DEVELOPING INTEROPERABLE SEMANTIC E-HEALTH

TOOLS FOR SOCIAL NETWORKS

Juha Puustjärvi

Helsinki University of Technology, Innopoli 2, Tekniikantie 14, Espoo, Finland

Leena Puustjärvi

The Pharmacy of Kaivopuisto, Neitsytpolku 10, Helsinki, Finland

Keywords: Social networks, Web 2.0, e-Health, Medical applications, Semantic web, Ontologies, Knowledge

management.

Abstract: Many studies have indicated that most patients are not satisfied with the medical treatment information on

the Web though many e-health tools provide links to materials or other websites that have information about

patient’s health conditions or medications. In addition, many studies have demonstrated that patients should

have easy access to their own health information as well as to any information they need in order to make

decisions about their own heath care. However, while there are a variety of tools for managing and sharing

medical information, no integrated tool for health information management and sharing has been developed.

Satisfying this challenge requires a means to capture and interconnect information from various sources

which are relevant to one patient and create personal health space containing links to the health information

that are related to the customer or of which the customer is interested in. In this paper we describe our work

on developing a personal health assistant, which integrates the tools supporting personal health records,

information therapy and health oriented blogs. Technically the personal health assistant is based on

knowledge management technologies, and it is easily extensible to capture additional e-health tools.

1 INTRODUCTION

Although the term social networking has started to

be used fairly recently, online social networks

existed before the Web in the form of email

discussion lists and bulletin boards, and which are

still commonly used.

Nowadays social networking has encouraged

new ways for communicating and sharing

information (Childs, 2007). Social networking Web

sites are regularly used by millions of people.

Advances in social networking and the

widespread use of Internet are also changing the way

health care is provided (Lewiset al., 2005). In

particular, health care provision is moving from a

disease oriented model, where the treatment

decisions are made almost exclusive by physicians

based on their clinical experience, to a patient

oriented model, where patients are active

participants in the decision making process about

their own health (Tuil et al., 2006, Trevana et al.,

2006). The term e-health is commonly used to

describe this evolution in health care.

Many studies have indicated that most patients

are not satisfied with the medical treatment

information on the Web though many e-health tools

provide links to materials or other websites that have

information about patient’s health conditions or

medications (Butcher, 2007; Kemper, 2008). In

particular, they have regarded many sites to be

overly commercial, or they could not determine the

source of the information (Puustjärvi and Puustjärvi,

2008).

E-health covers many fields including electronic

health records (Vesely, 2006, Ghani et al., 2008;

EHR, 2009), personal health records (Kaelber et al.,

2008; Raisinghani, 2008), evidence based medicine

(Metler and Kemper, 2004), information therapy

(Kemper, 2008) and disease management (Stalidis et

al., 2001). There are also various kinds of e-health

tools focusing different fields of health care, each

305

PuustjÃd’rvi J. and PuustjÃd’rvi L.

DEVELOPING INTEROPERABLE SEMANTIC E-HEALTH TOOLS FOR SOCIAL NETWORKS.

DOI: 10.5220/0002784003050312

In Proceedings of the 6th International Conference on Web Information Systems and Technology (WEBIST 2010), page

ISBN: 978-989-674-025-2

having their own user interfaces (Puustjärvi and

Puustjärvi, 2006).

A problem here is that these e-health tools do not

interoperate. This lack complicates the usability of

these systems as well as restricts the services that the

e-health tools can provide.

In order to illustrate the potential gain of

interoperation (or integration) let us consider the

tools supporting personal health records (PHRs),

Information therapy (Ix) and health oriented blogs.

A PHR is a record of a consumer that includes data

gathered from different sources such as from health

care providers, pharmacies, insures, and the

consumer (Angst et al., 2008). Its main goal is to

provide a complete and accurate summary of the

health and medical history of a consumer (Agarwal

and Angst, 2006) while the goal behind information

therapy is to prescribe the right information to right

people at right time (Mettler and Kemper, 2004).

Hence, by integrating PHR system and a system

providing Ix we could automate Ix based on the

content of the PHR as it describes patient health and

medication history and the present state as well.

Further, by integrating e-health oriented blogs to

PHR tool we could automatically deliver the blog

items to patient, which are related to patient’s

medication or illnesses. So from patient’s point of

view the integrated health tool would be like an

electronic newspaper that is personalized according

to patient’s dynamic health and medication profile.

