=Paper=
{{Paper
|id=Vol-2023/324-329-paper-52
|storemode=property
|title=Application of semantic integration methods for cross-agency information sharing in healthcare
|pdfUrl=https://ceur-ws.org/Vol-2023/324-329-paper-52.pdf
|volume=Vol-2023
|authors=Yury Akatkin,Elena Yasinovskaya,Michael Bich,Andrey Shilin
}}
==Application of semantic integration methods for cross-agency information sharing in healthcare==
https://ceur-ws.org/Vol-2023/324-329-paper-52.pdf
Proceedings of the XXVI International Symposium on Nuclear Electronics & Computing (NEC’2017)
Becici, Budva, Montenegro, September 25 - 29, 2017
APPLICATION OF SEMANTIC INTEGRATION METHODS
FOR CROSS-AGENCY INFORMATION SHARING IN
HEALTHCARE
Yu. M. Akatkin, E.D. Yasinovskaya, M.G. Bich, A.V. Shilin
Plekhanov Russian University of Economics, 36 Stremyanny per., Moscow, 117997, Russia
E-mail: u.akatkin@semanticpro.org, elena@semanticpro.org, misha@semanticpro.org,
a.shilin@semanticpro.org
Cross-agency Information sharing is a basic feature of digital economy in public sector.
Heterogeneous environment is inherent for the public sector as well as for other industries, which are
ready to digital transformations. The application of integration methods should guarantee the
achievement of unambiguous meaningful interpretation of data. The article represents comparative
analysis of basic integration approaches: (1) classic interaction via mediators, (2) integrated data
model (XML-based models implementation) and (3) semantic integration. We defined the advantages
of semantic integration and confirmed the possibility to use semantic core as a basis for a digital
health ecosystem. We implemented the example of semantic integration in healthcare within the
project of Plekhanov Russian University of Economics named the “Center of semantic integration”.
Keywords: semantic interoperability, semantic integration, cross-agency interaction, information
sharing, domain data model, information exchange, digital ecosystem, digital health, digital economy
© 2017 Yury M. Akatkin, Elena D. Yasinovskaya, Michael G. Bich, Andrey V. Shilin
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Proceedings of the XXVI International Symposium on Nuclear Electronics & Computing (NEC’2017)
Becici, Budva, Montenegro, September 25 - 29, 2017
1. Introduction
Digitalization is a priority for the future economic development of the Russian Federation.
Digital Health is one of the main industry directions that expands the federal program "Digital
Economy of the Russian Federation"1. The possibility to create digital health services in compliance
with the principles of semantic interoperability in a heterogeneous information environment taking
into account a multitude of actors (medical organizations, patients, doctors, insurance companies,
developers, etc.) and a multitude of diverse information resources is a scientific and practical task,
which is important for digital transformation in healthcare.
Currently, researchers as well as technical community around the world are working on data
standardization, semantic assets’ cataloguing and reuse, together with data models design and
dissemination, unification integration methods in order to implement them for the information
sharing in various knowledge domains.
At the semantic level, a unified description of data supports the integration, taking into
account the semantic properties in the context of a single ontology of the subject area [1]. A number
of works, for example [1-6], describes semantic integration methods and their advantages over the
traditional approaches. Despite the fact that “semantic modeling has been the subject of research
since the late 1970s” [3], the problem of heterogeneous data semantics that arise both within
information systems and during information exchange between them remains relevant [4].
The development of methods for the practical use of semantic integration is a key enabler for
digital transformation both at the national and sectoral level.
The objective of this article is to identify the advantages of semantic integration for the
implementation of information sharing principles, essential to the building of a digital health
ecosystem [7, 8]. To achieve this aim we made a comparative analysis of the existing approaches
used for the integration of data in information systems [6]. We confirmed the results of the analysis
by the approbation of the chosen method on real services of cross-sector interaction between the
information systems of the Ministry of Health of Russia and the Social Insurance Fund.
2. Comparative analysis of the existing data integration approaches
The researchers identify three approaches to the data integration of information systems in a
heterogeneous environment: (1) classic interaction via mediators, (2) integrated data model and (3)
semantic integration [6]. Russian practice of cross-agency interaction shows the frequent use of the
first method. NIEM (USA) [9, 10] is an example of the implementation of integrated XML data
models in the public sector and the European Union actively promotes the use of semantic integration
within ISA2 program, providing interoperability solutions for public administrations, businesses and
citizens [11].
To analyze the advantages or disadvantages of the existing integration methods, we consider
the possibility to implement them in a simplified (demonstration) example of information systems’
interaction in Russia. A special feature of this example is the use of really acting services that open
the access to the information systems of the state agencies.
