Top

Computing

Published in:

05-06-2020 | Editorial

Software-driven big data analytics

Guest editors’ introduction

Authors: Rajiv Ranjan, Zheng Li, Massimo Villari, Yan Liu, Dimitrios Georgeakopoulos

Published in: Computing | Issue 6/2020

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Data analytics is the crucial step to reveal essential values of datasets and complete the value chain of big data. In practice, both the hardware infrastructure and the software stack play a fundamental role in big data analytics (BDA). Unfortunately, it is evident that a disproportionately larger amount of effort is being invested in the hardware infrastructure development over the software stack development. Given our concern about a software crisis brewing in the big data ecosystem, we argue that it is time to further strengthen and expand the role of software in BDA implementations. This special issue is then aimed to create a common ground and a reference point for both researchers and practitioners from multiple disciplines to discuss the rigor, relevance, experience and challenges of software-driven BDA as an emerging domain. We also expect to use this special issue to attract more attention and efforts to tighten communication and collaboration between the software engineering community and the data science community.

previous article Fusing attack detection and severity probabilities: a method for computing minimum-risk war decisions

next article Optimizing the confidence bound of count-min sketches to estimate the streaming big data query results more precisely

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

https://www.microsoft.com/en-us/research/project/lightlda/.

https://www.microsoft.com/en-us/research/project/lightgbm/.

https://ai.googleblog.com/2019/04/morphnet-towards-faster-and-smaller.html.

Bosch J (2017) Speed, data, and ecosystems: excelling in a software-driven world. Chapman & Hall/CRC Innovations in Software Engineering and Software Development Series. CRC Press, Danvers, MACrossRef

Branstetter LG, Drev M, Kwon N (2018) Get with the program: software-driven innovation in traditional manufacturing. Manage Sci 65(2):541–558CrossRef

Calero C, Piattini M (2015) Green in software engineering. Springer, ChamCrossRef

Chasty C (2013) Forget the smart city... start with the smart workplace. https://www.wired.com/insights/2013/11/forget-the-smart-city-start-with-the-smart-workplace/. Accessed 24 May 2020

Chen L, Zhang N, Sun HM, Chang CC, Yu S, Choo KKR (2020) Secure search for encrypted personal health records from big data NoSQL databases in cloud. Computing 102(6): https://doi.org/10.1007/s00607-019-00762-z

Chen M, Mao S, Liu Y (2014) Big data: a survey. Mob Netw Appl 19(2):171–209CrossRef

Cook DJ, Das SK (2007) How smart are our environments? An updated look at the state of the art. Pervasive Mob Comput 3(2):53–73CrossRef

Dickinson R (2015) Using software for sustainability. https://en.muddyboots.com/news/view/using-software-for-sustainability. Accessed 24 May 2020

Ebert C (2018) 50 years of software engineering: progress and perils. IEEE Softw 35(5):94–101CrossRef

10.

Ebert C, Counsell S (2017) Toward software technology 2050. IEEE Softw 34(4):82–88CrossRef

11.

Fiore S, D’Anca A, Elia D, Palazzo C, Williams D, Foster I, Aloisio G (2014) Ophidia: a full software stack for scientific data analytics. In: Proceedings of the 12th international conference on high performance computing & simulation (HPCS 2014), IEEE Press, Bologna, Italy, pp 343–350

12.

Gordon WJ, Stern AD (2019) Challenges and opportunities in software-driven medical devices. Nat Biomed Eng 3:493–497CrossRef

13.

Guo R, Xue E, Zhang F, Zhao G, Qu G (2020) Optimizing the confidence bound of count-min sketches to estimate the streaming big data query results more precisely. Computing 102(6). https://doi.org/10.1007/s00607-018-00695-z

14.

Gupta D, Ahlawat AK, Sharma A, Rodrigues JJPC (2020) Feature selection and evaluation for software usability model using modified moth-flame optimization. 102(6). https://doi.org/10.1007/s00607-020-00809-6

15.

Jacobs A (2009) The pathologies of big data. Commun ACM 52(8):36–44CrossRef

16.

Kambatla K, Kollias G, Kumar V, Grama A (2014) Trends in big data analytics. J Parallel Distrib Comput 74(7):2561–2573CrossRef

17.

Kaur N, Sood SK, Verma P (2020) Cloud resource management using 3Vs of Internet of Big data streams. Computing 102(6). https://doi.org/10.1007/s00607-019-00732-5

18.

Li CS, Brech BL, Crowder S, Dias DM, Franke H, Hogstrom M, Lindquist D, Pacifici G, Pappe S, Rajaraman B, Rao J, Ratnaparkhi RP, Smith RA, Williams MD (2014) Software defined environments: an introduction. IBM J Res Dev 58(2/3):1–11CrossRef

19.

Li Z, Seco D, Rodríguez AES (2019) Microservice-oriented platform for internet of big data analytics: a proof of concept. Sensors 19(5), article no. 1134

20.