This kind of automation in delivering personal

health information would be useful as many studies

have demonstrated that the provision of information

therapy can increase compliance with treatment

regiments, satisfaction with the health care provider

and medical facility, and improve the ultimate health

outcome for the individual (Butcher, 2007). It is also

turned out that patients who do not understand their

treatment instructions, disease management, or

prescription requirements are more likely to

mishandle their health, be hospitalized more

frequently, and have much higher medical costs than

their more involved counterparts (Kaelber et al.,

2008).

In this paper, we describe our work on the

integration of the tools supporting PHRs, Ix and

health oriented blogs. We call such integrated tools

as personal health assistants or PHAs for short. In

this paper we do not consider PHAs from security

point of view though it is important aspect as it

specifies how well the tool can provide

confidentiality and nonrepudiation by authenticating

the parties involved and maintaining access control.

Instead the focus of this paper is to consider a PHA

from interoperation and data management points of

view.

The main advantage of a PHA is that patients do

not need to navigate on the Web to find evidence-

based medical information or relevant blog items.

Instead the relevant information or its links are

automatically delivered to patients’ PHA. Which

information is delivered depends on the content of

the patient’s personal health records, and thus the

delivery can be targeted automatically.

The corner stone of the system is the PHA-

ontology, which captures the ontologies used in

PHR, Ix and in the blog. Technically PHA is based

on knowledge management technologies and is

easily extensible to capture additional e-health tools.

The rest of the paper is organized as follows.

First, in Section 2, we consider the application

integration/interoperation strategies used in

developing the PHA, and the role of Knowledge

base in storing the health information constituting

the PHA-ontology. Then, in Section 3, we present

the components of the PHA, and introduce the

notions of Semantic blog, Semantic PHR and

Semantic Ix.

After this, in Section 4, we consider the PHA-

ontology, which is shared by all the interoperable e-

health tools. We represent parts of the ontology in a

graphical form as well as in OWL (Web Ontology

Language OWL) (OWL, 2006). We also illustrate

how ontology instances can be presented in RDF

(Resource Description Language) (RDF, 2004).

Finally Section 5 concludes the paper by discussing

the advantages and disadvantages of our represented

solutions.

2 THE ROLE OF KNOWLEDGE

MANAGEMENT IN PHA

2.1 Application Integration and

Interoperation Strategies

Basically the term integration refers to the idea of

putting diverse concepts together to create an

integrated whole (Singh and Huhns, 2005). Instead

interoperation refers to making applications work

together by sharing the appropriate messages but

without any single conceptual integration.

Even though the approaches for the

interoperation of various applications vary

considerable, the principal distinction between

Information-oriented, Process-oriented and Service-

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306

oriented and Portal-oriented application

interoperation can be done (Lithicum, 2004).

• In Information-oriented approaches

applications interoperate through a database or

knowledge base.

• In Process-oriented (also called workflow–

oriented) approach the interoperation is

controlled through a process model that binds

processes and information within many

systems.

• In Service-oriented interoperation applications

share methods (e.g., through Web service

interface) by providing the infrastructure for

such method sharing.

• In Portal-oriented application integration a

multitude of systems can be viewed through a

single user interface, i.e., the interfaces of a

multitude of systems are captured in a portal

that user access by their browsers.

From user’s point of view our used application

integration strategy follows the portal oriented

approach as the multitude of e-health tools can be

viewed through a single user interface. On the other

hand, we use the Information-oriented approach in

achieving the interoperability between the e-health

tools. That is, the tools interoperate through sharing

a knowledge base, and the ontology is developed by

integrating the ontologies of the interoperable e-

health tools.

2.2 Knowledge Management and PHA

Knowledge management (Daconta et al., 2003)

concerns with acquiring, accessing and maintaining

knowledge within an organization. Knowledge

management system refers to a computer based

system for managing knowledge in organizations. A

knowledge base is a special kind of database for

knowledge management. It provides the means for

the computerized collection, organization, and

retrieval of knowledge for various applications.

Today an ever expanding set of knowledge

management systems are using the technologies of

the Semantic Web. That is, knowledge is organized

according to ontologies, and automated tools are

used in accessing and maintaining knowledge.

In particular, knowledge management is

considered to be important because organizations

view internal knowledge as an intellectual asset from

which they can draw greater productivity, create

new value, and increase their know-how (Daconta et

al., 2003).

