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H-Kaas: a Knowledge-As-A-Service Architecture for E-Health

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H-Kaas: a Knowledge-As-A-Service Architecture for E-Health Brazilian Journal of Biological Sciences, 2018, v. 5, No. 9, p. 3-12. ISSN 2358-2731 https://doi.org/10.21472/bjbs.050901 H-KaaS: A Knowledge-as-a-Service architecture for E-health Renan G. Barreto¹, Lucas Aversari¹, Cecília Neta A. P. Gomes² and Natasha C. Q. Lino¹ ¹Universidade Federal da Paraíba. Centro de Ciências Exatas e da Natureza. Programa de Pós-Graduação em Informática. Campus I. -PB. Brazil. (CEP 58051-900). ²Programa de Pós-Graduação em Modelos de Decisão e Saúde.João CentroPessoa de Ciências Exatas e da Natureza. Universidade Federal da Paraíba. Campus I. -PB. Brazil. (CEP 58051-900). João Pessoa Abstract. Due to the need to improve access to knowledge and the establishment of means for sharing and organizing data in Received the health area, this research proposes an architecture based on January 8, 2018 the paradigm of Knowledge-as-a-Service (KaaS). This can be used in the medical field and can offer centralized access to Accepted April 30, 2018 ontologies and other means of knowledge representation. In this paper, a detailed description of each part of the architecture and Released its implementation was made, highlighting its main features and April 30, 2018 interfaces. In addition, a communication protocol was specified and used between the knowledge consumer and the knowledge Full Text Article service provider. Thus, the development of this research contributed to the creation of a new architecture, called H-KaaS, which established itself as a platform capable of managing multiple data sources and knowledge models, centralizing access through an easily adaptable API. Keywords: Knowledge-as-a-service architecture; Health informatics; Knowledge representation. 0000-0002-0919-6957 Renan G. Barreto 0000-0003-4152-5842 Lucas Aversari 0000-0002-8131-0566 . P. Gomes 0000Cecı́lia-0003 -Neta2395 -4846A Natasha C. Q. Lino ISSN 2358-2731/BJBS-2018-0001/5/9/1/3 Braz. J. Biol. Sci. http://revista.rebibio.net 4 Barreto et al. Introduction based on the Knowledge-as-a-Service paradigm in the health area is modeled; a With the advance of processing communication API that will be used to power and speed of data collection on transmit knowledge between the the internet, many organizations focus knowledge provider and the consumer on the development of tools, modeling applications is specified; and an existing techniques and the creation of structures prototype in the nephrology domain is dedicated to knowledge sharing. adapted to an implementation of the Knowledge representation, a subarea of proposed architecture in order to allow Artificial Intelligence, aims to find ways its execution and to validate our to automatically represent, store and approach. manipulate knowledge using reasoning algorithms (Brachman and Levesque, Background 2004). For this reason, the amount of Health informatics data collected in the health domain According to Hoyt et al. (2008), increases periodically, resulting in the Health Informatics can be defined as the emergence of diagnostic methods, field of science that deals with formal chemical principles, and advances in resources, equipment, and methods to molecular biology and genetics, among optimize storage, reading and other medical advances (Wechsler et al., management of medical information in 2003). problem-solving and decision making. Knowledge management and Thus, Health Informatics aims to sharing is a promising area, but it is still improve the quality of health services, inefficient in the field of health reducing costs and allowing the exchange (Sabbatini, 1998). The knowledge of medical information (Hoyt et al., generated through the experiences of the 2008). professionals of the area is not usually passed on satisfactorily, thus retained in Nephrology and chronic kidney their own minds (Silva et al., 2005). disease In this context, the Knowledge- Nephrology is an area of as-a-Service (KaaS) paradigm aims to medicine that has as its objective the provide centralized knowledge that is diagnosis and clinical treatment of normally extracted from various data diseases of the urinary system, mainly sources and can be maintained by related to the kidney (SBN, 2016). different organizations. In it, a Chronic Kidney Disease (CKD) is knowledge server responds to requests defined as damage to the renal made by one or more knowledge parenchyma (with normal renal consumers (Xu and Zhang, 2005). function) and/or renal functional The aim of this work is to impairment present for a period of three propose an architecture based on the months or more. In its last stage, the paradigm of Knowledge-as-a-Service, in kidneys are no longer able to maintain order to create a common knowledge the normality of