With the advent of digital technologies, awareness of media is acquiring crucial importance. Media literacy, information literacy and digital literacy are the three most prevailing concepts that focus on a critical approach towards media messages.This article gives an overview of the nature of these literacies, which show both similarities to and differences from each other. The various contexts of their functioning are outlined and additional literacies are mentioned. Especial attention is given to the question of the blurring line between media consumers and producers.

This paper describes data literacy and emphasizes its importance of data literacy. Data literacy is vital for researchers, who need to become data literate science workers and also for (potential) data management professionals. Its important characteristic is a close connection and similarity to information literacy. To support this argument, a review of literature was done on the importance of data, and the data-intensive paradigm of scientific research, researchers' expected and real behaviour, the nature of research data management, the possible roles of the academic library, data quality and data citation, Besides describing the nature of data literacy and enumerating the related skills, the application of phenomenographic approaches to data literacy and its relationship to the digital humanities have been identified as subjects for further investigations.

Purpose – The role of data literacy is discussed in the light of such activities as data a quality, data management, data curation, and data citation. The differing terms and their relationship to the most important literacies are examined. The paper aims to discuss these issues. Design/methodology/approach – By stressing the importance of data literacy in fulfilling the mission of the contemporary academic library, the paper centres on information literacy, while the characteristics of other relevant literacies are also examined. The content of data literacy education is explained in the context of data-related activities. Findings – It can be concluded that there is a need for data literacy and it is advantageous to have a unified terminology. Data literacy can be offered both to researchers, who need to become data literate science workers and have the goal to educate data management professionals. Several lists of competencies contain important skills and abilities, many of them indicating the close relationship between data literacy and information literacy. It is vital to take a critical stance on hopes and fears, related to the promises of widespread ability of (big) data. Originality/value – The paper intends to be an add-on to the body of knowledge about information literacy and other literacies in the light of research data and data literacy.

Data governance and data literacy are two important building blocks in the knowledge base of information professionals, involved in supporting dataintensive research, and both address data quality and research data management. Applying data governance to research data management processes and data literacy education helps in delineating decision domains and defining accountability for decision making. Adopting data governance is advantageous, because it is a service based on standardised, repeatable processes and is designed to enable the transparency of data-related processes and cost reduction. It is also useful, because it refers to rules, policies, standards; decision rights; accountabilities and methods of enforcement. Therefore, although it received more attention in corporate settings and some of the skills related to it are already possessed by librarians, knowledge on data governance is foundational for research data services, especially as it appears on all levels of research data services, and is applicable to big data. Keywords Data-intensive research, data librarian, data governance, data literacy, research data services On this background, a review of the literature was done in order to identify and examine significant constituents of the knowledge base that is crucial for information professionals, involved in supporting data-intensive research. The first constituent is data governance (DG), which is extensively dealt with mainly in the corporate (business) sector, and is explored in this paper with the belief that bringing it into the picture will enable better research data services. The second one is data literacy, about which there is a massive body of literature, among others in the form of review articles (MacMillan, 2014; Koltay, 2015a, Koltay 2015b). Data literacy is closely related to research data services that include research data management (RDM). As the concept of RDSs itself and data literacy education are still evolving, their relationship to data governance requires examination that may lead to some kind of synthesis. The management of data quality is also inspected in order to determine to what extent it plays the role of an interface between these two constituents. Accordingly, this writing is built on three core terms. Data governance can be defined as the exercise of decision-making and authority that comprises a system of decision rights and accountabilities that is based on agreed-upon models, which describe who can take what actions, when and under what circumstances, using what methods (DGI, 2015a). While the various definitions of data literacy will be discussed below, we define it here as the ability to process, sort, and filter vast quantities of information, which requires knowing how to search, how to filter and process, to produce and synthesize it (Johnson, 2012). This definitions is in accordance with the idea, expressed by Schneider (2013), that the boundaries between information in information literacy and data literacy are blurring, because these boundaries never...

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