=Paper=
{{Paper
|id=Vol-2823/Paper5
|storemode=property
|title=Knowing the Unknown: Unshielding the Mysteries of Semantic Web in Health Care Domain
|pdfUrl=https://ceur-ws.org/Vol-2823/Paper5.pdf
|volume=Vol-2823
|authors=Pallavi Nagpal, Deepika Chaudhary, Jaiteg Singh
}}
==Knowing the Unknown: Unshielding the Mysteries of Semantic Web in Health Care Domain==
https://ceur-ws.org/Vol-2823/Paper5.pdf
Knowing the Unknown: Unshielding the Mysteries of Semantic
Web in Health Care Domain
Pallavi Nagpal, Deepika Chaudhary and Jaiteg Singh
Chitkara University Institute of Engineering &Technology, Punjab, India.
Abstract
Health care is one of the popular segments wherein a huge amount of data is being generated
every second and in a heterogeneous format. It is only the use of semantic technologies that
can act as a guard for data integration and enriching it by adding proper semantics. The
Semantic Web gives us a sensible and versatile answer to perceive proficiency across the
congregation of healthcare data. Eventually the ultimate goal of improving the health care
practices depends on how the healthcare data is linked together. The major challenges to
chase the goal are not only limited to enable the integration of heterogeneous data sources but
also requires the development of certain tools for efficient search, ontology management, and
data analytics. The major objective of this study is to understand the technologies behind the
Semantic Web and to unshield the mysteries of application of Semantic Web in the healthcare
segment. The data for such an extensive survey was gathered from repositories of Pub Med,
Scopus, Web of Science, and Google Scholar along with few medical science libraries.
Keywords 1
Semantic Web, Healthcare, Ontology, Knowledge base, SNOMED-CT
ACI’21: Workshop on Advances in Computational
Intelligence at ISIC 2021, February 25-27, 2021, Delhi, India
EMAIL: pallavihptu@gmail.com (P.Nagpal);
deepika.chaudhary@chitkara.edu.in (D.Chaudhary.);
jaiteg.singh@chitkara.edu.in (J.Singh).
2020 Copyright for this paper by its authors. Use permitted under Creative
Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
1. Introduction Layer 1 Uniform Resource
Identifier (URI) – This layer uniquely
The better definition of Semantic Web identifies the available resources on the
(SW) always begins with the word Semantic. Internet. This layer ensures the uniqueness of
In simple words semantics signifies meaning. Objects.
Meaning allows effective use of data. Meaning
is mostly missing in many of the information
Layer 2 Extensible Mark-up
sources and is the job of the user or Language (XML) – A language that lets it
programming instruction to deliver the same. underlying user to create web pages with a
For example, if we simply look at the defined vocabulary. This layer also supports
tag it is used to highlight major headings but sharing documents across the web.
as technical people, it is understood that the Layer 3 & Layer 4 Resource
text which is surrounded by tag is of
more importance to the user when compared to Description Framework (RDF) - RDF
other. Basic semantics are attached for the acts like an Entity-Relationship(ER) model
search engines with tags; however, which is drafted for writing a set of statements
they are just solitary keywords and lacks when to describe objects (resources) available on the
linked. Semantics accord keywords with web. RDF Schema on the other hand is used to
effective meaning through relationships. The write ontologies to represent relationships
Semantic Web in simple terms is a web of data between web objects [26]. For integrating
paraphrased and linked together in ways to richness to the interoperability of data among
build context that follow a grammar & various domains Ontology Web Language
language construct. Although these semantics (OWL) was developed.
can also be added with a help of programming Layer 5 Proof & Trust layer - This
language in that case also formal standards are layer is all about the representation of logics to
missing and also these semantics cannot be deduce one document from another and there
shared, aggregated, and validated. One can validations. The trust layer ensures the faith
also attach these semantics through through the use of digital signatures.
programming languages but in that case, too, To conclude we can state that the Semantic
there are no formal standards to be followed, Web can be better understood as an extension
and sharing, aggregation, and validation of the WWW, it extends itself through the
among statements becomes complex if not usable, systematized semantics that is based on
impossible. The Semantic Web all together research in knowledge/facts representation and
supports the evolutionary nature of WWW. the logic to approach the goal of ubiquitous
The Semantic Web architecture is based on the information sharing. When compared to
Layered Approach. These layers have some WWW it's the Semantic Web which primarily
strong key dependencies between them. The consists of statements for application
Semantic Web layer cake presented in Figure consumption. These statements are not just
1 highlights these dependencies. plain statements for human interpretations but
also include logic and act as meaningful links
which can directly be interpreted by machines.
