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A Review on the Development of Big Data Analytics and Effective Data Visualization Techniques in the Context of Massive and Multidimensional Data

J. Jabanjalin Hilda, C. Srimathi, Bhulakshmi Bonthu
2016 Indian Journal of Science and Technology  
This paper focuses on the general background of data visualization and visualization techniques.  ...  Findings: The major difficultly in big data visualization is to preserve any of the original dimensional information.  ...  The article by 21, 22 presents the results of using the parallel coordinate representation for high-dimensional data analysis. Along these lines, a high number of dimensions can be visualized.  ... 
doi:10.17485/ijst/2016/v9i27/88692 fatcat:37fdoyhz7fh67fb6jtsol2e4gi

Data visualization of crime data using immersive virtual reality

Reehl Aishwarya, Sharma Sharad
2022 IS&T International Symposium on Electronic Imaging Science and Technology  
This paper focuses on VR visualization tool design, development, and usability assessment. A pilot user study was conducted for the VR visualization tool based on the system usability scale.  ...  This paper demonstrates the data visualization tool to visualize Baltimore crime data in immersive environment and non-immersive environment.  ...  Sri Teja Bodempudi for his help in building the visualization tool.  ... 
doi:10.2352/ei.2022.34.12.ervr-187 fatcat:5vzdeqgwtneanj4jx4efuyehhq

Rich Data: Risks, Issues, Controversies & Hype

Osmar R. Zaïane
2015 Symposium on Information Management and Big Data  
A large number of enterprises believe big data analytics will redefine the competitive landscape of their industries within the next few years. Adoption is now perceived as a matter of survival.  ...  We will try to shed some light on the current state of rich data.  ...  Visualization, the visual reporting of discoveries from data, is not a real science but an art; the art of conveying patterns from a high dimensional space in 2D representation, possibly interactively,  ... 
dblp:conf/simbig/Zaiane15 fatcat:bblkituwjzbyfjpkpckvr6k5km

Deep Learning for Big Data Analytics [chapter]

Rajendra Akerkar Priti Srinivas Sajja
2019 Zenodo  
Traditional approaches like artificial neural networks, in spite of their intelligent support such as learning from large amount of data, are not useful for big data analytics for many reasons.  ...  The chapter discusses the difficulties while analyzing big data and introduces deep learning as a solution. This chapter discusses various deep learning techniques and models for big data analytics.  ...  Section 2 highlights big data analytics by discussing large scale optimization, high dimensional data handling, and handling dynamic data.  ... 
doi:10.5281/zenodo.5106011 fatcat:vbxkbmzysvh45cwkbii5bck7wu

Managing Data for Visual Analytics: Opportunities and Challenges

Jean-Daniel Fekete, Cláudio T. Silva
2012 IEEE Data Engineering Bulletin  
A common feature shared by all the visual analytics applications developed so far is the reliance on ad-hoc and custom-built mechanisms to manage data: they re-implement their own in-memory databases to  ...  The domain of Visual Analytics has emerged with a charter to support interactive exploration and analysis of large volumes of (often dynamic) data.  ...  These efforts are generating ultra-scale data sets at very high spatial resolution.  ... 
dblp:journals/debu/FeketeS12 fatcat:zet6g4j5cfewnhgedsnjennluq

Editorial to the Special Issue on Demographic Data Visualization: Getting the point across – Reaching the potential of demographic data visualization

Tim Riffe, Nikola Sander, Sebastian Kluesener
2021 Demographic Research  
OBJECTIVE We discuss what makes a good data visualization and why it is worthwhile to strive for state-of-the-art visualization.  ...  We highlight the distinction between exploratory and explanatory graphics, and relate the seven papers that comprise the Demographic Research special collection on data visualization to the broader endeavor  ...  In addition, he offers some guidelines for elegant and clear graphics, with suggestions to aim for high "data density" and a high "data-ink ratio."  ... 
doi:10.4054/demres.2021.44.36 fatcat:homzgxthszdhrfuqp35gtn7zsa

Big data collection and analysis for manufacturing organisations

Erkki Jantunen, Jaime Campos, David Baglee, Pankaj Sharma
2017 Big Data & Information Analytics  
The paper examines the possible data inputs from machines, people and organizations that can be analysed for maintenance.  ...  However, an advent of new generation big data analytical tools has started to provide large scale benefits for the organizations.  ...  The authors would like to extend their gratitude to FIMECC Ltd (Finnish Metals and Engineering Competence Cluster) for project promotion  ... 
doi:10.3934/bdia.2017002 fatcat:qhrquxs7s5eihdn7evm7dbbiui

Intelligent Data Analysis in the EMERCOM Information System

Sharafutdinova Elena, Avdeenko Tatiana, Maxim Bakaev
2017 Journal of Physics, Conference Series  
The paper describes an information system development project for the Russian Ministry of Emergency Situations (MES, whose international operations body is known as EMERCOM), which was attended by the  ...  In particular, some operational OLAP reports and an example of multi-dimensional information space based on OLAP Data Warehouse are presented.  ...  Acknowledgments This work was supported by Russian Foundation for Basic Research (RFBR) according to the research project No. 16-37-60060 mol_a_dk.  ... 
doi:10.1088/1742-6596/803/1/012142 fatcat:i5iws2auuvgjdnm3ykg76cjo5u