We argue that this is also true with respect to e-

health. That is, by acquiring, accessing and

maintaining health-oriented knowledge we can

develope e-health tools that create new value and

increase the productivity of health care. Therefore

both knowledge management and the development

of e-health tools should be developed iteratively, so

as to provide mutual feedback.

However, for the present, the deployment of the

knowledge management technologies in e-health is

quite limited. The main obstacle is that the

developed schemas, such as those based on HL7

RIM (Dolin et al., 2001), are too weak with respect

to their semantics.

In developing knowledge oriented systems the

key idea is to revolve all applications around the

shared ontology. In our case, it means the integration

of the PHR-ontology, the Blog-ontology and the Ix-

ontology and then revolving the Semantic Blog,

Semantic PHR and the semantic Ix around this

integrated ontology as illustrated in Figure 1. The

integrated ontology is called PHA-ontology. So the

components of the PHA interoperate by accessing

the shared PHA-ontology.

PHR-

ontology

Personal health assistant (PHA)

User

Blog-ontology

Ix-ontology

Knowledge base

PHA-ontology

Semantic blog Semantic PHRs Semantic Ix

Knowledge Management System

User

Browser Browser

Internet

…

Figure 1: The Architecture of a PHA.

User interacts with the PHA by a browser, and so

all the documents for user are presented in HTML.

However, all the content in the knowledge base are

in OWL, i.e., represented by XML-documents.

The required transformation between these

representation formats can be automatically done.

DEVELOPING INTEROPERABLE SEMANTIC E-HEALTH TOOLS FOR SOCIAL NETWORKS

307

This requires that a specific style sheet is specified

for the translation for each document type. A

language associated with style sheets is XSLT

(Extensible Stylesheet Language) (Harold and Scott

Means, 2002). It is a markup language that uses

template rules to specify how a style sheet processor

transforms an XML document.

3 THE COMPONENTS OF THE

PHA

We now consider blogs, PHRs and Ix. We first give

a short overview of these terms, and then we

consider their semantic variations, i.e., how they can

be implemented by exploiting a knowledge base

3.1 Semantic Blogs

Blog represents a technology of Web 2.0, which is a

controversial term in that various definitions have

given for the term Web 2.0. A commonly used

definition is that Web 2.0 refers to a second

generation of services available on the Internet that

let people collaborate and share information online.

It is also regarded as synonymous with the term

Internet based social networking. The term social

network usually refers to a social structure made of

individuals or organizations called "nodes," which

are connected by one or more specific types of

interdependency, such as friendship.

Blogs provides a way for representing content in

social networks. Typically blogs are web pages that

contain a series of frequently generated entries by a

person or a group. A personal blog is an ongoing

diary or commentary by an individual. The entries

in a blog (text, links, figures, video or audio files)

are presented in chronological order with the latest

entry listed first.

Blogs are typically used on specific subjects,

which can be specified by tags such as keywords or

small phrases. Each item in a blog can be associated

with one or more tags. Usually sites which provide

tagging functionalities also combine it with sharing

capabilities, i.e., allow someone to share his or her

blog items with other people.

Many blogs use RSS feeds (i.e., RSS documents)

for allowing user subscriptions and thus leverages

the creation of blog networks. RSS is most

commonly translated as “Really Simple

Syndication”. Syndication refers to making web

feeds available from a site in order to provide other

people with the summary of the website’s recently

added content. In general, RSS is a family of web

feed formats used to publish frequently updated

works such as blog entries in a standardized format.

Web feeds includes full or summarized text and

metadata such as publishing dates and authorship.

By the tern semantic blogs we refer to blogs

which data is organized according to an ontology,

called blog ontology. The purpose of the blog

ontology is to describe the concepts of the domain in

which the blog takes place. Hence, blog ontology

describes the concepts, as well as their relationships,

such as blog-entry, predecessor and subject.

In our adopted approach semantic blogs are

maintained by a knowledge management system,

which provides data management functionalities

such as queries, updates and insertions. Such

functionalities can also be used in producing

summaries. Therefore in using semantic blogs RSS

feeds that are used with traditional blogs are not

needed. Neither tagging mechanism is needed as the

blog ontology captures the classification of the blog

entries, i.e., the relationships between blog entries

and classification system (e.g., a taxonomy) can be

specified in the blog ontology.

3.2 Semantic PHRs

A PHR is a record of a consumer that includes data

gathered from different sources. It includes

information about medications, allergies,

vaccinations, illnesses, laboratory and other test

results, and surgeries and other procedures.

