Critical questions for big data
The researchers of this paper have defined big data as technological, cultural and scholarly phenomenon. This paper analyses and interrogates six provocations of this phenomenon, its assumptions and its biases.
1. Big Data changes the definition of knowledge.
Big Data refers to computational focus in thinking and research. It also refers to the tools and procedures and very large data sets that are used to handle them and analyse them (Burkholder, 1992). Just as Henry Ford changed the way cars were made – and brought about the industrial revolution – Big Data emerged as a system of knowledge. It also has the ability to inform how we understand human associations and society. It is a profound change at the levels …show more content…
Plotting the data that is obtained from social media in the form of graphs and trying to analyse the relationships between people, does not give a clear and real picture. Just because a person spends more time with friends than with their spouse, does not mean that they consider their colleagues more important than their spouses. Two new types of social networks derived from big data are: articulated networks and behavioural networks. For certain line of inquiry, analysing data abstractions and still preserving context remains decisive.
5. Just because it is accessible does not make it ethical
Even when data is available on public domains, it gives the researcher no right to misuse the data. There is need for accountability. Institutional Review Boards (IRBs) – which emerged in 1970s took care of processes like consent appraisal and protection of privacy while overseeing research on human beings. Not all that is obtained from big data can go through the process of ethical clearance before it is used. But again, research ethics evaluation cannot be given a cold shoulder just because the data is available in the public domain.
6. Limited access to Big Data creates new digital …show more content…
Rather it is drive by government and industry which is channelled towards getting maximum value from the data. Which may in turn lead to a clear approach towards traffic planning, product design, or adverts that are targeted to a particular group. The authors also have made an observation that big data operationalization has some serious and broader implications.
Strengths of the paper: The researchers have presented the six interrogations in a systematic manner answering the questions that each of this provocations have asked. The authors have touched every aspect of big data. Starting from the definition of big data, to the quality of big data, to its accessibility and being ethical. They have been able to clearly point out the challenges that lie ahead for researchers in this field of big data. They have also used relevant examples to assert the points that the paper presents.
Weakness of the paper: As the researchers are trying to answer the six provocations, it is evident that the paper loses focus on a particular area of big data. This research work is more of a question and answer sheet which limits the research to the six areas mentioned in the
The researchers of this paper have defined big data as technological, cultural and scholarly phenomenon. This paper analyses and interrogates six provocations of this phenomenon, its assumptions and its biases.
1. Big Data changes the definition of knowledge.
Big Data refers to computational focus in thinking and research. It also refers to the tools and procedures and very large data sets that are used to handle them and analyse them (Burkholder, 1992). Just as Henry Ford changed the way cars were made – and brought about the industrial revolution – Big Data emerged as a system of knowledge. It also has the ability to inform how we understand human associations and society. It is a profound change at the levels …show more content…
Plotting the data that is obtained from social media in the form of graphs and trying to analyse the relationships between people, does not give a clear and real picture. Just because a person spends more time with friends than with their spouse, does not mean that they consider their colleagues more important than their spouses. Two new types of social networks derived from big data are: articulated networks and behavioural networks. For certain line of inquiry, analysing data abstractions and still preserving context remains decisive.
5. Just because it is accessible does not make it ethical
Even when data is available on public domains, it gives the researcher no right to misuse the data. There is need for accountability. Institutional Review Boards (IRBs) – which emerged in 1970s took care of processes like consent appraisal and protection of privacy while overseeing research on human beings. Not all that is obtained from big data can go through the process of ethical clearance before it is used. But again, research ethics evaluation cannot be given a cold shoulder just because the data is available in the public domain.
6. Limited access to Big Data creates new digital …show more content…
Rather it is drive by government and industry which is channelled towards getting maximum value from the data. Which may in turn lead to a clear approach towards traffic planning, product design, or adverts that are targeted to a particular group. The authors also have made an observation that big data operationalization has some serious and broader implications.
Strengths of the paper: The researchers have presented the six interrogations in a systematic manner answering the questions that each of this provocations have asked. The authors have touched every aspect of big data. Starting from the definition of big data, to the quality of big data, to its accessibility and being ethical. They have been able to clearly point out the challenges that lie ahead for researchers in this field of big data. They have also used relevant examples to assert the points that the paper presents.
Weakness of the paper: As the researchers are trying to answer the six provocations, it is evident that the paper loses focus on a particular area of big data. This research work is more of a question and answer sheet which limits the research to the six areas mentioned in the