Enabling Longitudinal Exploratory Analysis of Clinical COVID Data [article]

David Borland, Irena Brain, Karamarie Fecho, Emily Pfaff, Hao Xu, James Champion, Chris Bizon, David Gotz
2021 arXiv   pre-print
sequence visual analytics technologies to a longitudinal clinical data from a cohort of 998 patients with high rates of COVID-19 infection.  ...  This paper describes the initial steps toward this goal, including: (1) the data transformation and processing work required to prepare the data for visual analysis, (2) initial findings and observations  ...  Reflecting the need for rapid progress, the work reported in this paper leverages Cadence [30] , an existing visual analytics platform.  ... 
arXiv:2108.11476v1 fatcat:bjgqx3h74nawfmizefprm4x52a

Big Data architecture for intelligent maintenance: a focus on query processing and machine learning algorithms

Claude Lehmann, Lilach Goren Huber, Thomas Horisberger, Georg Scheiba, Ana Claudia Sima, Kurt Stockinger
2020 Journal of Big Data  
In particular, we will discuss various physical design choices for optimizing high-dimensional queries, such as partitioning and Z-ordering, that serve as the basis for health analytics.  ...  In this paper we present the design of an end-to-end Big Data architecture that enables intelligent maintenance in a real-world industrial setting.  ...  all of the necessary building blocks, starting from data acquisition, onto streaming and data warehousing, through data processing, analytics and visualization of condition monitoring data up to smart  ... 
doi:10.1186/s40537-020-00340-7 fatcat:223homnwufchhkh5pivbenrz3u

Data Driven Discovery in Astrophysics [article]

G. Longo, M. Brescia, S.G. Djorgovski, S. Cavuoti, C. Donalek
2014 arXiv   pre-print
Telescopes and observatories from both ground and space, covering a full range of wavelengths, feed the data via processing pipelines into dedicated archives, where they can be accessed for scientific  ...  Astronomy is at the forefront of "big data" science, with exponentially growing data volumes and data rates, and an ever-increasing complexity, now entering the Petascale regime.  ...  We thank numerous colleagues for useful discussions and collaborations over the years, and in particular to M. Graham, A. Mahabal, A. Drake, K. Polsterer, M. Turmon, G. Riccio, D.  ... 
arXiv:1410.5631v2 fatcat:2ssval6hevezdhclx2hgmamv6y

Research in Big Data and Analytics: An Overview

Lekha R.Nair, Sujala D. Shetty
2014 International Journal of Computer Applications  
Big Data Analytics has been gaining much focus of attention lately as researchers from industry and academia are trying to effectively extract and employ all possible knowledge from the overwhelming amount  ...  This paper presents a brief overview of research progress in various areas associated to Big Data Processing and Analytics and conclude with a discussion on research directions in the same area.  ...  More V's are added to Big Data dimensionality such as value that can be derived from the Big Data and veracity which defines the understandability of Big Data.  ... 
doi:10.5120/18980-0407 fatcat:qaixebzdyfhsld6qzqrsk3dd7i

Visualizing Big Data with augmented and virtual reality: challenges and research agenda

Ekaterina Olshannikova, Aleksandr Ometov, Yevgeni Koucheryavy, Thomas Olsson
2015 Journal of Big Data  
In this paper the modified Gartner Inc. definition [33, 34] is used: Big Data is a technology to process high-volume, high-velocity, high-variety data or data-sets to extract intended data value and  ...  Lately, Big Data processing has become more affordable for companies from resource and cost points of view.  ...  Authors' contributions EO performed the primary literature review and analysis for this work as well as designed illustrations. Manuscript was drafted by EO and AO.  ... 
doi:10.1186/s40537-015-0031-2 fatcat:nbpeobicbjfrxdyei3dtbc63bu

Feature-driven visual analytics of soccer data

Halld'or Janetzko, Dominik Sacha, Manuel Stein, Tobias Schreck, Daniel A. Keim, Oliver Deussen
2014 2014 IEEE Conference on Visual Analytics Science and Technology (VAST)  
We present a system for analyzing high-frequency position-based soccer data at various levels of detail, allowing to interactively explore and analyze for movement features and game events.  ...  Our Visual Analytics method covers single-player, multi-player and event-based analytical views.  ...  The soccer data used in this publication was generously provided by prozone/mastercoach.  ... 
doi:10.1109/vast.2014.7042477 dblp:conf/ieeevast/JanetzkoSSSKD14 fatcat:bzllexqemncntdqh7bxqvejgke

Big Data Analytics for Prostate Radiotherapy

James Coates, Luis Souhami, Issam El Naqa
2016 Frontiers in Oncology  
When taken together, such variables make up the basis for a multi-dimensional space (the "RadoncSpace") in which the presented modeling techniques search in order to identify significant predictors.  ...  We conclude by considering advanced modeling techniques that borrow concepts from big data analytics, such as machine learning and artificial intelligence, before discussing the potential future impact  ...  on paper.  ... 
doi:10.3389/fonc.2016.00149 pmid:27379211 pmcid:PMC4905980 fatcat:ffhv3e6dnfc3jod4tmr4npe35u
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