The outcome of this paper is to provide
insights on the recent advancements done in
this field. The more specific objectives can be
summarized as follows:
a) To create a theoretical foundation in the
area of data standards and interoperability,
ontologies and its visualization, semantic data
repositories and Semantic Web user Interfaces.
b) To reveal the current state of art of
Figure 1 : The Semantic Web Stack application of Semantic Web in Health Care
Domain.
c) To un-shield the successful use cases of segment. In this phase, a detailed study of
new approaches, techniques and Semantic literature has been carried on to improve the
Web applications in the field of health care quality and safety of web applications in the
data management. health care domain.
3.1 Data Standards and
The next section presents the present day
challenges which require attention of the Interoperability
researcher community. 3.1.1 Theoretical Foundation
2. Healthcare Challenges in Current The automation of various health care
services; usage of various medical information
Scenario systems and other technological instruments
The use of information systems and have put together and still is generating
technologically advanced medical devices in volumes of medical data and that too in
various health care hospitals is producing and heterogeneous form. The huge volume of data
will continue to produce vast amount of data. has to be processed in a meaningful form to
This huge collection needs to be explored and produce some valuable knowledge. This
transformed in such a way that it can be knowledge can lead to sound health care
converted into valuable information which can practices and thus can be of utmost use for
thus improve the healthcare processes. Which humans[26]. When the data is coming from
is not easy and can be daunting because of multiple sources it's the interoperability
various challenges? The following challenges standards that act as a bridge to integrate and
needs to be addressed: exchange the data across systems and services.
To achieve this requires Schema matching
a) Interoperability of health and medical techniques that can transform the data from
data. human-understandable to machine-ready
b) Personalization of Ontologies and its format. This technique when implemented can
visualization. produce good healthcare services thereby
c) Explosion of health data and Semantic reducing the cost by eliminating duplicate
Data Repositories operations. The authors in their work have
d) Development of new user friendly highlighted the meaning of interoperability for
interfaces Semantic Web applications which can be
defined as the vocabulary, organization, and
Semantic Web is attaining approval in structure of data required to integrate the data
addressing these challenges and therefore from multiple institutions [28]. Figure 2 gives
World Wide Web consortium (WWWC) a glimpse of various standards dealing with
established the Health Care and Life Science interoperability and the changes concerning
Interest Group in the year 2015 time.
(HCLSIG,2015) with the objective to defend
and support the use of Semantic Web
technologies in health care segment. The rest
part of the paper is organized as follows
section 3 provides a background and short
outline of prevailing literature for the
mentioned challenges, section 4 highlights the
new techniques and approaches relevant to
health care segment, section 5 concludes the
study.
3. Literature Review on Semantic Figure 2: Rate of Change/Year
(https://yosemiteproject.org/interoperability-
Web Technologies in Health Care roadmap/)
Domain
This section presents a short outline of a The interoperability can be categorized into
few of the prevailing literature towards two parts a) functional and b) semantic where
Semantic Web technologies in the health care functional deals with the common procedures
and semantic deals with the framing of a This standard can also leverage RESTFUL
common language which machine can web services. The given section categories the
understand in the end to end communication. literature review underwent by various
To make applications fully interoperable researchers.
requires standards. As per the literature
mentioned the standards can be divided into a) 1. Private and public sector organization to
Vocabulary or ontology Standards b) Data align their systems with Fast Healthcare
interchange and Integration standards c) Interoperability Resources is the upcoming
Health record maintenance standards. These standard for data exchange.
