Open access peer-reviewed Edited Volume

Data Visualization

Sara Shirowzhan

UNSW Sydney

Dr. Shirowzhan develops metrics, GIS-based apps, and algorithms to solve digital problems of 3D representation and analysis of indoor and outdoor Built Environment.

Covering

Trend Extraction Machine Learning Web-based Visualization Augmented Reality Virtual Reality Energy Data Analysis nD visualization Spatial and Temporal Trends Point Clouds Images Advanced Sensing Technologies Computer Vision

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About the book

As a graphic representation of data, data visualization is a useful approach for communicating with viewers which offers them a representation of possible trends or patterns of relationships among the represented data. Data visualization can be considered in various dimensions including 1D, 2D, 3D, and 4D. Where the spatial and temporal information of data is involved, the dimension of data can be increased from 2D to 3D or 4D. Evolving technologies are available for data visualization, including web-based platforms, which increase the interaction and the efficiency of using data by viewers. Data science methods including data mining, machine learning, and deep learning can be applied to extract patterns, identify problems, or predict the future/expected outcomes. Using these methods helps to explore deeper insights, offer accurate predictions, or even generate suggestions or decisions to users and decision makers. The examples include smart cities or smart construction where information is modelled in 3D, 4D, 5D, 6D and 7D and can be analysed in either Building Information Modelling (BIM) or Geographic Information System (GIS) environments. The integration of data mining techniques with BIM and GIS has resulted in significant improvements in data-driven decision-making and has offered efficient communication tools, reduction of reworks, higher productivity, and better time management.

This book tends to discuss different relevant areas of data visualizations and point to new avenues for developing innovative approaches, novel methods, learn from the smart data visualization literature across data science, engineering and the built environment fields that have been gateways for extracting hidden patterns and relationships among variables and agents with a broad impact to be used on other similar fields. This book calls for chapters proposing innovative and impressive data visualizations by increasing understanding of data and improving the insight from data for better decision making related to the analysis methods.

Publishing process

Book initiated and editor appointed

Date completed: September 1st 2020

Applications to edit the book are assessed and a suitable editor is selected, at which point the process begins.

Chapter proposals submitted and reviewed

Deadline for chapter proposals: September 29th 2020

Potential authors submit chapter proposals ready for review by the academic editor and our publishing review team.

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Approved chapters written in full and submitted

Deadline for full chapters: November 28th 2020

Once approved by the academic editor and publishing review team, chapters are written and submitted according to pre-agreed parameters

Full chapters peer reviewed

Review results due: February 16th 2021

Full chapter manuscripts are screened for plagiarism and undergo a Main Editor Peer Review. Results are sent to authors within 30 days of submission, with suggestions for rounds of revisions.

Book compiled, published and promoted

Expected publication date: April 17th 2021

All chapters are copy-checked and typesetted before being published. IntechOpen regularly submits its books to major databases for evaluation and coverage, including the Clarivate Analytics Book Citation Index in the Web of ScienceTM Core Collection. Other discipline-specific databases are also targeted, such as Web of Science's BIOSIS Previews.

About the editor

Sara Shirowzhan

UNSW Sydney

Dr. Sara Shirowzhan completed her Ph.D. in Geomatic Engineering at UNSW and her strong capability in designing and conducting high-quality multi-disciplinary research has been demonstrated by solving complex problems facing digital representation and analysis of the built environment and civil engineering infrastructures. Her areas of interest for research are automation, laser scanning technologies and robotics for construction, remote sensing and advanced GIS for Smart Cities and monitoring 3D urban growth, metric development for sustainability assessment and urban infrastructures. Some of her areas of expertise include lidar technology, machine learning algorithms, and app development. She has taught and supervised students in architecture, urban planning and construction departments as a lecturer, and research supervisor in several universities for over 10 years.

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Book chapters authored 2

Books edited 1

Introducing your Author Service Manager

Mr. Mateo Pulko

As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. Whether that be identifying an exceptional author and proposing an editorship collaboration, or contacting researchers who would like the opportunity to work with IntechOpen, I establish and help manage author and editor acquisition and contact.

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