Del i serien Quantitative Methods in the Humanities and Social Sciences

Cultural Data Science

An Introduction to R

Inbunden, Engelska, 2025

1 419 kr

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mso-fareast-language: EN-US;">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.

Produktinformation

Utgivningsdatum2025-05-17
Mått155 x 235 x 17 mm
Vikt400 g
FormatInbunden
SpråkEngelska
SerieQuantitative Methods in the Humanities and Social Sciences
Antal sidor161
FörlagSpringer International Publishing AG
ISBN9783031881299

Tillhör följande kategorier

Konsthistoria inom Kultur
Databaser inom Data och IT
Människa – datorinteraktion inom Data och IT

Dr. Harald Klinke, M.Sc., leads the Big Data Analysis business unit in a German federal authority and serves as a private lecturer at Ludwig-Maximilians-University Munich (LMU). As the founder and editor-in-chief of the International Journal for Digital Art History, he plays a key role in shaping discourse and research in the field, integrating data science with visual culture. His expertise spans art history, digital humanities, and artificial intelligence, with a focus on computational approaches to cultural heritage. Through courses, workshops, and summer schools, Dr. Klinke equips scholars and professionals with the tools to apply digital methods in research and practice. Beyond academia, he has advised institutions on leveraging technology for cultural analysis, fostering innovation at the intersection of AI, data, and the arts.

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.