The Concept of Pattern based Data Sharing in Big Data Environments

Hossen, Abid; Moniruzzaman, A B M; Hossain, Syed Akhter

doi:10.14257/ijdta.2015.8.4.02

Cited by 10 publications

(5 citation statements)

References 10 publications

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“…The value property of big data determines its usefulness to take actionable decisions after data analysis. However, big data is currently redefined with the addition of three new Vs: i) variety, ii) variability, and iii) veracity (Rehman & Batool, 2015;Gani, Siddiqa, Shamshirband, & Hanum, 2016). The variety property defines the multi-facet big data integrating with the different data types generated by various data sources.…”

Section: Big Data For Enterprisesmentioning

confidence: 99%

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Big data reduction framework for value creation in sustainable enterprises

Rehman

Chang

Batool

et al. 2016

International Journal of Information Management

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225

146

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Value creation is a major sustainability factor for enterprises, in addition to profit maximization and revenue generation. Modern enterprises collect big data from various inbound and outbound data sources. The inbound data sources handle data generated from the results of business operations, such as manufacturing, supply chain management, marketing, and human resource management, among others. Outbound data sources handle customer-generated data which are acquired directly or indirectly from customers, market analysis, surveys, product reviews, and transactional histories. However, cloud service utilization costs increase because of big data analytics and value creation activities for enterprises and customers. This article presents a novel concept of big data reduction at the customer end in which early data reduction operations are performed to achieve multiple objectives, such as a) lowering the service utilization cost, b) enhancing the trust between customers and enterprises, c) preserving privacy of customers, d) enabling secure data sharing, and e) delegating data sharing control to customers. We also propose a framework for early data reduction at customer end and present a business model for end-toend data reduction in enterprise applications. The article further presents a business model canvas and maps the future application areas with its nine components. Finally, the article discusses the technology adoption challenges for value creation through big data reduction in enterprise applications.

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Section: Big Data For Enterprisesmentioning

confidence: 99%

“…The objective of the proposed framework is to enable knowledge-driven data sharing in big data systems to replace raw data sharing (see Figure 2) (Rehman & Batool, 2015). Accordingly, we consider IoT-based big data systems as a case study in establishing the context of the proposed framework.…”

Section: Big Data Reduction Framework For Value Creation In Sustainabmentioning

confidence: 99%

Big data reduction framework for value creation in sustainable enterprises

Rehman

Chang

Batool

et al. 2016

International Journal of Information Management

Self Cite

225

146

View full text Add to dashboard Cite

show abstract

“…In addition to (1) the volume, Big Data is based on (2) the variety to present various data formats (structured, semi-structured or unstructured), (3) the velocity to provide timeliness requirements, (4) the value to give the ability to extract the meaning from the collected datasets, (5) the variability to provide inconsistency concept of the data, and (6) veracity to work on the trustworthiness of the data [18]. Figure 5 presents Big Data technologies for smart grid, in it different levels from data sources to visualization.…”

Section: Big Data Life Cyclementioning

confidence: 99%

Big Data management in smart grid: concepts, requirements and implementation

et al. 2017

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“…This includes, for example, the promotion of digital sector coupling, the development of digital services or the increase of energy efficiency (BMNT, 2019). Digital technologies such as cloud computing, digital platforms, and smart devices (Cao et al, 2016;Rehman & Batool, 2015) enable individuals to share their data with others (Huang et al, 2015). In this context, shared consumer data is of economic value to companies (Zhao & Xue, 2013).…”

Section: Introductionmentioning

confidence: 99%

Influencing Factors on Consumers’ Willingness to Share Energy Data on Online Energy Platforms

Maier

Pfeiffer²,

Hatzl³

et al. 2021

BMS

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Climate change requires an adaptation of the energy system towards an efficient use of renewable energies. For efficient control and optimization of the energy system, energy consumption and production data at household level play an essential role. Sharing platforms can enable the bundling and controlling of energy data from individual households. However, there is often a lack of acceptance among potential users to share their own data on such platforms. Therefore, this paper investigates the willingness of consumers to share their personal energy data. In particular, several factors that influence this willingness are examined. Decisive for the willingness are incentives for consumers in return for sharing their energy data. These can be offered in personal added value or collective added value. This paper shows that the factors perceived behavioral control, personal attitude and subjective norm have an influence on the willingness of private users to share energy data if a personal benefit or a collective benefit is provided. The age of users and their privacy concerns affect the willingness to share only in case personal value is added. These findings are valuable for the development and operation of online energy platforms.

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The Concept of Pattern based Data Sharing in Big Data Environments

Cited by 10 publications

References 10 publications

Big data reduction framework for value creation in sustainable enterprises

Big data reduction framework for value creation in sustainable enterprises

Big Data management in smart grid: concepts, requirements and implementation

Influencing Factors on Consumers’ Willingness to Share Energy Data on Online Energy Platforms

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