Abstract:

This paper highlights the main elements of a doctoral research regarding the importance of data, datasets and interconnectivity of data for a functioning Machine Learning (ML) and Artificial Intelligence (AI). We have reached a decade in which new technologies have taken over important roles in our private and business lives. Not only in terms of strategic decision-making processes for big market players but also in our private lives. Siri might tell us based on our schedule that we should leave earlier today and take an umbrella with us, as traffic is bad today and the weather forecast says that it is going to rain (Stradigi.ai 2019).

All that is not based on magic, it is based on logical decision-making processes with well-structured and interconnected information leading to actions as the one mentioned-above. These aspects which all aim to facilitate the user’s everyday life are usually supported by devices as mobile phones, during chats or phone calls by bots or by software and applications as Facebook or Instagram with face recognition software (Kurzmaier, F. 2018).

However, the fundamental basis for a functioning bot, face recognition software or even an autonomously driving car, as well as Artificial Intelligence is data; well maintained, accurately monitored, updated, clear and well-organized data or datasets. This research paper is founded on extensive review of existing literature from professional associations, recognized publishers and recent studies conducted by experts and journals.  The main objective of this study is to highlight the importance of data and datasets to establish the necessary basis for a well-working ML and AI.