La onto-epistemología del Big Data

Autores/as

DOI:

https://doi.org/10.37293/sapientiae52.03

Palabras clave:

Estudios latinoamericanos marxistas, neoliberalismo, teoría de conjuntos, algoritmos, capitalismo.

Resumen

Este estudio presenta los resultados de una investigación bibliográfica, la cual permite la exploración del fenómeno del Big Data tanto en términos técnicos, como también en términos socio-políticos y filosóficos, a través de la lectura de autores como: Rob Kitchin (2014), Dawn E. Holmes (2017), etc. Aquí se ofrece una nueva aproximación crítica al Big Data, en la medida que el análisis nos ha permitido evaluar no solo los componentes de esta nueva ciencia de datos, sino también las consecuencias onto-epistemológicas derivadas del desarrollo e implementación del Big Data tanto en el campo científico, como en lo cotidiano. También, este artículo nos permite comprender el vínculo entre el Big Data y la teoría de conjuntos en la construcción de una onto-epistemología ligada a un conservadurismo político, con el fin de que nosotros podamos tener un panorama completo para elaborar, en el futuro cercano, estrategias para superar tal fenómeno.

Referencias

Achtnich, Tilmann (reporter). (2018). Juego sin límites: las mentiras del libre comercio. Südwestrundfunk SWR/Deutsche Welle DW. Germany. Available at https://www.youtube.com/watch?v=FEdeaBjOYFs

Alfaro-Vargas, Roy. (2019). La undécima tesis: dialéctica del fascismo neoliberal. Progreso Editorial. Costa Rica. Available at https://yadi.sk/i/YqiEpv_XUITJww?fbclid=IwAR2nHSY1DjgWRaw3PzhMwnMwZpyhra11vW3whl5dn5-IpI4NprW2PcACy0k

Aragona, Biagio & de Rosa, Rossana. (2018). Big Data in policy making. Mathematical Population Studies. UK and USA (Pp.1-7). DOI: 10.1080/08898480.2017. 1418113

Barnes, Trevor J. (2013). Big Data, little history. Dialogues in Human Geography. Vol. 3, No 3. UK (Pp. 297–302). DOI: 10.1177/ 2043820613514323

Burhanuddin, Baki. (2015). Badiou’s Being and Event and the Mathematics of Set Theory. Bloomsbury. UK and USA.

Byrne, David. (1998). Complexity Theory and the Social Sciences. An Introduction. Routledge. UK and USA.

Castellani, Brian & Hafferty, Frederic William. (2009). Sociology and Complexity Science. A New Field of Inquiry. Springer. Germany.

Cilliers, Paul. (1998). Complexity and Postmodernism. Understanding Complex Systems. Routledge. UK and USA.

Cohen, Bruce M.Z. (2016). Psychiatric Hegemony: A Marxist Theory of Mental Illness. Palgrave Macmillan. UK. DOI: 10.1057/978-1-137-46051-6

Couldry, Nick and Mejias, Ulises A. (2018). Data Colonialism: Rethinking Big Data’s Relation to the Contemporary Subject. Television & New Media. UK (Pp. 1-14). DOI: 10.1177/1527476418796632

Danesi, Marcel. (2017). The Semiotics of Emoji. Bloomsbury. UK and USA.

Deighton, John. (2018). Big data. Consumption Markets & Culture. UK (Pp. 1-6). DOI: 10.1080/ 10253866.2017.1422902

Fraser, Heather & Taylor, Nik. (2016). The University Goes to Market: The Infiltration of Neoliberalism. In Fraser, Heather and Taylor, Nik. Neoliberalization, Universities and the Public Intellectual: Species, Gender and Class and the Production of Knowledge. Palgrave Macmillan. UK. DOI: 10.1057/978-1-137-57909-6_1

Gironi, Fabio. (2015). Naturalising Badiou. Mathematical Ontology and Structural Realism. Palgrave Macmillan. UK and USA.

Harvey, David. (2018). Marx, Capital and the Madness of Economic Reason. Oxford University Press. USA.

Holmes, Dawn E. (2017). Big Data. A Very Short Introduction. Oxford University Press. UK.

