The Trouble With Big Data: How Datafication Displaces Cultural Practices
- Length: 192 pages
- Edition: 1
- Language: English
- Publisher: Bloomsbury Academic
- Publication Date: 2022-01-27
- ISBN-10: 1350239623
- ISBN-13: 9781350239623
- Sales Rank: #0 (See Top 100 Books)
This book explores the challenges society faces with big data, through the lens of culture rather than social, political or economic trends, as demonstrated in the words we use, the values that underpin our interactions, and the biases and assumptions that drive us. Focusing on areas such as data and language, data and sensemaking, data and power, data and invisibility, and big data aggregation, it demonstrates that humanities research, focussing on cultural rather than social, political or economic frames of reference for viewing technology, resists mass datafication for a reason, and that those very reasons can be instructive for the critical observation of big data research and innovation.
Cover Half title Series Title Title Copyright Contents Acknowledgements 1 | Viewing big data through the lens of culture The KPLEX project The KPLEX interviews Knowledge complexity ‘in the wild’ Applying the KPLEX approach to these issues 2 | What do we mean when we talk about data? 3 | Making sense of data Interpretation in the humanities: Two examples Digitization and the change of interpretive practices in the humanities The historical sciences and big data Numbers and description, narrative and interpretation Science as a social system: The social construction of meaning Making sense of big data 4 | Please mind the gap: The problems of information voids in the knowledge discovery process The dominance of search engines Ranking and the long tail problem Cultural heritage institutions: The original custodians of big data CHIs provide expert services as knowledge gatekeepers Content versus context Spacelessness, placelessness and hypertravel Google as a threat Benefits of search engines and digital cultural heritage Beyond the keyword 5 | Data incognita: How do data become hidden? Hidden by digital obscurity Hidden by working practices Hidden by inconsistent methods of description Hidden by a loss or unavailability of expertise Hidden by a lack of material resources Hidden by privacy The dark side of discoverability Discovery through cultural heritage institutional involvement in (European) data and research infrastructures The future should not be hidden 6 | From obscure data to datafied obscurity: The invisibilities of datafication What you see is what you get The minoritized material: Corner cases and downward spirals of invisibility Casting a shadow: A little sharing is a dangerous thing Knowledge after Google: The agonism of archives and AI Future invisibilities: Popular music, unmapped terrain and alternative facts Hypernormalised hypermarkets of big data: Refusing to be cowed 7 | Power through datafication Language as data Cultural heritage The academic field Conclusion 8 | Expatriates in the land of data: Software tensions as a clash of culture More questions than answers? Is software production also a culture? Cross-cultural competencies for a Digital Age Index
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