scholarly journals The significance of typography in data visualization

2021 ◽  
Vol 11 (1) ◽  
pp. 12-23
Author(s):  
Halime Turkkan
Keyword(s):  
Big Data ◽  
Data Visualization ◽  
Graphic Design ◽  
Design Space ◽  
Critical Issue ◽  
Information Design ◽  
The Other ◽  
Essential Information ◽  
Digital World ◽  
Design Systems

With the development of technology and the dominance of the digital world, typography has become a critical issue. Information design systems are considered as one of the significant areas of graphic design and big data provides essential information on data visualization. This research aims to analyse the effects of typographic elements on visualizing data in terms of visual communication, by discussing the value that typography gives to design space. The research discusses randomly selected 10 infographic design samples published in the last six months on google. From the results, 5 designs with typographic concern were more favourable and visually more striking and preferable than the other 5 designs in terms of design disciplines. As in all areas of graphic design, it is argued that the power of typography is an indisputable concept in data visualization, which is seen as a sub-branch of information design. Keywords: data visualization; design; typography, significance, technology

scholarly journals The significance of typography in data visualisation

2020 ◽  
Vol 10 (1) ◽  
pp. 75-84
Author(s):  
Halime Türkkan
Keyword(s):  
Critical Issue ◽  
Information Design ◽  
Data Visualisation ◽  
Design Data ◽  
Visual Elements ◽  
Digital World ◽  
Design Systems ◽  
Critical Components ◽  
To Receive ◽  
Type Hierarchy

With the development of technology and the dominance of the digital world, typography has become a critical issue. Information design systems are considered as one of the significant areas of graphic design. Big data provides important information on data visualisation. While presenting this information, the value that the script adds to the design will be examined in this study. The choice of typefaces, leading and kerning in typography, type hierarchy, harmony, balance, unity, the contrast between the visual elements and typography are the critical components of data visualisation. ‘Communication designers often err on the side of providing features that entertain and visually please audience's ability to receive or understand the message, in the hope that messages will be understood because they are associated with appealing features. Although designers often concentrate on visuals and aesthetics, at other times they hope to attract viewers by focusing clearly on valuable content. But too often both approaches impair the audience's ability to receive or understand the message’. In support of what Jacobson mentioned above in his book titled Information Design, this study aims to emphasise the undeniable importance of typography in data visualisation designed for informative purposes.   Keywords: Typography, design, data visualisation

Big Data for Satellite Image Processing

2022 ◽  
pp. 1110-1124
Author(s):  
Remya S. ◽  
Ramasubbareddy Somula ◽  
Sravani Nalluri ◽  
Vaishali R. ◽  
Sasikala R.
Keyword(s):  
Image Processing ◽  
Big Data ◽  
Satellite Image ◽  
High Volume ◽  
The Other ◽  
Essential Information ◽  
Satellite Image Processing ◽  
Architecture Modeling

This chapter presents an introduction to the basics in big data including architecture, modeling, and the tools used. Big data is a term that is used for serving the high volume of data that can be used as an alternative to RDBMS and the other analytical technologies such as OLAP. For every application there exist databases that contain the essential information. But the sizes of the databases vary in different applications and we need to store, extract, and modify these databases. In order to make it useful, we have to deal with it efficiently. This is the place that big data plays an important role. Big data exceeds the processing and the overall capacity of other traditional databases. In this chapter, the basic architecture, tools, modeling, and challenges are presented in each section.

Big Data for Satellite Image Processing

2018 ◽  
pp. 133-150
Author(s):  
Remya S. ◽  
Ramasubbareddy Somula ◽  
Sravani Nalluri ◽  
Vaishali R. ◽  
Sasikala R.
Keyword(s):  
Image Processing ◽  
Big Data ◽  
Satellite Image ◽  
High Volume ◽  
The Other ◽  
Essential Information ◽  
Satellite Image Processing ◽  
Architecture Modeling

This chapter presents an introduction to the basics in big data including architecture, modeling, and the tools used. Big data is a term that is used for serving the high volume of data that can be used as an alternative to RDBMS and the other analytical technologies such as OLAP. For every application there exist databases that contain the essential information. But the sizes of the databases vary in different applications and we need to store, extract, and modify these databases. In order to make it useful, we have to deal with it efficiently. This is the place that big data plays an important role. Big data exceeds the processing and the overall capacity of other traditional databases. In this chapter, the basic architecture, tools, modeling, and challenges are presented in each section.

