Semantic Web Approach of Integrating Big Data- A Review

Ahmed, Jeelani; Ahmed, Muqeem

doi:10.26438/ijcse/v6i9.529532

Cited by 5 publications

(3 citation statements)

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“…Data integration is the process of making it possible for people to access, deliver, and utilize data from several sources and huge businesses while preserving its integrity and quality. Real-time updates to data saved in one source can also be mirrored in other sources thanks to this [15].…”

Section: Nosql Databasesmentioning

confidence: 99%

A Semantic NoSQL Application Program Interface for Big Data

ElDahshan¹,

Elsayed²,

Mancy³

et al. 2022

IJACSA

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Complexity, heterogeneity, schemaless-ness, data visualization, and extraction of consistent knowledge from Big Data are the biggest challenges in NoSQL databases. This paper presents a general semantic NoSQL Application Program Interface that integrates and converts NoSQL databases to semantic representation. The generated knowledge base is suitable for visualization and knowledge extraction from different Big Data sources. The authors use a case study of the COVID-19 pandemic prediction and other weather occurrences in various parts of the world to illustrate the suggested API. The Authors find a correlation between COVID-19 spread and deteriorating weather. According to the experimental findings, the API's performance is enough for heterogeneous Big Data.

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Section: Nosql Databasesmentioning

confidence: 99%

A Semantic NoSQL Application Program Interface for Big Data

ElDahshan¹,

Elsayed²,

Mancy³

et al. 2022

IJACSA

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“…The semantic web is used for integrating diverse web data to enable easy search, reuse, and linking of data. Semantic web technologies act as integrators of various web services, databases and other formats for the presentation of data using ontologies and data annotation (Ahmed and Ahmed, 2018). Semantic technologies are used for managing, querying and integrating sensor data (Compton et al, 2012).…”

Section: Semantic Web Technologiesmentioning

confidence: 99%

Wireless Body Area Network and Sensor Data Interoperability

Alatta¹

2021

Preprint

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The monitoring of maternal and child health, using wearable devices made with wireless sensor technologies, is expected to reduce maternal and child death rates. Wireless sensor technologies have been used in wireless sensor networks to enable the acquisition of data for monitoring machines, smart cities, transportation, asset tracking, and tracking of human activity. Applications based on wireless body area network (WBAN) have been used in healthcare for measuring and monitoring of patient health and activity through integration with wearable devices. Wireless sensors used in WBAN can be cost-effective, enable remote availability, and can be integrated with electronic health record (EHR) management systems. Interoperability of WBAN sensor data with other linked data has the potential to improve health for all, including maternal and child health through the improvement of data access, data quality and healthcare access. This paper presents a survey of the state-of-the-art techniques for managing WBAN sensor data interoperability. The findings in this study will provide reliable support to enable policymakers and health care providers to take action to enhance the use of e-health to improve maternal-child health and reduce the mortality rates of women and children.

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“…In the last few years, the semantic web was introduced by the World Wide Web Consortium (W3C) to enable a simpler method for searching, reusing, integrating, and sharing information [ 11 ]. Semantic techniques have demonstrated to be the most pertinent for comprehending and solving a lot of difficulties and challenges which face the healthcare big data community.…”

Section: Introductionmentioning

confidence: 99%

A Semantic-Based Approach for Managing Healthcare Big Data: A Survey

Hammad

Barhoush

Abed-alguni

2020

Journal of Healthcare Engineering

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Healthcare information systems can reduce the expenses of treatment, foresee episodes of pestilences, help stay away from preventable illnesses, and improve personal life satisfaction. As of late, considerable volumes of heterogeneous and differing medicinal services data are being produced from different sources covering clinic records of patients, lab results, and wearable devices, making it hard for conventional data processing to handle and manage this amount of data. Confronted with the difficulties and challenges facing the process of managing healthcare big data such as volume, velocity, and variety, healthcare information systems need to use new methods and techniques for managing and processing such data to extract useful information and knowledge. In the recent few years, a large number of organizations and companies have shown enthusiasm for using semantic web technologies with healthcare big data to convert data into knowledge and intelligence. In this paper, we review the state of the art on the semantic web for the healthcare industry. Based on our literature review, we will discuss how different techniques, standards, and points of view created by the semantic web community can participate in addressing the challenges related to healthcare big data.

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Semantic Web Approach of Integrating Big Data- A Review

Cited by 5 publications

References 0 publications

A Semantic NoSQL Application Program Interface for Big Data

A Semantic NoSQL Application Program Interface for Big Data

Wireless Body Area Network and Sensor Data Interoperability

A Semantic-Based Approach for Managing Healthcare Big Data: A Survey

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