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The growing role of research data and the rise of open science has also led to a demand for data literacy, which also serves managing, critically sharing and reusing research, business and citizen data. Focusing on these areas, this paper presents the characteristics of information literacy and data literacy, including their critical versions approaches. [ABSTRACT FROM AUTHOR]

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Data science is an interdisciplinary field that draws on the ideas and tools of many disciplines and varied professions. Data scientists may work as data analysts, or data engineers. We also can speak about vertical and horizontal data scientists. Data science education requires a richly layered system of relationships that are not just useful mechanisms, but also tools for navigating data as social text. Library and information science (LIS) overlaps significantly with data science, but data science is (at least for the time being) not standardised, because it often demands personalised, exploratory solutions. At the same time, data science offers new methods and practices for data librarianship that draw on the core values, ethics, skills and professional knowledge of general librarianship. Computational thinking, a common way of human problem solving, is one of the increasingly prominent competencies of data literacy that is an important part of both disciplines. The ideas that characterise our thinking about data science are linked not only to the cultivation of science, or commercial goals, but also to active and informed citizenship and action, which is also one of the reasons for the emergence of critical data literacy. [ABSTRACT FROM AUTHOR]

It is not only the commercial sector that benefits from the data boom since there is an increasing number of non-profit initiatives and governmental measures that focus on data collected from civil society. In my publication I intend to illustrate the different contexts of data awareness: I will start by analysing data protection and privacy, then I will review research that has been exploring issues of privacy. For us to understand the scale that data awareness is measured on, we need to acquaint ourselves with the two extremes: namely, international initiatives aimed at triggering the engagement of civil society in solving social issues or problems by providing their personal data, and researching the negative implications that deter consumers from providing their personal data. Both are important. Besides geographical, cultural, economic and historical factors, sharing behavioural information can be influenced by the extent to which companies, governmental and professional organisations in a given country prepare their citizens for the digital revolution. So I will also provide an overview of how much authorities, civil society and professional organisations in Hungary deal with the challenges of a changing world. [ABSTRACT FROM AUTHOR]