In developing this example, we used the following scenario: the X-ray specialist applied to
the branch of the Federal Social Insurance Fund (FSIF) territorial body (hereinafter referred to as the
Branch) assigning for monthly payments in connection with an occupational disease. To make a
decision on the payment, it is necessary to check the information containing in a number of
documents. Therefore, before making a decision, the Branch requests the confirmation of some
information from the other agencies. The Ministry of Health (Source 1) is a supplier of the
1
The program Digital Economy of the Russian Federation approved by the Government of the Russian
Federation in its resolution No. 1632-r, July 28, 2017, Available at: http://ac.gov.ru/files/content/14091/1632-r-
pdf.pdf.
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Proceedings of the XXVI International Symposium on Nuclear Electronics & Computing (NEC’2017)
Becici, Budva, Montenegro, September 25 - 29, 2017
“information about the medical worker and his professional work activity”2. The Federal Medical
Biological Agency (FMBA, Source 2) provides the “information on the existence of a causal
relationship between developed diseases and the disability caused by the effects of radiation
exposure”. We request this data set from the Cross-agency Electronic Interaction System of St.
Petersburg3. In accordance with the requested data, the information is checked.
In the example, we show the solution for the task of integrating the service of the Federal
Register of Medical Workers (Source 1, MedStaff Web Service) and FMBA service (Source 2) with
the branch information system. We assume that the Branch has an information system that performs
all the necessary business processes of its activity (including checking information in the documents
provided by the Applicant).
In the classical version of integration – the architecture with a mediated schema [6] – (Option
1), in the information system of the Branch we implement a unique client of each web service
(hereinafter referred to as the client) to request and obtain the necessary data (Fig. 1). The client
contains the program code for calling the corresponding web service (WS), requesting and converting
the data from/to the data of the Branch. To simplify the schemas, the Branch's clients, as well as
MedStaff WS and FMBA WS, encapsulate all software layers, including references to the relational
DBMS. In this case, information systems have their own independent (and often contradictory) data
models, which become the basis for the formation of a mediated data storage schema.
IS of Federal Social Insurance Fund Federal Register of Medical Workers
SQL Query Client of SQL Query
SOAP Request MedStaff RDBMS
MedStaff
SOAP Response WS
WS Native Data
Native Data
Register objects Register
XSD Data Model
IS FSIF Data
RDBMS IS of FMBA
Model
FMBA Objects IS FMBA Data
XSD Model
Native Data
Client of SQL Query
SOAP Request FMBA
FMBA WS RDBMS
SQL Query SOAP Response WS
Native Data
Figure 1. Classical integration of data
Among the obvious disadvantages of this integration method, we point individual
development of the client for each web service, as well as the need to re-program the client code
every time, when the changes in web services occur due to the changes in the data model or a storage
schema.
Modern approaches to the integration of heterogeneous sources based on the construction of
an integrated data model [6] (Option 2), for example, NIEM [5], provide independent development
and maintenance of a unified data model (UMD) (Fig. 2). For the information exchange, it is enough
to “know” two models: UMD and the own model of the information system. UMD is a
common/reference model for the information sharing and exchange, but the data models of
information systems are conducted locally (Fig. 2). Thus, the IS data model can be created both with
and without UMD. This is especially important for the integration of legacy information systems and
helps to avoid a significant and costly upgrade.
2
http://ms-
info.rosminzdrav.ru/index.php?option=com_content&view=category&layout=blog&id=69&Itemid=101
WSDL: http://ms-info.rosminzdrav.ru/attachments/article/323/MedStaffWCF_WSDL_XSD.zip
3
https://smev.spb.ru/SMEVRegistry2/viewService.jsp?serviceId=233. WS passport:
https://smev.spb.ru/SMEVRegistry2/UploadServiceFile?fileId=10034&type=2
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Proceedings of the XXVI International Symposium on Nuclear Electronics & Computing (NEC’2017)
Becici, Budva, Montenegro, September 25 - 29, 2017
IS of Federal Social Insurance Fund Federal Register of Medical Workers
SQL Query Client of SQL Query
MedStaff RDBMS
SOAP Request
MedStaff WS WS
SOAP Response
Native Data Native Data
Register Data Model
IS FSIF Data Data Model objects Unified Data
RDBMS FMBA Objects XSD
Model XSD Model
IS of FMBA
IS FMBA Data Model
Native Data
SOAP Request
Client of SOAP Response FMBA WS
SQL Query FMBA WS SQL Query RDBMS
Native Data
Figure 2. Local use of a unified data model in the processing system
The option with UMD-based integration provides an unambiguous interpretation of domain
objects by all interaction participants and allows eliminating some drawbacks of the classical method
(Option 1). When developing the client and the web service itself we provide the compliance to
UMD but not to the data models of multiple systems. It is clear, the UMD change causes the changes
in the client code as well as in the web services, but changing the IS data models of the Sources while
keeping the UMD unchanged entails the modification only of the web services, but not the clients.
Applying semantic integration [6] (Option 3), we create an ontology-based model (domain
model) which describes the subject area. It is also a common/reference model (Fig. 3), but unlike
option 2, all the participants of the information exchange use it without the possibility to make local
changes in the IS data models (excluding internal extensions).
