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Cultural Data Science : An Introduction to R / by Harald Klinke.

Springer Nature - Springer Mathematics and Statistics (R0) eBooks 2025 English International Available online

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Format:
Book
Author/Creator:
Klinke, Harald.
Series:
Quantitative Methods in the Humanities and Social Sciences, 2199-0964
Language:
English
Subjects (All):
Quantitative research.
Information visualization.
Art--History.
Art.
Data Analysis and Big Data.
Data and Information Visualization.
Art History.
Local Subjects:
Data Analysis and Big Data.
Data and Information Visualization.
Art History.
Physical Description:
1 online resource (159 pages)
Edition:
1st ed. 2025.
Place of Publication:
Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Summary:
This book addresses growing demand in the visual humanities for foundational knowledge in data analysis, image processing, and artificial intelligence. Intended for readers without prior technical knowledge, its eighteen chapters introduce key concepts in data science through examples from art history, visual computing, and cloud technologies. For advanced readers, it explores how digital methods enhance our understanding of our cultural past. Focusing on image-based humanities research, the book demonstrates practical applications using open source software such as R, RStudio, and ImageMagick, along with open data sets from institutions like the MoMA, the Met, and the Rijksmuseum. Ideal for students, researchers, and professionals in art history, digital humanities, and museum studies, this book bridges the gap between technology and the humanities, making complex digital methods accessible to a broad audience.
Contents:
Chapter 1 Introduction
Chapter 2 Setting up R
Chapter 3 First Steps
Chapter 4 First Data
Chapter 5 Exploring Data
Chapter 6 Compare data
Chapter 7 Case Study 1: Picasso from creation to acquisition
Chapter 8 Subdividing and combining data sets
Chapter 9 Case Study 2: Photography Aspect Ratios
Chapter 10 Case Study 3: Overview of the MNBAQ Dataset
Chapter 11 Stacked bar plot
Chapter 12 Working with Images
Chapter 13 Case Study: Image plot
Chapter 14 Dimensions
Chapter 15 Network Visualizations
Chapter 16 Image Analysis
Chapter 17 Cloud Computing
Chapter 18 Epilogue: The Future of Cultural Data Science.
ISBN:
3-031-88130-3
OCLC:
1520499313

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