medicine"
...Web 3.0, on the other hand, enables computers to communicate with each other (Guistini, 2007)....
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...Perhaps, the primary feature of Web 3.0 is that it uses metadata, which is data about data (Guistini, 2007)....
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TL;DR: An SNS for people with depressive tendencies provides various opportunities to obtain support that meets users’ needs, but it is recommended that participants do not use SNSs when they feel that the SNS is not user-selectable, when they get egocentric comments, when friends have a negative assessment of the S NS, or when they have additional psychological burden.
Abstract: Background: Internet peer support groups for depression are becoming popular and could be affected by an increasing number of social network services (SNSs). However, little is known about participant characteristics, social relationships in SNSs, and the reasons for usage. In addition, the effects of SNS participation on people with depression are rather unknown. Objective: The aim was to explore the potential benefits and harms of an SNS for depression based on a concurrent triangulation design of mixed methods strategy, including qualitative content analysis and social network analysis. Methods: A cross-sectional Internet survey of participants, which involved the collection of SNS log files and a questionnaire, was conducted in an SNS for people with self-reported depressive tendencies in Japan in 2007. Quantitative data, which included user demographics, depressive state, and assessment of the SNS (positive vs not positive), were statistically analyzed. Descriptive contents of responses to open-ended questions concerning advantages and disadvantages of SNS participation were analyzed using the inductive approach of qualitative content analysis. Contents were organized into codes, concepts, categories, and a storyline based on the grounded theory approach. Social relationships, derived from data of “friends,” were analyzed using social network analysis, in which network measures and the extent of interpersonal association were calculated based on the social network theory. Each analysis and integration of results were performed through a concurrent triangulation design of mixed methods strategy. Results: There were 105 participants. Median age was 36 years, and 51% (36/71) were male. There were 37 valid respondents; their number of friends and frequency of accessing the SNS were significantly higher than for invalid/nonrespondents (P = .008 and P = .003). Among respondents, 90% (28/31) were mildly, moderately, or severely depressed. Assessment of the SNS was performed by determining the access frequency of the SNS and the number of friends ( P = .02 and P = .01). Qualitative content analysis indicated that user-selectable peer support could be passive, active, and/or interactive based on anonymity or ease of use, and there was the potential harm of a downward depressive spiral triggered by aggravated psychological burden. Social network analysis revealed that users communicated one-on-one with each other or in small groups (five people or less). A downward depressive spiral was related to friends who were moderately or severely depressed and friends with negative assessment of the SNS. Conclusions: An SNS for people with depressive tendencies provides various opportunities to obtain support that meets users’ needs. To avoid a downward depressive spiral, we recommend that participants do not use SNSs when they feel that the SNS is not user-selectable, when they get egocentric comments, when friends have a negative assessment of the SNS, or when they have additional psychological burden. [J Med Internet Res 2009;11(3):e29]
117 citations
Cites background from "Web 3.0 and medicine"
...0 [39], new technologies and services emerge and are put to use even before their benefits or harms are assessed....
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TL;DR: E-health advances being explored with chronic conditions other than pain that may provide opportunities for developments in chronic pain management are summarized and critically appraise current technological developments as they might apply to pain.
Abstract: There are significant geographic, economic, and educational barriers for patients with chronic pain accessing evidence-based treatments. Recent developments in computing and sensing technologies have led to applications facilitating the management of other long-term health conditions such as diabetes, stroke, heart failure, and depression. Technology could also offer promising solutions to the management of chronic pain conditions and the current barriers of access. A number of technologies are being explored worldwide with a variety of goals. In what follows we focus largely on electronicbased innovations offered as part of a solution for the management of chronic pain. For ease of narration we adopt the term ‘e-health’ to encompass developments labelled variously as ‘telemedicine’, ‘telehealth’, ‘telecare’, ‘assistive technology’, ‘cybertherapy’. We aim to (i) introduce and scope the developing field, (ii) review the extant projects in pain, drawing on basic science, clinical case studies and where available treatment intervention trials, (iii) summarize e-health advances being explored with chronic conditions other than pain that may provide opportunities for developments in chronic pain management, (iv) critically appraise current technological developments as they might apply to pain, and (v) discuss challenges to further development.
108 citations
Cites background from "Web 3.0 and medicine"
...0 technology means that we could soon see more personalized mobile healthcare interventions [12]....
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References
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