A PHR should provide a complete and accurate

summary of the health and medical history of a

consumer. It is accessible to the consumer and to

those authorized by the consumer. It is not the same

as electronic health record (EHR), which is designed

for use by health care providers.

PHRs can be classified according to the platform

by which they are delivered. In internet-based PHRs

health information is stored at a remote server, and

so the information can be shared with health care

providers. Some PHRs also have the capacity to

import data from other information sources such as a

hospital laboratory and physician office. However,

importing data to PHRs from other sources requires

the standardization of PHR-formats.

Various standardization efforts on PHRs have

been done. In particular, the use of the Continuity of

Care Record (CCR standard) of ASTM (CCR, 2009)

and HL7’s Continuity of Care Document (CCD

standard) (CCD, 2009) has been proposed. From

technology point of view CCR and CCD-standards

represent two different XML schemas designed to

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store patient clinical summaries. However, both

schemas are identical in their scope in the sense that

they contain the same data elements.

A problem with XML-based PHRs is that their

data is document-centric-data, i.e., they are

collections of documents such as documents

including lab tests, prescribed medications and

illnesses. Instead the effective usage of PHRs is

mainly data centric, meaning that data should be

extracted from various documents and then

integrated according to specific criteria.

For example, a consumer may be interested to

know the average blood pressure and/or blood sugar

concentration during the time periods he or she was

using a drug for blood pressure, or the consumer

may be interested to know the cholesterol values

when he or she was on a diet. Unfortunately the

computation required by such queries is not

provided by the query languages such as XPath

(XPath, 2008) and XQuery (XQuery, 2008)] which

are designed to address XML documents.

In order to allow high expression power in

accessing PHRs we have developed an ontology for

the data stored in PHRs. It describes the concepts of

the domain in which PHRs take place. Hence, a

PHR-ontology describes the concepts, as well as

their relationships, such as demographics, insurance

information, immunizations, allergies, diagnoses,

procedures and medication. In developing the PHR-

ontology, we have exploited the XML-schema of the

CCR file, which is originally developed for storing

patient clinical summaries.

The PHRs which data is organized according to

an ontology we call semantic PHRs. That is,

semantic PHRs exploit knowledge management

systems, and thus they provide high expression

power in accessing the PHR-ontology. The PHA-

ontology, which is presented in Section 4, includes

the PHR-ontology.

3.3 Semantic Information Therapy

Information therapy is a type of healthcare

information service that has emerged in the past

decade. The goal behind information therapy is to

prescribe the right information to right people at

right time (Kemper, 2008). Information therapy is

also described as “the prescription of specific

evidence based medical information to specific

patients at just the right time to help them make

specific health decisions or behavior changes”

(Mettler and Kemper, 2004).

Information therapy applies to a wide range of

situations and context. For example, information

therapy may be a physician-written prescription

telling a patient what to read, or it may use to help a

patient to make treatment decision such as whether

to continue medication.

Information therapy can be compared to similar

concepts in medicine such as drug therapy,

physiotherapy or bibliotherapy. However,

information therapy differs from these in the sense

that by exploiting information technology

information therapy aims at providing

personalization, targeting and documentation.

There is a variety of paper-based mediums for

delivering information therapy such as handing out

information pamphlets or sending them through the

post. There are also many electronic infrastructures

(such as electronic medical record systems, personal

digital assistants, order entry systems and personal

health records) that have been proposed for

delivering information therapy.

By semantic information therapy we refer to the

ontology based management of the information

entities such that prescribing can be automated by

exploiting the Ix-ontology. The idea behind this is

that the information entities can be modelled in an

Ix-ontology in the way that their relationship to

other relevant health care concepts (e.g., diseases

and medication) can be specified.

In our used Ix-ontology the class

InformationEntity (IE) is further divided into

subclasses such as ProductIE, DiseaseIE,

ColesterolTestIE, and BlodPressureTestIE. Their

relationships to other relevant classes in the PHA-

ontology are considered in the next section.

4 PHA-ONTOLOGY

Originally ontology is the philosophical study of the

nature of being, existence or reality in general, as

well as of the basic categories of being and their

relations (Antoniou and Harmelen, 2004).

Traditionally listed as a part of the major branch of

philosophy known as metaphysics, ontology deals

with questions concerning what entities exist or can

be said to exist, and how such entities can be

grouped, related within a hierarchy, and subdivided

according to similarities and differences.