The beginning of phygital world

2020 ◽  
Vol 10 (2) ◽  
pp. 1-4
Author(s):  
Evgeny Soloviov ◽  
Alexander Danilov
Keyword(s):  
Big Data ◽  
Learning Styles ◽  
21St Century ◽  
Digital Technology ◽  
Aviation Education ◽  
Digital World ◽  
The World ◽  
Unique Experience ◽  
Smart Data

The Phygital word itself is the combination pf physical and digital technology application.This paper will highlight the detail of phygital world and its importance, also we will discuss why its matter in the world of technology along with advantages and disadvantages.It is the concept and technology is the bridge between physical and digital world which bring unique experience to the users by providing purpose of phygital world. It is the technology used in 21st century to bring smart data as opposed to big data and mix into the broader address of array of learning styles. It can bring new experience to every sector almost like, retail, medical, aviation, education etc. to maintain some reality in today’s world which is developing technology day to day. It is a general reboot which can keep economy moving and guarantee the wellbeing of future in terms of both online and offline.

scholarly journals DV-DVFS: merging data variety and DVFS technique to manage the energy consumption of big data processing

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hossein Ahmadvand ◽  
Fouzhan Foroutan ◽  
Mahmood Fathy
Keyword(s):  
Big Data ◽  
Energy Consumption ◽  
Processing Time ◽  
Experimental Results ◽  
The Other ◽  
Data Sets ◽  
Multiple Sources ◽  
Evaluation Phase ◽  
Dynamic Voltage ◽  
Processing Resources

AbstractData variety is one of the most important features of Big Data. Data variety is the result of aggregating data from multiple sources and uneven distribution of data. This feature of Big Data causes high variation in the consumption of processing resources such as CPU consumption. This issue has been overlooked in previous works. To overcome the mentioned problem, in the present work, we used Dynamic Voltage and Frequency Scaling (DVFS) to reduce the energy consumption of computation. To this goal, we consider two types of deadlines as our constraint. Before applying the DVFS technique to computer nodes, we estimate the processing time and the frequency needed to meet the deadline. In the evaluation phase, we have used a set of data sets and applications. The experimental results show that our proposed approach surpasses the other scenarios in processing real datasets. Based on the experimental results in this paper, DV-DVFS can achieve up to 15% improvement in energy consumption.

CAD in the CIM Environment: Where Do We Go From Here?

1986 ◽  
Vol 39 (9) ◽  
pp. 1345-1349 ◽  
Author(s):  
Dell K. Allen ◽  
W. Van Twelves
Keyword(s):  
Computer Aided Design ◽  
Material Selection ◽  
Operating Conditions ◽  
Computer Integrated Manufacturing ◽  
Accurate Information ◽  
Functional Requirements ◽  
Essential Information ◽  
Design Systems ◽  
Aided Design ◽  
Product Definition

The importance of computer-aided design (CAD) has not been fully appreciated as it relates to computer integrated manufacturing (CIM). The CAD product definition model can provide essential information for many down-stream production, estimating, tooling, and quality assurance functions in the CIM environment. However, the product definition model may be inaccurate or incomplete, thus causing incomplete communication with possible scrap, re-work, and missed production deadlines. Other problems are related to the fact that many of our expert designers are retiring and taking their expertise with them. Merely being able to make 2D or 3D drawings on a CAD workstation does not make its operator a designer. A knowledge of production processes, tolerances, surface finish, and material selection is needed to supplement a designers knowledge of user needs, product functional requirements, operating conditions, cost, quality, and reliability targets. One of the most promising methods for providing timely and accurate information to the designer on an “as-needed” basis is through the use of expert design systems. Such systems promise to bridge the knowledge gap between CAD and CAM and help to incorporate these functions into the overall CIM environment.

scholarly journals An Approach for Big Data to Evolve the Auspicious Information from Cross-Domains

2017 ◽  
Vol 7 (2) ◽  
pp. 967 ◽  
Author(s):  
Preeti Arora ◽  
Deepali Virmani ◽  
P.S. Kulkarni
Keyword(s):  
Big Data ◽  
Sentiment Analysis ◽  
Relevant Information ◽  
Domain Analysis ◽  
The Self ◽  
The Other ◽  
Classification Approach ◽  
Cross Domain ◽  
The Cross

Sentiment analysis is the pre-eminent technology to extract the relevant information from the data domain. In this paper cross domain sentimental classification approach Cross_BOMEST is proposed. Proposed approach will extract <strong>†</strong>ve words using existing BOMEST technique, with the help of Ms Word Introp, Cross_BOMEST determines <strong>†</strong>ve words and replaces all its synonyms to escalate the polarity and blends two different domains and detects all the self-sufficient words. Proposed Algorithm is executed on Amazon datasets where two different domains are trained to analyze sentiments of the reviews of the other remaining domain. Proposed approach contributes propitious results in the cross domain analysis and accuracy of 92 % is obtained. Precision and Recall of BOMEST is improved by 16% and 7% respectively by the Cross_BOMEST.

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