On Big Data: How should we make sense of them?
The topic of Big Data is today extensively discussed, not only on the technical ground. This also depends on the fact that Big Data are frequently presented as allowing an epistemological paradigm shift in scientific research, which would be able to supersede the traditional hypothesis-driven metho...
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| Format: | Article |
| Language: | Catalan |
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Universitat de València
2021-01-01
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| Series: | Mètode Science Studies Journal: Annual Review |
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| Online Access: | https://turia.uv.es/index.php/Metode/article/view/15258 |
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| _version_ | 1846164078410596352 |
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| author | Fulvio Mazzocchi |
| author_facet | Fulvio Mazzocchi |
| author_sort | Fulvio Mazzocchi |
| collection | DOAJ |
| description |
The topic of Big Data is today extensively discussed, not only on the technical ground. This also depends on the fact that Big Data are frequently presented as allowing an epistemological paradigm shift in scientific research, which would be able to supersede the traditional hypothesis-driven method. In this piece, I critically scrutinize two key claims that are usually associated with this approach, namely, the fact that data speak for themselves, deflating the role of theories and models, and the primacy of correlation over causation. My intention is both to acknowledge the value of Big Data analytics as innovative heuristics and to provide a balanced account of what could be expected and what not from it.
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| format | Article |
| id | doaj-art-c509b6b2cd2e4e05b3acbd93b68624da |
| institution | Kabale University |
| issn | 2174-3487 2174-9221 |
| language | Catalan |
| publishDate | 2021-01-01 |
| publisher | Universitat de València |
| record_format | Article |
| series | Mètode Science Studies Journal: Annual Review |
| spelling | doaj-art-c509b6b2cd2e4e05b3acbd93b68624da2024-11-18T16:01:55ZcatUniversitat de ValènciaMètode Science Studies Journal: Annual Review2174-34872174-92212021-01-011110.7203/metode.11.15258On Big Data: How should we make sense of them?Fulvio Mazzocchi0<p>Institute of Heritage Science of the CNR (Rome, Italy).</p> The topic of Big Data is today extensively discussed, not only on the technical ground. This also depends on the fact that Big Data are frequently presented as allowing an epistemological paradigm shift in scientific research, which would be able to supersede the traditional hypothesis-driven method. In this piece, I critically scrutinize two key claims that are usually associated with this approach, namely, the fact that data speak for themselves, deflating the role of theories and models, and the primacy of correlation over causation. My intention is both to acknowledge the value of Big Data analytics as innovative heuristics and to provide a balanced account of what could be expected and what not from it. https://turia.uv.es/index.php/Metode/article/view/15258Big Datadata-driven scienceepistemologyend of theorycausalityopacity of algorithm |
| spellingShingle | Fulvio Mazzocchi On Big Data: How should we make sense of them? Mètode Science Studies Journal: Annual Review Big Data data-driven science epistemology end of theory causality opacity of algorithm |
| title | On Big Data: How should we make sense of them? |
| title_full | On Big Data: How should we make sense of them? |
| title_fullStr | On Big Data: How should we make sense of them? |
| title_full_unstemmed | On Big Data: How should we make sense of them? |
| title_short | On Big Data: How should we make sense of them? |
| title_sort | on big data how should we make sense of them |
| topic | Big Data data-driven science epistemology end of theory causality opacity of algorithm |
| url | https://turia.uv.es/index.php/Metode/article/view/15258 |
| work_keys_str_mv | AT fulviomazzocchi onbigdatahowshouldwemakesenseofthem |