In computer science, an ontology is a general

vocabulary of a certain domain, and it can be

defined as “an explicit specification of a

conceptualization” (Gruber, 1993). Essentially the

used ontology must be shared and consensual

terminology as it is used for information sharing and

exchange.

DEVELOPING INTEROPERABLE SEMANTIC E-HEALTH TOOLS FOR SOCIAL NETWORKS

309

Essentially ontology tries to capture the meaning

of a particular subject domain that corresponds to

what a human being knows about that domain. It

tries to characterize that meaning in terms of

concepts and their relationships. It is typically

represented as classes, properties, attributes and

values. Depending on the generality level of

conceptualization, different types of ontologies are

needed (Puustjärvi and Puustjärvi, 2009). Each type

of ontology has a specific role in information

sharing and exchange.

The purpose of our used PHA-ontology is to

describe the concepts of the domain in which blogs,

PHRs and Ix take place. In order to illustrate its

content consider Figure 2, which represents a subset

of the PHA-ontology. In this graphical

representation ellipses represent classes and

subclasses, and rectangles represent data and object

properties. Classes, subclasses, data properties and

object properties are modelling primitives in OWL.

Patient

Me di cation

La b T es t

BloodPressureTest

ProductProductNa m e

BrandName

StrenghtUnit

Source

ActorIDActorRole

ColesterolTest

Val ue Unit

Val ue Uni t

PatientId

PatientNam e

SubclassOf

Use s

Perform ed

ContainsStrenghtVa lue

O rig ina t es

Me di c ati on I d

In f o rma t io nE n tit y

SubclassOfSubclassOf SubclassOf

Disease

Name

RelatesTo

DiseaseIE

Deals

SubclassOf

ProductIE

Deals

ColesterolTestIE

Deals

BloodPressureTestIE

Deals

Date Sour ce

URL

Author

Predecessor

Deals Subject

Blog BlogNameIncludes

BlogItem

Relates

Ins ertion D at e

Associates

URL

Figure 2: A PHA-ontology in a graphical form.

In the graphical ontology:

• the classes Patient and Medication are connected

by the object property Uses,

• the classes BlogItem and Medication connected

by object property Relates, and

• the classes informationEntity and Medication are

connected by the object property Associates.

Note that based on the above classes and object

properties it is possible to process the queries

presented in Section 1 (Introduction). That is, based

on the medication the patient uses, the PHA can

automatically deliver to the patient the blog items

and information entities that are related to

medication the patient uses.

The OWL Web Ontology Language is designed

for use by applications that need to process the

content of information instead of just presenting

information to humans. By an ontology language it

is possible to write explicit, formal

conceptualizations of domains. So OWL facilitates

greater machine interpretability of Web content than

that supported by XML, RDF, and RDF Schema by

providing additional vocabulary along with a formal

semantics.

A part of the graphical ontology of Figure 2 is

presented in OWL in Figure 3.

<rdf:RDF

xmlns:rdf=http://www.w3.org/1999/02/22-rdf-syntax-nsl#

xmln s:rdfs=http://www.w3.org/2000/01/rdf-schema#

xmln s:owl=http://www.w3.org/2002/07/owl#>

<owl:Ontology rd f:about=“”PHA/>

<owl:Class rdf:ID=“Blog/”>

<owl:Class rdf:ID=“BlogItem/”>

<owl:Class rdf:ID=“Patient/”>

<owl:Class rdf:ID=“Medication/”>

<owl:Class rdf:ID=“Source/”>

<owl:Class rdf:ID=“Product/”>

<owl:Class rdf:ID=“LabTest/”>

<owl:Class rdf:ID=“BloodPressureTest”>

<rdfs:subClassOf rdf:resource=“#LabTest”/>

</o wl:Class>

<owl:Class rdf:ID=“ColesterolTest”>

<rdfs:subClassOf rdf:resource=“#LabTest”/>

</o wl:Class>

<owl:ObjectProperty rdf:ID=“Relates”>

<rdfs:range rdf:resource=“#Medication”/>

</owl:ObjectProperty>

<owl:ObjectProperty rdf:ID=“Uses”>

<rdfs:range rdf:resource=“#Medication”/>

</owl:ObjectProperty>

</rdf:RDF>

Figure 3: Representing the PHA-ontology in OWL.

In data storage (knowledge base) the instances of

the health ontology are presented by RDF. RDF is a

framework for representing information in the Web.

