Feature Driven Survey of Big Data Systems

Salma, Cigdem Avci; Tekinerdoğan, Bedir; Athanasiadis, Ioannis N.

doi:10.5220/0005877503480355

Cited by 6 publications

(9 citation statements)

References 9 publications

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“…In this context, the term Big Data usually refers to data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time [1,2,12,14,16]. The extraction of useful information out of the big data is done using data analytics.…”

Section: Introductionmentioning

confidence: 99%

Exploration of Data Analytics for Ground Segment in Space Systems

Tekinerdoğan

Acar

Cabıoğlu

et al. 2020

Lecture Notes in Business Information Processing

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Article 25fa states that the author of a short scientific work funded either wholly or partially by Dutch public funds is entitled to make that work publicly available for no consideration following a reasonable period of time after the work was first published, provided that clear reference is made to the source of the first publication of the work.This publication is distributed under The Association of Universities in the Netherlands (VSNU) 'Article 25fa implementation' project. In this project research outputs of researchers employed by Dutch Universities that comply with the legal requirements of Article 25fa of the Dutch Copyright Act are distributed online and free of cost or other barriers in institutional repositories. Research outputs are distributed six months after their first online publication in the original published version and with proper attribution to the source of the original publication.

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Section: Introductionmentioning

confidence: 99%

Exploration of Data Analytics for Ground Segment in Space Systems

Tekinerdoğan

Acar

Cabıoğlu

et al. 2020

Lecture Notes in Business Information Processing

Self Cite

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“…We will develop reference architectures for e-government systems and Big Data systems, and define the approach deriving concrete e-government architecture. [48]. In this chapter, we adopt the functional architecture as described in [47] and as shown in…”

Section: Reference Architecturementioning

confidence: 99%

“…The variability model for big data systems is represented as a feature diagram [41] and is shown in Figure 3-4. This has been adopted from our earlier work on a feature-based analysis of big data systems [48]. The feature diagram includes a root node representing the domain or system that includes features representing the essential characteristics or externally visible properties of the system.…”

Section: Variability Model For Big Data Systemsmentioning

confidence: 99%

“…In our recent work we have provided a feature driven survey of big data systems [48]. To this end, we proposed a domain engineering approach in which a family feature model, a reference architecture and the corresponding design rules are identified.…”

Section: Related Workmentioning

confidence: 99%

“…Finally, the design rules define the reusable design heuristics for designing an application architecture based on the selection of features of the family feature model and the reference architecture. We have illustrated our approach for deriving the big data architectures of different well-known big data systems [48].…”

Section: Related Workmentioning

confidence: 99%

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Model-driven software architecture conformance analysis

Uzun¹

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The software architecture of systems contains vital information for both functional and nonfunctional requirements of system stakeholders. Software systems are designed and implemented with respect to their architectures in mind. Hence, architecture conformance analysis is important to ensure that the implemented system has not deviated from the intended architecture and thus the requirements.Software architectures can be used when guiding software development, communicating between stakeholders, deciding on organizational structures and analysing software systems. Therefore, deviating from intended software architecture can create both organizational and system-wise flaws. Domain Driven AnalysisIn order to answer RQ3 in chapter 5, we adopted a domain-driven analysis methodology. A well-known process for analysing and modelling the current state of the art of a particular domain is domain analysis. Domain analysis is the process of identifying and capturing domain knowledge about the problem domain with the purpose of making it reusable when creating new systems [41][46][53][84]. The aforementioned domain refers to "an area of knowledge or activity characterized by a set of concepts and terminology understood by practitioners in that area". Like many application domains Big Data has become a very important driver for innovation and growth for e-government which aims to automate the public services to citizens. In general, e-government systems are often characterized as big data systems in which data storage and processing is one of the business-critical concerns. However, different features are required for different e-government systems, and likewise the corresponding big data architectures will need to be different as well. In this chapter, we present a systematic approach for the design of various big data architectures within the e-government domain. In this context, we adopt a big data reference architecture with a variability model for big data systems and e-government systems. We discuss the design decisions, the experiences and the lessons learned for deriving application architectures for different e-government systems.

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