Federal Register of Medical Workers
IS of FSIF
SQL Query
SPARQL SPARQL/ RDBMS
MedStaff
WS SOAP Request
SOAP Response WS Native Data
adapter
RDF Data
Register Data Model
Semantic enrichment of Medstaff WS
WSDL
RDF Domain Data
Database IS of FMBA
Model
Semantic enrichment of FMBA WS WSDL
IS FMBA Data Model
RDF Data
SPARQL/ SQL Query
FMBA
WS SOAP Request RDBMS
WS
SPARQL adapter SOAP Response
Native Data
Figure 3. Use of domain model by all the information exchange participants
The advantage of this approach is that UMD changes do not cause multiple modifications in
the mediators (Option 1) or web service clients (Option 2), because the configuration of SPARQL
adapters goes automatically in compliance with the domain model. In addition, the application of the
domain model allows the use of semantically oriented tools (for example, ontologies) to control the
integrity and consistency of the interaction.
Digital Health ecosystem is an open system of systems [7] with a changing number of
interaction participants [8], which entails frequent changes in the data model. Therefore, the
application of the first method becomes extremely inefficient, and the use of UMD will lead to
constant improvements in the clients of web services. Thus, the advantages of semantic integration
for building the Digital Health ecosystem are very distinct.
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Proceedings of the XXVI International Symposium on Nuclear Electronics & Computing (NEC’2017)
Becici, Budva, Montenegro, September 25 - 29, 2017
3. Example of applying semantic integration methods
In practice, we confirmed the advantages discussed above by implementing the example of
semantic integration in healthcare within the project of Plekhanov Russian University of Economics
named the “Center of semantic integration”4.
At the stage of preparation, we uploaded various types of semantic assets (SA) to the
catalogue of SA, based on ADMS [12]. We described the data models of web services (input and
output data schema), which then we used in the developed example. We registered the models in the
SA catalogue and fixed their association with the information about the services (links to web sites,
passports, etc.). Each element of WS data model contains a description of the element, its type,
description and other attributes, including the link to relevant vocabularies registered in the SA
catalogue.
The developed domain model contains the following objects: “Person”, “Disease”, “Medical
institution” with the required attributes (Fig. 4). We linked created elements with the corresponding
elements of other SAs, for example, vCard, FOAF and other.
hbb=http://hbb.ru/schema# Disease Code
hbb:Code
hbb:FamilyName hbb:Person hbb:radioactive hbb:Disease
hbb:Name Name
Surname hbb:Company
hbb:MedicalInstitution hbb:OGRN Registration Number
Date of Birth
hbb:DateOfBirth
hbb:Name Name
Figure 4. Example of the domain data model
To meet the features of the implementation, we extended the basic domain model in
correspondence with WS data models by means of mapping and linking. As a result, the elements of
the domain model are associated with the data model elements of the web services chosen for the
example (Sources 1, 2) and other relevant schemas. Association of WS data model elements with the
elements of the domain model provides the same interpretation of data during the information
exchange5.
Application of the semantic approach to the organization of interaction and data storage in
the form of RDF objects (using the model “object” – “attribute” – “value”) provides the possibility of
sharing the information from different sources. At the same time, it helps to enrich the information
exchange with the additional opportunities for the data search using the links that are not explicitly
specified. For example, the classical integration method makes impossible to find the information
about medical facilities in which workers received a disease or disability from radiation (in Fig. 4 the
broken line indicates this link) without downloading all the data, because this link is not available in
the web service. Whereas a simple SPARQL query will allow to obtain this information without a
revision of the domain model.
The enrichment of WSDL schema with semantics can transfer WS to the category of a
semantic web service. This provides the possibility of inheriting the already existing service
infrastructure. We can also combine a set of semantic web services into a semantic integration bus, in
which the central part is the domain model, and the services themselves contain all the necessary
information for semantic integration and interpretation of data.
4. Conclusion
The semantic approach drastically reduces the need for constant updating of cross-system
interaction interfaces and its implementation for the information sharing in a variable heterogeneous
4
Centre of Semantic Integration, Portal: http://csi.semanticpro.org/catalog
5
Additional materials for the example: http://csi.semanticpro.org/library/article/172.ru.html
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Proceedings of the XXVI International Symposium on Nuclear Electronics & Computing (NEC’2017)
Becici, Budva, Montenegro, September 25 - 29, 2017
environment is important. Despite an open number of participants, changes in technologies and
software platforms, as well as in the conditions of information exchange, it provides the access to the
systems and services within the open connection of independent consumers. Semantic integration
extends the possibilities of obtaining information about the relationships between the elements that
are not explicitly specified.
The use of semantic approach to the integration provides significant advantages and allows
the formation of a semantic core, which will keep the knowledge and become the basis for the Digital
Health ecosystem [8].
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