User:LindaV123/sandbox

Datafication is the transformation of different aspects of human lives into computerised data. It refers to the quantification of a phenomenon to make it possible to tabulate and analyze it. According to Kenneth Cukier and Viktor Mayer-Schönberger, the prerequisites of datafication are the knowledge of how to measure and record what is measured, the right set of tools and the desire to quantify.

Mark Lycett points out that the term datafication can be explained by applying concepts of dematerialisation, liquification and density. Dematerialisation refers to the possibility to distinguish between informational aspects of a source and the physical world, liquification entails that the dematerialised information can be manipulated and shifted, whereas density „is the best (re)combination of resources, mobilized for a particular context, at a given time and place”.

Digitization and datafication

Digitization is a term that refers to converting “analog information into computer readable format", whereas datafication is a broader term that includes turning different aspects of human life into data. When information is datafied, it can be turned “into new forms of value”. For example, to digitize a text means to scan the pages, transforming them into digital copies. By using optical character-recognition software it is possible to datafy the digital image. Datafication provides that the digitized text is readable for humans and suitable for computers to analyze. Therefore, datafication makes the text indexable and searchable.

Datafication of private lives

Nowadays, various technologies make it possible for people to measure aspects of their lives that previously could not be quantified. Social media and communication platforms (for example, Facebook, Twitter, LinkedIn, WhatsApp, Skype) collect metadata and quantify such aspects of social life as friendships, professional networks, casual conversations, interests, preferences and emotions. This data, in turn, is “made accessible to third parties, be it fellow users, companies, government agencies, or other platforms”. For example, the companies DataSift and Gnip have bought access to the data from Twitter, hedge funds Derwent Capital and MarketPsych have analyzed datafied tweets in connection with investments in stock market, and many businesses examine tweets to evaluate customer feedback or effect of marketing campaigns.

Moreover, new wearable technologies have made it possible for individuals to quantify themselves by measuring, for example, their heart rate, sugar level, exercise, eating and sleeping habits, thus providing more extensive insights in individual’s health conditions and deeper understanding of the ways diseases form.

Datafication of business

In the business context, datafication implies the transformation of an organization into a “data-driven enterprise” which requires that the main business processes, strategies and decisions are made relying on data. Datafication can be applied to streamline business processes, boost organization’s financial performance, improve customer relationships and design new products and services. “The lowering costs of sensors, increased processing capacity and availability of low-cost bandwidth” provides that datafication moves into previously un-monitored business processes. For example, the increasingly detailed understanding of micropayments is changing financial services and has a great impact on supply chains. Moreover, datafication has also brought about the profession of data scientist – the person in the company that possesses analytical skills and business knowledge to extract insights from data.