scholarly journals Big Data as “Practical Ontology”: The Ontotheology Underlying the Interpretation of Reality as Data

2021 ◽  
Vol 16 ◽  
pp. 12-23
Author(s):  
Guilherme Silva ◽  
Tales Tomaz
Keyword(s):  
Big Data ◽  

The article discusses the emergence of a “practical ontology” in some of the most triumphalist discourses on Big Data. Such an interpretation can be drawn from the Heideggerian critique of ontotheology, a term he used as an equivalent to Western metaphysics. Following his perspective, the article argues that the reduction of reality to data, as in many Big Data discourses, means putting functionality as the fundamental aspect of beings, hence – the idea of a practical ontology. The Heideggerian critique of ontotheology, however, not only makes the ontological core of Big Data’s practical discourses more transparent but also points out the theoretical limits of that ontology and, furthermore, of most discourses around Big Data. It could be said that eventually Big Data’s practical ontology conceals the very moment of unconcealment of beings as data, undermining a proper comprehension of its object of analysis – the data.

Big Datais a buzzword affecting nearly every domain and providing different set new opportunity for the development of knowledge discovery process. Although it comes with challengeslike abundance, extensiveness and diversity, timeliness and dynamism, messiness and vagueness, and with an uncertainty as all the data generated does not relates to any specific question and can be associated with another process or activity. To address these challenges are certainly cannot be handled by the traditional infrastructure, platforms and frameworks. New analytical techniques and high performance computing architecture came into picture to handle this explosion. These platforms and architecture are giving a cutting edge to the Big Data Knowledge Discovery process by using Artificial Intelligence, Machine Learning and Expert systems. This study encompasses a comprehensive review of Big Data analytical platforms and frameworks with their comparative analysis. A Knowledge Discovery architecture for Big Data Analytics is also proposed while considering the fundamental aspect of gaining insights from Big Data sets and focus of this analysis is to provide the open challenges associated with these techniques and future research directions.


ASHA Leader ◽  
2013 ◽  
Vol 18 (2) ◽  
pp. 59-59
Keyword(s):  

Find Out About 'Big Data' to Track Outcomes


2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.


2017 ◽  
Vol 225 (3) ◽  
pp. 287-288
Keyword(s):  

An associated conference will take place at ZPID – Leibniz Institute for Psychology Information in Trier, Germany, on June 7–9, 2018. For further details, see: http://bigdata2018.leibniz-psychology.org


PsycCRITIQUES ◽  
2014 ◽  
Vol 59 (2) ◽  
Author(s):  
David J. Pittenger
Keyword(s):  

2015 ◽  
Author(s):  
Kirsten Weir
Keyword(s):  

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