Big Data Research and Application - A Systematic Literature Review

Petrova-Antonova, Dessislava, Ilieva, Sylvia, and Pavlova, Irena. "Big Data Research and Application - A Systematic Literature Review." Serdica Journal of Computing 11.2 (2017): 073-114. <http://eudml.org/doc/294978>.

@article{Petrova2017,
abstract = {In the recent years Big Data has become a research topic for both academia and industry. Given the data value for applications in different domains, as well as the business value of the data per se, there is an urgent need for solid end-to-end, data-driven and data-oriented solutions to guide strategic decisions. Such solutions should include a set of mechanisms for runtime adaptations across the complete data lifecycle of Big Data Value Chain. Thus, advanced data functions enabling data to be structured, cleaned, stored, aggregated, modelled, processed, and analyzed are needed. Considering the significant value of Big Data, this paper presents a systematic literature review. Its main goal is to provide a holistic view of Big Data challenges as a result of a thorough analysis of state-of-the-art research and applications. ACM Computing Classification System (1998): Y.1.0, Z.2.1.*This work was supported by the European Commission under grant agreement No 763566, by the National Science Fund, Bulgarian Ministry of Education and Science, within project No DN 02/11, and by the Science Fund of the St. Kliment Ohridski University of Sofa within project 80-10-192/24.04.2017.},
author = {Petrova-Antonova, Dessislava, Ilieva, Sylvia, Pavlova, Irena},
journal = {Serdica Journal of Computing},
keywords = {Big Data; Big Data Value Chain; State-of-the-Art},
language = {eng},
number = {2},
pages = {073-114},
publisher = {Institute of Mathematics and Informatics Bulgarian Academy of Sciences},
title = {Big Data Research and Application - A Systematic Literature Review},
url = {http://eudml.org/doc/294978},
volume = {11},
year = {2017},
}

TY - JOUR
AU - Petrova-Antonova, Dessislava
AU - Ilieva, Sylvia
AU - Pavlova, Irena
TI - Big Data Research and Application - A Systematic Literature Review
JO - Serdica Journal of Computing
PY - 2017
PB - Institute of Mathematics and Informatics Bulgarian Academy of Sciences
VL - 11
IS - 2
SP - 073
EP - 114
AB - In the recent years Big Data has become a research topic for both academia and industry. Given the data value for applications in different domains, as well as the business value of the data per se, there is an urgent need for solid end-to-end, data-driven and data-oriented solutions to guide strategic decisions. Such solutions should include a set of mechanisms for runtime adaptations across the complete data lifecycle of Big Data Value Chain. Thus, advanced data functions enabling data to be structured, cleaned, stored, aggregated, modelled, processed, and analyzed are needed. Considering the significant value of Big Data, this paper presents a systematic literature review. Its main goal is to provide a holistic view of Big Data challenges as a result of a thorough analysis of state-of-the-art research and applications. ACM Computing Classification System (1998): Y.1.0, Z.2.1.*This work was supported by the European Commission under grant agreement No 763566, by the National Science Fund, Bulgarian Ministry of Education and Science, within project No DN 02/11, and by the Science Fund of the St. Kliment Ohridski University of Sofa within project 80-10-192/24.04.2017.
LA - eng
KW - Big Data; Big Data Value Chain; State-of-the-Art
UR - http://eudml.org/doc/294978
ER -