Standard

Big Data Structuring : The Role of Visual Models and Ontologies. / Gavrilova, T.; Gladkova, M.

Big Data Structuring: The Role of Visual Models and Ontologies. 2014. p. 336-343.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Gavrilova, T & Gladkova, M 2014, Big Data Structuring: The Role of Visual Models and Ontologies. in Big Data Structuring: The Role of Visual Models and Ontologies. pp. 336-343. https://doi.org/10.1016/j.procs.2014.05.276

APA

Gavrilova, T., & Gladkova, M. (2014). Big Data Structuring: The Role of Visual Models and Ontologies. In Big Data Structuring: The Role of Visual Models and Ontologies (pp. 336-343) https://doi.org/10.1016/j.procs.2014.05.276

Vancouver

Gavrilova T, Gladkova M. Big Data Structuring: The Role of Visual Models and Ontologies. In Big Data Structuring: The Role of Visual Models and Ontologies. 2014. p. 336-343 https://doi.org/10.1016/j.procs.2014.05.276

Author

Gavrilova, T. ; Gladkova, M. / Big Data Structuring : The Role of Visual Models and Ontologies. Big Data Structuring: The Role of Visual Models and Ontologies. 2014. pp. 336-343

BibTeX

@inproceedings{b1c1fdd98fa34dcc819b852f0dc357df,
title = "Big Data Structuring: The Role of Visual Models and Ontologies",
abstract = "This paper presents a novel approach aimed at analyzing the leading role of the visual structuring strategies of Big Data based on the principles of ontological engineering and cognitive psychology. It is targeted at the development of methodology scaffolding the process of data structuring for the better vision and understanding of huge amounts of business information. The structuring procedure is the kernel of any data model design and development. Ontologies that describe the main concepts of exemplary domains are used both for deeper comprehension and better information sharing. The main stress is put on using visual techniques of mind-mapping that serve as a powerful mind tool. Cognitive bias and some results of Gestalt psychology are highlighted. The ideas of balance, clarity, and beauty are applied to the ontology design and refinement procedures.",
keywords = "WEB OF SCIENCE, SCOPUS, РИНЦ",
author = "T. Gavrilova and M. Gladkova",
note = "Gavrilova, T. Big Data Structuring: The Role of Visual Models and Ontologies / T. Gavrilova, M. Gladkova // 2nd International Conference on Information Technology and Quantitative Management, ITQM 2014. - 2014. - P. 336-343. ",
year = "2014",
doi = "10.1016/j.procs.2014.05.276",
language = "English",
isbn = "ISSN 1877-0509",
pages = "336--343",
booktitle = "Big Data Structuring",

}

RIS

TY - GEN

T1 - Big Data Structuring

T2 - The Role of Visual Models and Ontologies

AU - Gavrilova, T.

AU - Gladkova, M.

N1 - Gavrilova, T. Big Data Structuring: The Role of Visual Models and Ontologies / T. Gavrilova, M. Gladkova // 2nd International Conference on Information Technology and Quantitative Management, ITQM 2014. - 2014. - P. 336-343.

PY - 2014

Y1 - 2014

N2 - This paper presents a novel approach aimed at analyzing the leading role of the visual structuring strategies of Big Data based on the principles of ontological engineering and cognitive psychology. It is targeted at the development of methodology scaffolding the process of data structuring for the better vision and understanding of huge amounts of business information. The structuring procedure is the kernel of any data model design and development. Ontologies that describe the main concepts of exemplary domains are used both for deeper comprehension and better information sharing. The main stress is put on using visual techniques of mind-mapping that serve as a powerful mind tool. Cognitive bias and some results of Gestalt psychology are highlighted. The ideas of balance, clarity, and beauty are applied to the ontology design and refinement procedures.

AB - This paper presents a novel approach aimed at analyzing the leading role of the visual structuring strategies of Big Data based on the principles of ontological engineering and cognitive psychology. It is targeted at the development of methodology scaffolding the process of data structuring for the better vision and understanding of huge amounts of business information. The structuring procedure is the kernel of any data model design and development. Ontologies that describe the main concepts of exemplary domains are used both for deeper comprehension and better information sharing. The main stress is put on using visual techniques of mind-mapping that serve as a powerful mind tool. Cognitive bias and some results of Gestalt psychology are highlighted. The ideas of balance, clarity, and beauty are applied to the ontology design and refinement procedures.

KW - WEB OF SCIENCE

KW - SCOPUS

KW - РИНЦ

U2 - 10.1016/j.procs.2014.05.276

DO - 10.1016/j.procs.2014.05.276

M3 - Conference contribution

SN - ISSN 1877-0509

SP - 336

EP - 343

BT - Big Data Structuring

ER -

ID: 7029341