A knowledge-based platform for Big Data analytics based on publish/subscribe services and stream processing

Esposito, Christian; Ficco, Massimo; Palmieri, Francesco; Castiglione, Aniello

doi:10.1016/j.knosys.2014.05.003

Cited by 88 publications

(33 citation statements)

References 21 publications

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“…The rapid development of big data has created many challenges for KM. Big data can be considered as a knowledge asset, and thus the field of knowledge management gained new momentum with the introduction of big data analytics for knowledge creation [14]. So, we formulated the fifth research question:…”

Section: Rq4mentioning

confidence: 99%

Visualizing the Academic Discipline of Knowledge Management

et al. 2018

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Abstract:The aim of this paper was to evaluate the research status of knowledge management (KM) and identify the characteristics of KM in the literature. We selected and studied in detail 7628 original research articles from the Web of Science from 1974 to 2017. Although many studies have contributed to the evolution of the KM domain, our results showed that a comprehensive bibliometric and visualization investigation was required. The literature on KM has grown rapidly since the 1970s. The United States of America, as the original contributing country, has also internationally collaborated the most in this field of study. The National Cheng Kung University has made the highest number of contributions. The majority of authors contributed a small number of publications. Additionally, the most common category in KM research was management. The main publications for KM research include Journal of Knowledge Management, and Knowledge Management Research & Practice. A keywords analysis determined that "knowledge sharing", "innovation", "ontology", and "knowledge management" were consistent hotspots in knowledge management research. Through a document co-citation analysis, the intellectual structures of knowledge management were defined, and four emerging trends were identified that focus on new phenomenon, the practice of knowledge management, small and medium enterprises (SMEs) management based on knowledge perspective, innovation and performance, and big data-enabled KM. We also provide eight research questions for future studies. Our results will benefit academics, researchers, and research students who want to rapidly obtain an overview of knowledge management research. This study can also be a starting point for communication between academics and practitioners.

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Section: Rq4mentioning

confidence: 99%

Visualizing the Academic Discipline of Knowledge Management

et al. 2018

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“…In particular, the MapReduce paradigm is affected by several performance limitations, introducing high latency in data access and making it not suitable for interactive use. This makes the MapReduce paradigm unsuitable for event-based online Big Data processing architectures, and motivates the need of investigating other different paradigms and novel platforms for large-scale event stream-driven analytics solutions [152]. Also, iterative algorithms are not able to obtain a good performance as they need to launch a MapReduce job for each iteration notably increasing the computation time due to the overhead [153].…”

Section: Big Data Tools Based On Batch Analysismentioning

confidence: 99%

A general perspective of Big Data: applications, tools, challenges and trends

et al. 2015

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Big Data has become a very popular term. It refers to the enormous amount of structured, semi-structured and unstructured data that are exponentially generated by high-performance applications in many domains: biochemistry, genetics, molecular biology, physics, astronomy, business, to mention a few. Since the literature of Big Data has increased significantly in recent years, it becomes necessary to develop an overview of the state-of-the-art in Big Data. This paper aims to provide a comprehensive review of Big Data literature of the last 4 years, to identify the main challenges, areas of application, tools and emergent trends of Big Data. To meet this objective, we have analyzed and classified 457 papers concerning Big Data. This review gives relevant B Giner Alor-Hernández

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“…The solution is modular, decentralized and reusable (19) thus allows IoT devices to easily to attach over the service. We are motivated by the works in publish/subscribe systems in clouds and inter-clouds as in (1), (8), (22), (7), (10) and (15).The basic characteristic of the proposed service is the simplicity of use at any time requested by the user. Such reusable services are very important in a cloud computing because it allows developers to model complex systems.…”

Section: Motivationmentioning

confidence: 99%

Modular and generic IoT management on the cloud

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Future Generation Computer Systems

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Cloud computing and Internet of the things encompasses various physical devices that generate and exchange data with services promoting the integration between the physical world and computer-based systems. This work presents a novel future Internet cloud service for data collection from Internet of the things devices in an automatic, generalized and modular way. It includes a flexible API for managing devices, users and permissions by mapping data to users, publish and subscribe to context data as well as storage capabilities and data processing in the form of NoSQL big data. The service has been implemented in OpenStack platform and is easily deployable, reusable Preprint submitted to Future Generation Computer SystemsMay 21, 2016 and reconfigurable. The contributions of this work includes the on the fly data collection from devices that is stored in cloud scalable databases, the vendor agnostic Internet of things device connectivity (since it is designed to be flexible and to support device heterogeneity), and finally the modularity of the event based publish/subscribe service for context oriented data that could be easily utilized by third party services without worrying about how data are collected and stored and managed.

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A knowledge-based platform for Big Data analytics based on publish/subscribe services and stream processing

Cited by 88 publications

References 21 publications

Visualizing the Academic Discipline of Knowledge Management

Visualizing the Academic Discipline of Knowledge Management

A general perspective of Big Data: applications, tools, challenges and trends

Modular and generic IoT management on the cloud

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