Big Data in the Arts and Humanities
Big Data in the Arts and Humanities

Author: Giovanni Schiuma

Publisher: CRC Press

Published: 2018-04-27

Total Pages: 361

ISBN-13: 1351172581

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As digital technologies occupy a more central role in working and everyday human life, individual and social realities are increasingly constructed and communicated through digital objects, which are progressively replacing and representing physical objects. They are even shaping new forms of virtual reality. This growing digital transformation coupled with technological evolution and the development of computer computation is shaping a cyber society whose working mechanisms are grounded upon the production, deployment, and exploitation of big data. In the arts and humanities, however, the notion of big data is still in its embryonic stage, and only in the last few years, have arts and cultural organizations and institutions, artists, and humanists started to investigate, explore, and experiment with the deployment and exploitation of big data as well as understand the possible forms of collaborations based on it. Big Data in the Arts and Humanities: Theory and Practice explores the meaning, properties, and applications of big data. This book examines therelevance of big data to the arts and humanities, digital humanities, and management of big data with and for the arts and humanities. It explores the reasons and opportunities for the arts and humanities to embrace the big data revolution. The book also delineates managerial implications to successfully shape a mutually beneficial partnership between the arts and humanities and the big data- and computational digital-based sciences. Big data and arts and humanities can be likened to the rational and emotional aspects of the human mind. This book attempts to integrate these two aspects of human thought to advance decision-making and to enhance the expression of the best of human life.

The Digital Arts and Humanities
The Digital Arts and Humanities

Author: Charles Travis

Publisher: Springer

Published: 2016-11-02

Total Pages: 0

ISBN-13: 9783319409511

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The case studies in this book illuminate how arts and humanities tropes can aid in contextualizing Digital Arts and Humanities, Neogeographic and Social Media activity and data through the creation interpretive schemas to study interactions between visualizations, language, human behaviour, time and place.

Data Analytics in Digital Humanities
Data Analytics in Digital Humanities

Author: Shalin Hai-Jew

Publisher: Springer

Published: 2017-05-03

Total Pages: 304

ISBN-13: 3319544993

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This book covers computationally innovative methods and technologies including data collection and elicitation, data processing, data analysis, data visualizations, and data presentation. It explores how digital humanists have harnessed the hypersociality and social technologies, benefited from the open-source sharing not only of data but of code, and made technological capabilities a critical part of humanities work. Chapters are written by researchers from around the world, bringing perspectives from diverse fields and subject areas. The respective authors describe their work, their research, and their learning. Topics include semantic web for cultural heritage valorization, machine learning for parody detection by classification, psychological text analysis, crowdsourcing imagery coding in natural disasters, and creating inheritable digital codebooks.Designed for researchers and academics, this book is suitable for those interested in methodologies and analytics that can be applied in literature, history, philosophy, linguistics, and related disciplines. Professionals such as librarians, archivists, and historians will also find the content informative and instructive.

Knowledge Management, Arts, and Humanities
Knowledge Management, Arts, and Humanities

Author: Meliha Handzic

Publisher: Springer

Published: 2019-03-28

Total Pages: 259

ISBN-13: 3030109224

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This book presents a series of studies that demonstrate the value of interactions between knowledge management with the arts and humanities. The carefully compiled chapters show, on the one hand, how traditional methods from the arts and humanities – e.g. theatrical improvisation, clay modelling, theory of aesthetics – can be used to enhance knowledge creation and evolution. On the other, the chapters discuss knowledge management models and practices such as virtual knowledge space (BA) design, social networking and knowledge sharing, data mining and knowledge discovery tools. The book also demonstrates how these practices can yield valuable benefits in terms of organizing and analyzing big arts and humanities data in a digital environment.