It itself is a data model. Its modelling primitive is an

object-attribute-value triple, which is called a

statement.

A description may contain one or more

statements about an object. For example, in Figure 4,

the description concerning “Voltaren” contains two

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310

statements: the first states that its type is

ProductName in the PHA-ontology, and the second

states that its BrandName in the PHA-ontology is

Diclofenac.

<rdf:RDF

xmlns : rdf=”http://www.w3.org/1999/02/22-rdf-syntax-ns

#”

xmlns : xsd=”http://www.w3.org/2001/XMLSchema#

”

xmlns : po=http://www.lut.fi/ontologies/PHA-ontology#

<rdf:Description rdf:about=”120962-K3”>

<rdf:type rdf:resource=“&po;Patient”/>

<po : PatientName>Lisa Smith</po : PatientName>

</rdf : Description>

<rdf:Description rdf:about=” MO-5481”>

<rdf:type rdf:resource=“&po;Medication”/>

<po : Contains>Voltaren</po: Contains>

<po : StrenghtValue rdf:datatype=

”&xsd;integer”>30</po: StrenghtValue>

</rdf : Description>

<rdf:Description rdf:about=” 211708-8”>

<rdf:type rdf:resource=“&po;Source/>

<po : ActorRole>Pharmacy</po : ActorRole>

</rdf : Description>

<rdf:Description rdf:about=” Voltaren”>

<rdf:type rdf:resource=“&po;ProductName”/>

<po : BrandName>Diclofenac</po : Contains>

</rdf : Description>

</rdf:RDF>

Figure 4: Representing ontology instances in RDF.

5 CONCLUSIONS

Internet has changed the way people work, bank and

shop, but a similar change in health care has been

small-scale. However, recent interest in social

networking and the evolvement towards patient-

centric healthcare is speeding this change. At the

same time the use of patient-centric e-health tools is

rapidly increasing. These tools cover many fields

including electronic health records, personal health

records, telemedicine, evidence based medicine,

information therapy and disease management.

A problem is that the e-health tools each have

their own interfaces. By integrating the e-health

tools we can achieve two gains: simplify user

interaction and provide new more advanced services.

The situation is analogous with many organizations

having heterogeneous legacy systems each having

own user interfaces. Hence also the solutions

developed for the integration and interoperation of

organizational and business applications can be

adopted for the e-health case as well.

We have designed an e-health tool (PHA) which

captures the functions of a personal health record,

information therapy and health oriented blog. From

enterprise application integration (EAI) point of

view it represents information oriented integration

approach, and from technology point of view it

represents knowledge management technologies

such as RDF and OWL.

Moving from XML-archives to semantic PHA

requires the introduction of the PHA-ontology, and

transforming the XML-based medical and health

information in the format that is compliant with the

PHA-ontology. This transformation can be executed

automatically. However, a specific stylesheet must

be specified for each transformed document type.

The PHA-ontology stores the urls of the

information entities and blog items, and so the

information entities as well as the blog items may be

stored in any server. However, the content of the

PHRs should be stored in centralized way in the

knowledge base as otherwise making expressive

queries on the PHRs is not possible.

REFERENCES

Agarwal R, Angst C.M., 2006. Technology-enabled

transformations in U.S. health care: early findings on

personal health records and individual use, In Galletta

G, Zhang P, (Eds.), Human-Computer Interaction and

Management Information Systems: Applications (Vol.

5). Armonk, NY: M.E. Sharpe, Inc., pp. 357-378.

Angst, C.M., Agarwal, R, Downing, J., 2008. An

empirical examination of the importance of defining

the PHR for research and for practice, Proceedings of

the 41st Annual Hawaii International Conference on

System Sciences.

Antoniou, G., Harmelen, F., 2004. A semantic web primer.

The MIT Press.

Butcher L., 2007. What the devil is information therapy?

Available at:

http://www.managedcaremag.com/archives/0706/0706

.infotherapy.html

CCD, 2009. What Is the HL7 Continuity of Care

Document? Available at:

http://www.neotool.com/blog/2007/02/15/what-is-hl7-

continuity-of-care-document/

CCR, 2009. Continuity of Care Record (CCR) Standard.

Available at: http://www.ccrstandard.com/.

Daconta, M., Obrst, L., Smith, K., 2003. The semantic

web. Indianapolis: John Wiley & Sons.