standards are established through four methods (https://www.dataversity.net/ semantic-
a) Adhoc b) Defacto b) Government- interoperability-future-healthcare-data/ ).s
mandated) Consensus. [14]
2. Development of various standards for
3.1.2 Present State of Art providing data interoperability; XML,
Below we present the literature survey GPS, Web Services, and Security, TCP/IP,
done in this direction: 802.11, GPS [12]
The authors worked on schema matching 3. Development of Reference Information
techniques and presented a method for Model (RIM) (HL7 Version 3 (V3) - a
automating the process for matching schema at suite of specifications based on HL7's
the field level; they achieved 71.8% when Reference Information Model (RIM)), its
mapping the four staged process which data elements, terminology, clinical
includes string matching and substring statements, templates, document
matching [25]. The authors in their paper have architecture.
discussed the standards required in Clinical (http://www.hl7.org/implement/standards/r
data management [15]. Clinical data im.cfm).
management deals with signs, operations, 4. Development of Collaborative Standard
medicines, and lab values for a particular Hubs for quality improvement in the
patient. The data here can only be healthcare segment across rural and urban
interoperable when in a structured form. This states (Srivastava et al., 2020).
transformation is a challenge and requires a lot
of research. Further data analysis also requires 3.2 Ontologies & its Visualization
the data to be converted in a structured form. 3.2.1 Theoretical Foundation
The authors have given the FAIR guiding Ontologies play a very important role in
principle as one of the possible solutions to Semantic Web applications. They act as a
this problem. The acronym of FAIR is common vocabulary for a specific domain
"Findability", "Accessibility", consisting of a terminological collection of
"Interoperability", and "Reusability". The terms together with the rules to combine these
authors in the study have mentioned Fast terms and form relations. They also act as a
Healthcare Interoperability Resources (FHIR) basis for interoperability.
as a newbie in the area of biomedical
informatics and healthcare [26]. These 3.2.2 Present State of Art
guidelines when followed can provide a
Here, we first survey the work done in this
technological edge over health level seven
direction. The authors in this paper did an
(HL7). It was also discussed in the Yosemitea
extensive survey on the current state of
manifesto (https://www.dataversity.net/
ontology development in the area of health
semantic-interoperability-future-healthcare-
care [20]. They have studied various papers in
data/) that for data exchange the Resource
the time frame of 2009 and 2018. They
Description Framework (RDF) to be used.
classified the work done by various
Existing data standards to be mapped with
researchers and proved that at present also
RDF's, Government agencies should mandate
there is a dire need for the development of new
RDF as a Universal Healthcare exchange
ontologies for delivering effective healthcare
language. These standards can be adopted in
services. The authors in this paper have
the area of legacy systems, modern medical
highlighted the role of ontology in decision
entities, and healthcare information systems.
making and how ontology that defines
concepts such as disease, location, and evidence-based decision support systems
environment and the interrelationships can [11].
influence the process of decision making in the 5. To work upon improving the quality of
public sector domain [26]. They also focused health services using semantic web
on the various mapping methods to work on technologies. Majorly the privacy and
interoperability issues. Further, they have security, trust, risks, and social
developed a centralized knowledge base for implications and the quality of information
healthcare systems specifically for the Tamil are important and play an important role in
Nadu Region of India. The author in this the semantic web areas [15].
paper has integrated the data which is coming 6. HCLS Knowledge Base is designed as a
from different sources and thus created an knowledge base where data from multiple
ontology [19]. They have followed four-way sources (PubMed, Clinical Trials) have
steps which include identification of data been stored. WHOsGHO – From WHO
sources, the formalization of concepts, statistics about 3 million of data has been
performed audit, and thus formulated converted to RDF [23]. Other projects
ontology. In the table given below we similar to the one mentioned above like
summarize the work done in the direction of DailyMed (2015) would continue to
creating new ontologies into past, Work in generate data from the health domain
progress, and Future Scope. The authors based on the principles of linked data [23]
stated that today also lot of data which is 7. The data hub is currently indexing
published by big organization like WHO is hundred of datasets which are tagged
published in proprietary format and not in under the healthcare category. The
accordance with Semantic Web standards and requirement of a lot of new projects in this
therefore it is still very difficult to integrate direction which can convert the data stored
and further process those chunks [28]. in a proprietary format to linked data [23]
Although a lot of research work (WHOGO,
2015), (PubMed, 2015), (NIH, 2015) has been 3.3 Semantic Websites user
carried in this direction still there is a long way Interface
ahead. The table below summarizes the
literature. 3.3.1 Theoretical Foundation
There are multiple projects such as
1. Development of a Centralized knowledge CardioShare and Bio2RDF which have certain
base. Personalization of ontologies for capabilities for navigating and querying the
describing the class hierarchies among underlying Semantic Web data. However they
chronically ill patients to form a decision lag intuition and can be more improvised.
