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Big Data in the Arts and Humanities: Theory and Practice: Data Analytics Applications

Autor Giovanni Schiuma, Daniela Carlucci
en Limba Engleză Paperback – 30 iun 2021
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.
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Specificații

ISBN-13: 9781032095462
ISBN-10: 1032095466
Pagini: 248
Ilustrații: 25 Illustrations, black and white
Dimensiuni: 156 x 234 x 15 mm
Greutate: 0.36 kg
Ediția:1
Editura: CRC Press
Colecția Auerbach Publications
Seria Data Analytics Applications


Cuprins

I. Understanding Big Data in Arts and Humanities. 1. Literature Review on Big Data: What Do We Know So Far? 2. Toward a Data-Driven World: Challenges and Opportunities in Arts and Humanities. 3. "Never Mind the Quality, Feel the Width": Big Data for Quality and Performance Evaluation in the Arts and Cultural Sector and the Case of "Culture Metrics". 4. Toward "Big Data" in Museum Provenance. 5. From Big Data to Thick Data: Theory and Practice. Section II. Digital Humanities. 6. Big Data and the Coming Historical Revolution: From Black Boxes to Models. 7. Use of Big Data in Historical Research. 8. The Study of Networked Content: Five Considerations for Digital Research in the Humanities. 9. The English Gothic Novel: Theories and Praxis of Computer-Based Macroanalysis in Literary Studies. Section III. Managing Big Data with and for Arts and Humanities. 10. Toward a Data Culture in the Cultural and Creative Industries. 11. Arts Council England: Using Big Data to Understand the Quality of Arts and Cultural Work. 12. Visualization of Scientific Image Data as Art Data. 13. Museums, Archives, and Universities—Structuring Future Connections with Big Data. 14. Mobile Technology to Contribute Operatively to the Safeguard of Cultural Heritage. 15. Artists, Data, and Agency in Smart Cities.

Notă biografică

Giovanni Schiuma is professor of innovation management at the University of Basilicata (Italy) and visiting professor of Arts Based Management at University of the Arts London. He is widely recognized as one of the world’s leading experts in arts and business and has authored or coauthored more than 200 publications on a range of research topics particularly embracing strategic knowledge asset and intellectual capital management, strategic performance measurement and management, innovation systems, innovation management, and organizational development. He is an inspiring speaker and facilitator, with extensive research management expertise and excellent ability to coordinate complex projects and lead research teams. Giovanni holds a number of visiting professorships and research fellowship appointments with renowned international universities, and as a visiting lecturer, he regularly gives seminars, workshops, and master classes around the world.


Daniela Carlucci is an assistant professor at the University of Basilicata, Italy. She teaches business management, project management, and project evaluation and management. Her research interests focus mainly on knowledge assets management, performance measurement and management, decision support methods, and organizational development. She has been a visiting scholar at the Cranfield School of Management, visiting professor at the Tampere University of Technology, and visiting researcher at the University of Arts of London. She is author and coauthor of several publications, including chapters of books, articles, and research reports on a range of research topics. Her researches have been published in internationally recognized journals such as Expert Systems with Applications, Production Planning and Control, Healthcare Management Science, Measuring Business Excellence, Knowledge Management Research and Practice, and many others. She systematically carries out referee activities for international scientific journals. She is actively involved in relevant research and consultancy activities as researcher and has worked on research projects involving national organizations and institutions. Moreover, Daniela is systematically engaged in teaching activities in public and private institutions.

Descriere

This books sheds light on the unique and creative contributions that the arts and humanities can make to the development of approaches to effectively use big data. It also looks at opportunities and challenges for research in the arts and humanities created by the capability to handle and use sophisticatedly very huge and complex data sets.