Liu T (2019) Liu Tieyan talks about machine learning: there are too many easy followers, we need to reflect. https://www.msra.cn/zh-cn/news/features/tie-yan-liu-machine-learning. Accessed 24 May 2020

21.

Madhavji NH, Miranskyy A, Kontogiannis K (2015) Big picture of big data software engineering: with example research challenges. In: Proceedings of the 1st international workshop on big data software engineering (BIGDSE 2015), IEEE Press, Florence, Italy, pp 11–14

22.

Al-Jaroodi J, Hollein B, Mohamed N (2017) Applying software engineering processes for big data analytics applications development. In: Proceedings of the IEEE 7th annual computing and communication workshop and conference (CCWC 2017), IEEE Press, Las Vegas, NV, USA, pp 1–7

23.

Penzenstadler B, Duboc L, Venters CC, Betz S, Seyff N, Wnuk K, Chitchyan R, Easterbrook SM, Becker C (2018) Software engineering for sustainability: find the leverage points!. IEEE Softw 35(4):22–33CrossRef

24.

Rabhi F, Bandara M, Namvar A, Demirors O (2018) Big data analytics has little to do with analytics. In: Beheshti A, Hashmi M, Dong H, Zhang WE (eds) ASSRI 2015, ASSRI 2017: service research and innovation. Lecture Notes in Business Information Processing, vol 234. Springer, Cham, pp 3–17

25.

Roberts RD (2016) Why software really will eat the world—and whether we should worry. Indep Rev 20(3):365–368

26.

Sachs R (2016) The mind as computer metaphor: Benson and the mistaken application of mental steps to software (part 3). https://www.bilskiblog.com/2016/04/the-mind-as-computer-metaphor-benson-and-the-mistaken-application-of-mental-steps-to-software-part-3/. Accessed 24 May 2020

27.

Salit ML, Parsons ML (1985) Software-driven instrumentation: the new wave. Anal Chem 57(6):715A–729A

28.

Spinellis D (2017) Future trends and research priorities in the area of software technologies. A report prepared for EU DG Communications Networks, Content and Technology PO 30-CE-0751856/00-91, European Commission, available online: https://ec.europa.eu/digital-single-market/en/news/future-trends-and-research-priorities-area-software-technologies. Accessed 24 May 2020

29.

Stewart M (2019) The future of computation for machine learning and data science. https://towardsdatascience.com/the-future-of-computation-for-machine-learning-and-data-science-fad7062bc27d. Accessed 24 May 2020

30.

Wang X (2019) Why the rise of software startup research: an insider’s view. In: Hyrynsalmi S, Suoranta M, Nguyen-Duc A, Tyrväinen P, Abrahamsson P (eds) ICSOB 2019: software business. Lecture Notes in Business Information Processing, vol 370. Springer, Cham, pp 11–18

31.

Xu D, Ma Y, Yan J, Liu P, Chen L (2020) Spatial-feature data cube for spatiotemporal remote sensing data processing and analysis. Computing 102(6). https://doi.org/10.1007/s00607-018-0681-y

32.

Yang CT, Wan TY (2020) Implementation of an energy saving cloud infrastructure with virtual machine power usage monitoring and live migration on OpenStack. Computing 102(6). https://doi.org/10.1007/s00607-020-00808-7

33.

Yuan J, Gao F, Ho Q, Dai W, Wei J, Zheng X, Xing EP, Liu TY, Ma WY (2015) LightLDA: Big topic models on modest computer clusters. In: Proceedings of the 24th international conference on world wide web (WWW 2015), International World Wide Web Conferences Steering Committee, Florence, Italy, pp 1351–1361

34.

Zhao Q, Zhang B, Feng W, Du Z, Zhang H, Sun D (2020) Long-term real time object tracking based on multi-scale local correlation filtering and global re-detection. Computing 102(6). https://doi.org/10.1007/s00607-020-00807-8#citeas

35.

Zhu X, Song B, Ni Y, Ren Y, Li R (2016) Software defined anything-from software-defined hardware to software defined anything. In: Business trends in the digital era. Springer, Cham, pp 83–103

Title: Software-driven big data analytics
Guest editors’ introduction
Authors: Rajiv Ranjan
Zheng Li
Massimo Villari
Yan Liu
Dimitrios Georgeakopoulos
Publication date: 05-06-2020
Publisher: Springer Vienna
Published in: Computing / Issue 6/2020
Print ISSN: 0010-485X
Electronic ISSN: 1436-5057
DOI: https://doi.org/10.1007/s00607-020-00822-9

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Other articles of this Issue 6/2020

Secure search for encrypted personal health records from big data NoSQL databases in cloud

Fusing attack detection and severity probabilities: a method for computing minimum-risk war decisions

Long-term real time object tracking based on multi-scale local correlation filtering and global re-detection

Cloud resource management using 3Vs of Internet of Big data streams

Optimizing the confidence bound of count-min sketches to estimate the streaming big data query results more precisely

Enabling distributed intelligence for the Internet of Things with IOTA and mobile agents

Premium Partner