support system for chronically ill patients 3.3.2 Present State of Art
(Riaño et al., 2012) The projects which are designed in this
2. Introduction of Electronic Health care direction should have the capabilities for
system to improve the various parameters searching and navigating through the Semantic
of health care services [19]. Web data [28]. There are certain projects
3. Improvement was done in various which have these capabilities like Bio2RDF
organizations dealing in the service and CardioShare, but these projects are limited
delivery segment, availability of reliable and are not that intuitive which means a novice
health data for healthcare providers, and user will find it very difficult to explore and
improves upon in the public health system. visualize the RDF triples. Therefore, there is a
A lot of new ontologies were also strong need to develop a good interface while
developed. The process of ontology developing the Semantic Web Applications.
validation was also improved [27]. The architecture is so simple that even a
4. Development of comprehensive beginner can explore it without much
monitoring frameworks in the field of difficulty. The authors in this paper have
maternal health informatics that would be designed and Semantic Web Portal (SWP)
created with the consensus of people which is a light weight portal to browse and
practicing it and also on the ontology- visualize the data generated and that too in
based data integration approach. These meaningful and friendly way [9]. This system
frameworks will facilitate the research and was deployed in Indiana University Health
Care Center to store and visualize the semantic application. A reasoner can therefore be
information from one place and was used by defined as a piece of code which is able to
multiple users i.e the patients the doctors, the infer logical consequences among a set of
practitioners to look all semantic information declared facts or axioms [8]. Correctness,
in one place. efficiency, soundness and completeness of the
1. Design and development of few interfaces new inferences drawn are some of the
to explore and navigate the Semantic Web important attributes of a good reasoner.
data. The portals can only read the JSON FaCT++, Pellet, HermiT, Kaon2, Hoolet are
files [18] the few examples of Semantic Web reasoners.
2. To make this process more interactive the The reasoners can be categorized into various
researchers are working on the strategies categories as per the various OWL profiles. In
which can also read the dynamically the study done by [9] the authors have a
generated JSON objects. For novice users, clearly described the various types of
the researchers are working to make the reasoners.
interface user friendly and easy to explore
[18]
3. Semantic Graph mining to identify and 4. Conclusions
rank the nodes and relationships. Although the technologies in the underlying
Development of user friendly and more domain have contributed a lot in health care
intuitive interface and graph visualisation segment still this study reveals that there still
methods to navigate through various certain challenges that needs to be resolved.
ontologies This survey reveals the present day challenges
(https://arxiv.org/abs/2008.03053). which require an ultimate attention of the
4. Representation of Semantic data in researcher .The end users can be benefitted in
proprietary formats- A lot of big case we get an optimal solution to the
organizations share the data in PDF or challenges mentioned herein.
spreadsheet format which makes it
difficult to integrate. CardioSHARE 5. Future Work and advancements
(Vandervalk, McCarthy& Wilkinson, in Semantic Health Care Segment
2008) represents a decentralized web
service framework that provides a Healthcare segment is generating a lot of data
SPARQL endpoint that enables querying continuously. Semantic interoperability of data
transparently resources in the "deep web" can help the human community a lot. The
from distributed and independent source. patients, the doctors, various organizations can
5. Bio2RDF in this project 11 billion of data get the maximum benefits from this. The
that comes from various heterogeneous figure below represents the future issues that
sources have been ported to RDF formats need to be addressed to make this technology a
(https://bio2rdf.org/).Bio2RDF in this huge success.
project 11 billion of data that comes from
various heterogeneous sources have been
ported to RDF formats
(https://bio2rdf.org/).
3.4Semantic Web and Reasoning
3.4.1Theoretical Foundation
The success behind any Semantic Web
application lies in the inference process.
Semantic Analysis is the mapping between
syntax and the meaning of the sentences.
Semantic analysis is used to check whether
inserted sentence is accurate or not. The
Semantic Web application designers are
extremely benefitted if they can select a Figure 3: Advancements in Semantic HealthCare
suitable reasoner as per the design of the
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