Big Data and the Little Big Bang: An Epistemological (R)evolution
Starting from an analysis of frequently employed definitions of big data, it will be argued that, to overcome the intrinsic weaknesses of big data, it is more appropriate to define the object in relational terms. The excessive emphasis on volume and technological aspects of big data, derived from th...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Published: |
Frontiers
2020
|
| Online Access: | https://hdl.handle.net/1721.1/128865 |
| _version_ | 1826207767482859520 |
|---|---|
| author | Balazka, Dominik Rodighiero, Dario |
| author2 | Massachusetts Institute of Technology. Program in Comparative Media Studies/Writing |
| author_facet | Massachusetts Institute of Technology. Program in Comparative Media Studies/Writing Balazka, Dominik Rodighiero, Dario |
| author_sort | Balazka, Dominik |
| collection | MIT |
| description | Starting from an analysis of frequently employed definitions of big data, it will be argued that, to overcome the intrinsic weaknesses of big data, it is more appropriate to define the object in relational terms. The excessive emphasis on volume and technological aspects of big data, derived from their current definitions, combined with neglected epistemological issues gave birth to an objectivistic rhetoric surrounding big data as implicitly neutral, omni-comprehensive, and theory-free. This rhetoric contradicts the empirical reality that embraces big data: (1) data collection is not neutral nor objective; (2) exhaustivity is a mathematical limit; and (3) interpretation and knowledge production remain both theoretically informed and subjective. Addressing these issues, big data will be interpreted as a methodological revolution carried over by evolutionary processes in technology and epistemology. By distinguishing between forms of nominal and actual access, we claim that big data promoted a new digital divide changing stakeholders, gatekeepers, and the basic rules of knowledge discovery by radically shaping the power dynamics involved in the processes of production and analysis of data. |
| first_indexed | 2024-09-23T13:54:38Z |
| format | Article |
| id | mit-1721.1/128865 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T13:54:38Z |
| publishDate | 2020 |
| publisher | Frontiers |
| record_format | dspace |
| spelling | mit-1721.1/1288652022-09-28T17:01:08Z Big Data and the Little Big Bang: An Epistemological (R)evolution Balazka, Dominik Rodighiero, Dario Massachusetts Institute of Technology. Program in Comparative Media Studies/Writing Starting from an analysis of frequently employed definitions of big data, it will be argued that, to overcome the intrinsic weaknesses of big data, it is more appropriate to define the object in relational terms. The excessive emphasis on volume and technological aspects of big data, derived from their current definitions, combined with neglected epistemological issues gave birth to an objectivistic rhetoric surrounding big data as implicitly neutral, omni-comprehensive, and theory-free. This rhetoric contradicts the empirical reality that embraces big data: (1) data collection is not neutral nor objective; (2) exhaustivity is a mathematical limit; and (3) interpretation and knowledge production remain both theoretically informed and subjective. Addressing these issues, big data will be interpreted as a methodological revolution carried over by evolutionary processes in technology and epistemology. By distinguishing between forms of nominal and actual access, we claim that big data promoted a new digital divide changing stakeholders, gatekeepers, and the basic rules of knowledge discovery by radically shaping the power dynamics involved in the processes of production and analysis of data. 2020-12-18T21:24:41Z 2020-12-18T21:24:41Z 2020-09 2019-11 Article http://purl.org/eprint/type/JournalArticle 2624-909X https://hdl.handle.net/1721.1/128865 Balazka, Dominik and Dario Rodighiero. "Big Data and the Little Big Bang: An Epistemological (R)evolution." Frontiers in Big Data 3 (September 2020): 31 © 2020 Balazka and Rodighiero https://doi.org/10.3389/fdata.2020.00031 Frontiers in Big Data Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf Frontiers Frontiers |
| spellingShingle | Balazka, Dominik Rodighiero, Dario Big Data and the Little Big Bang: An Epistemological (R)evolution |
| title | Big Data and the Little Big Bang: An Epistemological (R)evolution |
| title_full | Big Data and the Little Big Bang: An Epistemological (R)evolution |
| title_fullStr | Big Data and the Little Big Bang: An Epistemological (R)evolution |
| title_full_unstemmed | Big Data and the Little Big Bang: An Epistemological (R)evolution |
| title_short | Big Data and the Little Big Bang: An Epistemological (R)evolution |
| title_sort | big data and the little big bang an epistemological r evolution |
| url | https://hdl.handle.net/1721.1/128865 |
| work_keys_str_mv | AT balazkadominik bigdataandthelittlebigbanganepistemologicalrevolution AT rodighierodario bigdataandthelittlebigbanganepistemologicalrevolution |