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Big Historical Data: Theories, Methods, and Applications.
・ISBN 978-3-032-38151-4 hard EUR 49.99
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| 著者・編者 | Fernandes, Ricardo / Harris, Alison / Hixon, Sean / Cocozza, Carlo (eds.), |
|---|---|
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2026 |
| ページ数 | 274 pp. |
| 言語 | ENG |
| ニュース番号 | <A05-88251> |
解説
This open access book comprehensively overviews the groundbreaking insights and methodologies presented at the inaugural Big Historical Data Conference held in November 2023. It is a synthesis of interdisciplinary research leveraging advanced computational techniques and digital data to unravel historical processes. The book is segmented into theoretical, methodological, and application sections, each essential for understanding the value and challenges of Big Historical Data.
The modelling section introduces various computational techniques applied to historical data to simulate and predict ancient human-environment interactions; application case studies present relevant examples of insights obtained through use of Big Historical Data; and the theory section explores the philosophical, ethical, and theoretical implications of digital data in historical research. The accumulation of digital data and advancements in computational techniques have revolutionized the study of past human-environmental interactions, presenting significant challenges in data management, integration, and interpretation. New tools and frameworks are needed to harmonize and analyze diverse data sources. By proposing a holistic overview, our book seeks to enable a more integrated and insightful examination of historical processes, offering a clearer lens through which we can understand the past and its lessons for the future.
This book is aimed at researchers, scholars, and students in the fields of history, archaeology, paleo-environmental sciences, and related disciplines interested in using Big Data and digital methodologies in historical research. Additionally, it serves as an invaluable resource for data scientists and computational modellers seeking to apply their technical expertise to historical contexts, for educators looking to incorporate cutting-edge research into their curricula and programs, and for policymakers who wish to explore the use of historical knowledge to address modern-day problems.