Big data
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The document explores the concept of big data, defining it through its volume, velocity, variety, and characteristics such as scalability and ethical considerations. It critiques the common belief that big data inherently provides more accurate insights, highlighting issues like potential biases and the implications of limited access. The document concludes with calls for careful handling and ethical protocols for utilizing big data in research.
Big data
- 1. Big Data Claire Choong Learning & Research Librarian (Scholarly Communications)
- 2. Etymology
- 3. Definitions: 3 Vs? âhuge in volume â consisting of terabytes or petabytes of data high in velocity â being created in or near real-time diverse in variety in type â being structured and unstructured in nature, and often temporally and spatially referencedâ (Kitchin, 2014)
- 4. Other key characteristics exhaustive in scope ( n=all) fine-grained in resolution indexical in identification (able to be uniquely labelled and identified) relational in nature (different datasets can be conjoined) flexible â can add new fields easily scalable - can expand in size rapidly
- 5. Small and Big Data Small data Big Data Volume Limited to large Very large Velocity Slow, freeze-framed, bundled Fast, continuous Variety Limited to wide Wide Exhaustivity Samples Entire populations Resolutions and indexicality Course and weak to tight and strong Tight and strong Relationality Weak to strong Strong Extensionability and scalability Low to middling High
- 6. Vagaries
- 7. The mythology of Big Data âthe widespread belief that large data sets offer a higher form of intelligence and knowledge that can generate insights that were previously impossible, with the aura of truth, objectivity and accuracy.â boyd & Crawford
- 8. Ethics
- 9. Inequalities
- 10. Practicalities Implications for the training of future academics â thatâs you! Institutional and cross-institutional infrastructures to support data storage and processing capacity Agreements and incentives for sharing data need to be drawn up (e.g. Concordat on Open Research Data) Ethical guidelines and protocols are needed
- 11. What do Big Data actually tell us? what people actually do (not what they say they do) patterns of behaviour
- 12. boyd with a small b Big Data changes the definition of knowledge Claims to objectivity and accuracy are misleading Bigger data are not always better data Taken out of context, Big Data loses its meaning Just because it is accessible does not make it ethical Limited access to Big Data creates new digital divides These points should be carefully considered before utilising Big Data in research.
- 13. Conclusions âData should be cooked with careâ (Bowker (2005) in boyd and Crawford, 2012)
- 14. Big Data in practice Fast food Beer Casinos Supermarkets Healthcare Zooniverse
- 15. Researcher Development (Vitae) Framework
- 16. Sources ⢠boyd, d. and Crawford, K. (2012) âCritical questions for Big Dataâ, Information, Communication & Society, 15(5), pp. 662-679. ⢠Davidag. (2011) âDrive Thruâ. Available at: http://flic.kr/p/9X8hpQ. Accessed 9th August 2017. ⢠Dinnen, P. (2010) âSketch of Twitter Data Visualizationâ. Available at: http://flic.kr/p/7MH2rf. Accessed 8th August 2017. ⢠Eynon, R. (2013) âThe rise of Big Data: what does it mean for education, technology, and media research?â, Learning, Media and Technology, 30(3), pp. 237-240. ⢠G4ll4is. (2013) âPrivacyâ. Available at: http://flic.kr/p/dZ2y6b. Accessed 8th August 2017. ⢠Kitchin, R. (2014) The Data Revolution, London: SAGE. ⢠Kitchin, R. and McArdle, G. (2016) âWhat makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasetsâ, Big Data & Society, January-June 2016, pp. 1-10.
- 17. Sources (2) ⢠Lebied, M. (2017) â5 big data examples in your real life at bars, restaurants and casinosâ, Datapine. Available at: http://www.datapine.com/blog/big-data-examples-in-real-life/. Accessed 9th August 2017. ⢠Marr, B. (2016) âThe most practical big data use cases of 2016â, Forbes. Available at: https://www.forbes.com/sites/bernardmarr/2016/08/25/the-most-practical-big-data-use- cases-of-2016. Accessed 9th August 2017. ⢠System of Ideas. (2012) âVâ. Available at: http://flic.kr/p/bi2CPn. Accessed 8th August 2017. ⢠Yassan Yukky. (2011) âCookingâ. Available at: http://flic.kr/p/9tU7BB. Accessed 9th August 2017.