Big Data in Education: Pedagogy and Research
Big Data in Education: Pedagogy and Research

Author: Theodosia Prodromou

Publisher: Springer Nature

Published: 2021-10-04

Total Pages: 249

ISBN-13: 3030768414

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This book discusses how Big Data could be implemented in educational settings and research, using empirical data and suggesting both best practices and areas in which to invest future research and development. It also explores: 1) the use of learning analytics to improve learning and teaching; 2) the opportunities and challenges of learning analytics in education. As Big Data becomes a common part of the fabric of our world, education and research are challenged to use this data to improve educational and research systems, and also are tasked with teaching coming generations to deal with Big Data both effectively and ethically. The Big Data era is changing the data landscape for statistical analysis, the ways in which data is captured and presented, and the necessary level of statistical literacy to analyse and interpret data for future decision making. The advent of Big Data accentuates the need to enable citizens to develop statistical skills, thinking and reasoning needed for representing, integrating and exploring complex information. This book offers guidance to researchers who are seeking suitable topics to explore. It presents research into the skills needed by data practitioners (data analysts, data managers, statisticians, and data consumers, academics), and provides insights into the statistical skills, thinking and reasoning needed by educators and researchers in the future to work with Big Data. This book serves as a concise reference for policymakers, who must make critical decisions regarding funding and applications.

Uncertain Archives
Uncertain Archives

Author: Nanna Bonde Thylstrup

Publisher: MIT Press

Published: 2021-02-02

Total Pages: 638

ISBN-13: 0262539888

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Scholars from a range of disciplines interrogate terms relevant to critical studies of big data, from abuse and aggregate to visualization and vulnerability. This pathbreaking work offers an interdisciplinary perspective on big data, interrogating key terms. Scholars from a range of disciplines interrogate concepts relevant to critical studies of big data--arranged glossary style, from from abuse and aggregate to visualization and vulnerability--both challenging conventional usage of such often-used terms as prediction and objectivity and introducing such unfamiliar ones as overfitting and copynorm. The contributors include both leading researchers, including N. Katherine Hayles, Johanna Drucker and Lisa Gitelman, and such emerging agenda-setting scholars as Safiya Noble, Sarah T. Roberts and Nicole Starosielski.

Data Loam
Data Loam

Author: Johnny Golding

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2020-12-16

Total Pages: 496

ISBN-13: 311069784X

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Als Reaktion auf die dominante Wirkkraft und Deutungshoheit des Digitalen vereint Data Loam auf der Basis von Positionen der internationalen zeitgenössischen Kunstpraxis radikale Denkansätze. Vorbei: das Beharren auf Indexikalität und die instrumentelle Reduktion des Wissens. Stattdessen: eine neue Metrik, die Spiel, Neugier, Experiment und Risiko fordert. Als dringende Antwort auf die stetig wachsende Informationsflut, der Bibliotheken, Suchmaschinen und kulturelle Einrichtungen ausgesetzt sind, werden Ansätze entwickelt, die sinnliche Logik, kausale Durchlässigkeit und neue Formen der Mensch-Maschine-Interaktion anregen und erlauben. Data Loam beleuchtet die Zukunft von Wissenssystemen in Texten zu künstlicher Intelligenz, Kybernetik und Kryptoökonomie: als Gegenmittel zur Zerstreuung apokalyptischer Ängste.

Extraordinary Partnerships
Extraordinary Partnerships

Author: Christine Henseler

Publisher: Lever Press

Published: 2020-05-01

Total Pages: 418

ISBN-13: 164315009X

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This inspirative and hopeful collection demonstrates that the arts and humanities are entering a renaissance that stands to change the direction of our communities. Community leaders, artists, educators, scholars, and professionals from many fields show how they are creating responsible transformations through partnership in the arts and humanities. The diverse perspectives that come together in this book teach us how to perceive our lives and our disciplines through a broader context. The contributions exemplify how individuals, groups, and organizations use artistic and humanistic principles to explore new structures and novel ways of interacting to reimagine society. They refresh and reinterpret the ways in which we have traditionally assigned space and value to the arts and humanities.

High-Performance Big Data Computing
High-Performance Big Data Computing

Author: Dhabaleswar K. Panda

Publisher: MIT Press

Published: 2022-08-02

Total Pages: 275

ISBN-13: 0262369427

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An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deployment and management; and surveys benchmarks and workloads for evaluating big data middleware systems. It presents a detailed discussion of big data computing systems and applications with high-performance networking, computing, and storage technologies, including state-of-the-art designs for data processing and storage systems. Finally, the book considers some advanced research topics in high-performance big data computing, including designing high-performance deep learning over big data (DLoBD) stacks and HPC cloud technologies.