the patient’s internal base that can be used in the medical field environment. Thus, early diagnosis and or any other health area, and to facilitate disease prevention have become the diagnosis of patients, besides the increasingly important in order to take possibility of centrally providing access preventive measures that may delay or to ontologies and other means of halt the progression of CKD (Bastos and representing and processing knowledge. Kirsztajn, 2011). In this article, the following contributions are made: an architecture Braz. J. Biol. Sci., 2018, v. 5, No. 9, p. 3-12. H-KaaS 5 that competes with traditional business Knowledge representation, models (Benlian et al., 2012). ontologies and reasoning From the users’ point of view, the Knowledge Representation is a use of the SaaS architecture presents subarea of Artificial Intelligence (AI) that numerous advantages, such as: cost is concerned with the way that reduction, elasticity, automatic updates knowledge can be represented and easy implementation. For software symbolically and manipulated developer companies, this architecture automatically by reasoning algorithms offers a new way of selling functionality (Brachman and Levesque, 2004). Given a to their customers and competes with structure of knowledge representation traditional business models (Benlian et and a process of reasoning, it is possible al., 2012). to draw conclusions from previously In the context of knowledge modeled knowledge. These conclusions sharing and distribution, the Knowledge- can be used to assist in decision making as-a-Service (KaaS) paradigm aims to (Ladeira, 1997). centrally provide knowledge that is The term ontology, when used in normally extracted from various data the area of computer science, in the sources and can be maintained by context of knowledge representation different organizations. In it, a systems, refers to a general structure of knowledge server responds to requests concepts represented by a logical made by one or more knowledge vocabulary (Russell et al., 1995). To infer consumers (Xu and Zhang, 2005). in ontologies, we need an inference According to Xu and Zhang mechanism called reasoning algorithms. (2005), in an implementation of the KaaS These algorithms allow the comparison architecture, we can find three main of the syntax, possibly normalized components: Data Owners, which are are structure, and concepts expressed in the responsible for collecting data from their ontology (Baader, 2003). daily transactions and for filtering and protecting the collected information; Service Oriented Architectures Knowledge Service Provider, which aims Service-oriented architectures to centralize and provide knowledge (SOA) arose from the need for business through its knowledge server, where integration and automation over the data is extracted using an extractor internet (Papazoglou, 2003). In SOA, algorithm; and Knowledge Consumers, resources are packaged as well-defined which are applications that use the “services” that produce a standardized provided knowledge in their decision- output independently of the state or making process, communicating with the context of other parts of the application server by using a previously established (Fremantle et al., 2002). protocol. The Software-as-a-Service (SaaS) paradigm describes applications and Related work software delivered as a service over the internet. This architecture has already In order to understand and become an important model for selling compare similar researches, this section and delivering software in various presents and analyses several proposals industry sectors, providing several of architectures and frameworks applied benefits to both service providers and to different domains. their users (Armbrust et al., 2010), such It was proposed by Grolinger et as cost reduction, elasticity, automatic al. (2013) the Disaster-CDM, a KaaS updates, easy implementation, and a new framework, aiming to be able to store a way of selling functionality to customers large amount of disaster-related data Braz. J. Biol. Sci., 2018, v. 5, No. 9, p. 3-12. 6 Barreto et al. from several sources, facilitating its Thus, when analyzing the related search and indexing in addition to work, we can see that service-based providing support and interoperability architectures can help in decision tools. Disaster-CDM has as its main form support in several domains. We can also of data storage, the use of Relational see that most architectures use a textual Databases (RDB) and NoSQL databases. format for data serialization and It communicates with consumer communication with consumers. On the applications in three ways: ontologies, other hand, we can see that the sources APIs, and services. These three forms of of knowledge vary according to the data access allow Disaster-CDM to domain and availability of data holding
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