Humphrys, Elizabeth. (2019). Introduction. In Humphrys, Elizabeth. How Labour Built Neoliberalism: Australia’s Accord, the Labour Movement and the Neoliberal Project. Brill. The Netherlands and USA. DOI: 10.1163/9789004383463_002

Iliadis, Andrew & Russo, Federica. (2016). Critical data studies: An introduction. Big Data & Society. UK (Pp. 1-17). DOI: 10.1177/ 2053951716674238

Kitchin, Rob. (2014). Big Data, new epistemologies and paradigm shifts. Big Data & Society. UK (Pp. 1-12). DOI: 10.1177/2053951714528481

Kitchin, Rob & McArdle, Gavin. (2016). What makes Big Data, Big Data? Exploring the Ontological characteristics of 26 datasets. Big Data & Society. UK (Pp. 1-10). DOI: 10.1177/2053951716631130

Konings, Martijn. (2018). Capital and Time: For a New Critique of Neoliberal Reason. Stanford University Press. USA.

Lee, Min Kyung. (2018). Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic management. Big Data & Society. UK (Pp. 1-16). DOI: 10.1177/2053951718756684

Lefebvre, Henri. (1976). The Survival of Capitalism: Reproduction of the Relations of Production. St. Martin's Press. USA.

Micocci, Andrea & Di Mario, Flavia. (2018). The Fascist Nature of Neoliberalism. Routledge. UK and USA.

Moore, Gregory H. (1978). The Origins of Zermelo's Axiomatization of Set Theory. Journal of Philosophical Logic. Vol. 7, No 1. Germany (Pp. 307-329).

Petitot, Jean. (1994). Phenomenology of Perception, Qualitative Physics and Sheaf Mereology. In Casati, Roberto; Smith, Barry, and White, Graham (eds.). Philosophy and the Cognitive Sciences. Hölder-Pichler-Tempsky. Austria.

Shu, Hong. (2016). Big data analytics: six techniques. Geo-spatial Information Science. USA and UK (Pp. 1-10). DOI: 10.1080/10095020. 2016.1182307

Srbljinović, Armano & Božić, Jasmina. (2014). Implications of the Sociology of Emotions for the Restoration of Social Order. Emotion Review. Vol 6 No 2. UK (Pp. 152-159). DOI: 10.1177/1754073913503371

Stark, Luke & Crawford, Kate. (2015). The Conservatism of Emoji: Work, Affect, and Communication. Social Media + Society. UK (Pp. 1–11). DOI: 10.1177/2056305115604853

Tarrant, Shira. (2016). The Pornography Industry: What Everyone Needs to Know. Oxford University Press. USA.

Tieszen, Richard. (1999). Mathematics. In Smith, Barry and Smith, David Woodruff (eds.). The Cambridge Companion to Husserl. Cambridge University Press. USA.

Torra, Vicenç; Karlsson, Alexander; Steinhauer, H. Joe, and Berglund, Stefan. (2019). Artificial Intelligence. In Said, Alan and Torra, Vicenç (eds.). Data Science in Practice, Studies in Big Data 46. Springer. Switzerland. DOI: 10.1007/978-3-319-97556-6_2

Turner, Jonathan H. (2009). The Sociology of Emotions: Basic Theoretical Arguments. Emotion Review. Vol. 1, No 4. UK (Pp. 340-354). DOI: 10.1177/ 1754073909338305

Veltri, Giuseppe. (2017). Big Data is not only about data: The two cultures of modelling. Big Data & Society. UK (Pp. 1-6). DOI: 10.1177/ 2053951717703997

Xu, Li Da & Duan, Lian. (2018). Big data for cyber physical systems in industry 4.0: a survey. Enterprise Information Systems. USA and UK (Pp. 1-22). DOI: 10.1080/17517575.2018.1442934

Žižek, Slavoj. (2019). The Relevance of the Communist Manifesto. Polity. UK and USA.

Descargas

Publicado

2020-01-14

Cómo citar

Alfaro Vargas, R. (2020). La onto-epistemología del Big Data. SAPIENTIAE, 5(2), 286-294. https://doi.org/10.37293/sapientiae52.03