Source: Vishal Krishna/yourstory.com (27 June 2016)
Big Data are mostly discussed for two reasons. The first reason is whetherthose data that include personal information are safe or not. The second one is about how the data that are provided are used.
To begin with, I need to clarify what I am talking about when I use the term ‘Big Data’.CERN also uses Big Databut with another meaning for example. In this post I refer to the specific kind of Big Data that include private information and are mostly generated by humansthrough social media platforms or records of mobile phone lines.
As we approach the issue of ethics in media reporting evidenced by distorted information and unreliability of the information they present, this issue can create several questions in our minds of where the media is taking us as a society in general. The major question that remains strongly in our minds is, do we still trust the media reporting?
My attention in this post is focused on emphasizing the need for reliability of the information presented to us, majorly informed of statistics by the media. This is because lately the public trust has been abused by unethical and unreliable media reporting. With this focus it is considered that statistics are meant to provide stable reference points to provide an objective judgment but this has not been the case lately, rather they provide misleading false information.
What does ‘development’ mean to data scientists, and how does that determine what data science can achieve within the field of international development? This essential question has been raised, in relation to certain D4D (Data for Development) projects, by some experts who further state:
Data science conducted with the aim of informing development policy must, by definition, involve an understanding of the policy area in question, and importantly the analysis must be combined with understanding of the local context. Without these characteristics, research only informs the field of data science rather than development policy.
(Taylor & Schroeder, 2015, pp. 508 & 514)
‘Data science must involve an understanding of the policy area and the local context’. Here is an interesting statement to begin with. So, let’s start with a video from the Geospatial Revolution Project.