Dolin, R. H., Alschuler; L., Beerb, C., Biron, P. V.,

Boyer, S- L, Essin, D., Kimber, E., Lincoln, T., and

Mattison, J-E., 2001. The HL7 Clinical Document

Architecture. J. Am Med Inform Assoc (6). pp 552-

569.

EHR, 2009. Electronic Health Record, Available at:

http://en.wikipedia.org/wiki/Electronic_health_record.

Ghani, M., Bali, R.K., Naguib, R., Marshall, I.M.,

Wickramasinghe, N.S., 2008. Electronic health

DEVELOPING INTEROPERABLE SEMANTIC E-HEALTH TOOLS FOR SOCIAL NETWORKS

311

records approaches and challenges: a comparison

between Malaysia and four East Asian countries,

International Journal of Electronic Healthcare, Vol. 4,

No.1 pp.78-104-77.

Childs, S., 2007. Social networking in the health context

Export, He@lth Information on the Internet, Vol. 56,

No. 1., pp. 1-2.

Gruber, T. R., 1993. Toward principles for the design of

ontologies used for knowledge sharing. Padua

workshop on Formal Ontology.

Harold, E., Scott Means W. ,2002. XML in a Nutshell.

O’Reilly & Associates.

Kaelber, D. Jha, A. Johnston, D. Middleton, B.and Bates,

D., 2008. A Research Agenda for Personal Health

Records (PHRs), J. Am. Med. Inform. Assoc.,

November 1,15(6). pp. 729 - 736.

Kemper D.W., 2008. White paper: The Business Case for

Information therapy. Available at:

http:/www.informationtherapy.org/publications/docum

ents/e0678.pdf

Lewis, D, Eysenbach. G., Kukafka, R., Stavri P.Z., and

Jimison, H., 2005. Consumer health informatics:

informing consumers and improving health care. New

York: Springer.

Lithicum, D., 2004. Next Generation Application

Integration. Boston: Addison-Wesley.

Mettler M., Kemper D., 2004. Information Therapy:

Health Education One Person at a Time. Health

Promotion Practice. 4(3) 214-217.

OWL, 2006. Web Ontology Language.

http://www.w3.org/TR/owl-ref/

Puustjärvi, J., Puustjärvi, L., 2006. The challenges of

electronic prescription systems based on semantic web

technologies. In Proc. of the 1st European Conference

on eHealth, pp. 251-261.

Puustjärvi, J., Puustjärvi, L., 2008. Using semantic web

technologies in visualizing medicinal vocabularies. In

the proc of the IEEE 8th International Conference on

Computer and Information Technology.

Puustjärvi, J., Puustjärvi, L., 2009. The role of medicinal

ontologies in querying and exchanging

pharmaceutical information, International Journal of

Electronic Healthcare, Vol. 5, No.1 pp. 1 - 13

Raisinghani. M.S. and Young, E., 2008. Personal health

records: key adoption issues and implications for

management, International Journal of Electronic

Healthcare. Vol. 4, No.1 pp.67-77.

RDF, 2004, Resource Description Framework (RDF).

Available at: http://www.w3.org/RDF/

Singh, M., Huhns, M. 2005. Service Oriented Computing:

Semantics Proceses Agents. John Wiley & Sons.

Stalidis, G., Prenza, A. Vlachos, N., Maglavera S.,

Koutsouris, D., 2001. Medical support system for

continuation of care based on XML web technology:

International journal of Medical Informatics, 64, 2001,

p. 385-400.

Trevena L., Davey H., Barratt A., Butow P., and Caldwell

P., 2006. A systematic review on communicating with

patients about evidence. Journal of Evaluation in

Clinical Practice. 12,(1): 13-23.

Tuil, W. S., Hoopen, A. J., Braat, D. D. M., Vries Robbe,

P.F., and Kremer J. A. M., 2006. Patient-centred care:

using online personal medical records in IVF practice,

Hum. Repro., November 1, 21(11). pp. 2955 - 2959.

Vesely, A., Zvarova, J., Peleska, J., Buchtela, D. and

Anger, Z. ,2006. Medical guidelines presentation and

comparing with Electronic Health Record,

International journal of Medical Informatics, No. 64,

pp. 240-245.

XPath, 2008. XML Path Language (XPath). Available at:

http://www.w3.org/TR/xpath.

XQuery, 2008. XQuery 1.0: An XML Query Language.

Available at: http://www.w3.org/TR/xquery/.

WEBIST 2010 - 6th International Conference on Web Information Systems and Technologies

312