The term Big Data is commonly used to describe a range of different concepts: from the collection and aggregation of vast amounts of data, to a plethora of advanced digital techniques designed to reveal patterns related to human behavior. In spite of its widespread use, the term is still loaded with conceptual vagueness. The aim of this study is to examine the understanding of the meaning of Big Data from the perspectives of researchers in the fields of psychology and sociology in order to examine whether researchers consider currently existing definitions to be adequate and investigate if a standard discipline centric definition is possible. Methods Thirty-nine interviews were performed with Swiss and American researchers involved in Big Data research in relevant fields. The interviews were analyzed using thematic coding. Results No univocal definition of Big Data was found among the respondents and many participants admitted uncertainty towards giving a definition of Big Data. A few participants described Big Data with the traditional "Vs" definition-although they could not agree on the number of Vs. However, most of the researchers preferred a more practical definition, linking it to processes such as data collection and data processing.

Big Data has been described as a "one-size-fits-all (so long as it's triple XL) answer" [24] to solve some of the most challenging problems in the fields of climate change, healthcare, education and criminology. This may explain why it has become the buzzword of the decade. Big Data is a very complex and extensive phenomenon that has had fluctuating meanings since its appearance in the early 2010's [86]. Traditionally it has been defined in terms of four dimensions (the four V's of Big Data): volume, velocity,

Big Data and Internet and Communication Technologies (ICT) are being increasingly implemented in the healthcare sector. Similarly, research in the field of dental medicine is exploring the potential beneficial uses of digital data both for dental practice and in research. As digitalization is raising numerous novel and unpredictable ethical challenges in the biomedical context, our purpose in this study is to map the debate on the currently discussed ethical issues in digital dentistry through a systematic review of the literature. Four databases (Web of Science, Pub Med, Scopus, and Cinahl) were systematically searched. The study results highlight how most of the issues discussed by the retrieved literature are in line with the ethical challenges that digital technologies are introducing in healthcare such as privacy, anonymity, security, and informed consent. In addition, image forgery aimed at scientific misconduct and insurance fraud was frequently reported, together with issues of online professionalism and commercial interests sought through digital means.

Research ethics has traditionally been guided by well-established documents such as the Belmont Report and the Declaration of Helsinki. At the same time, the introduction of Big Data methods, that is having a great impact in behavioral research, is raising complex ethical issues that make protection of research participants an increasingly difficult challenge. By conducting 39 semi-structured interviews with academic scholars in both Switzerland and United States, our research aims at exploring the code of ethics and research practices of academic scholars involved in Big Data studies in the fields of psychology and sociology to understand if the principles set by the Belmont Report are still considered relevant in Big Data research. Our study shows how scholars generally find traditional principles to be a suitable guide to perform ethical data research but, at the same time, they recognized and elaborated on the challenges embedded in their practical application. In addition, due to the growing introduction of new actors in scholarly research, such as data holders and owners, it was also questioned whether responsibility to protect research participants should fall solely on investigators. In order to appropriately address ethics issues in Big Data research projects, education in ethics, exchange and dialogue between research teams and scholars from different disciplines should be enhanced. In addition, models of consultancy and shared responsibility between investigators, data owners and review boards should be implemented in order to ensure better protection of research participants.

The employment of Big Data as an increasingly used research method has introduced novel challenges to ethical research practices and to ethics committees (ECs) globally. The aim of this study is to explore the experiences of scholars with ECs in the ethical evaluation of Big Data projects. Thirty-five interviews were performed with Swiss and American researchers involved in Big Data research in psychology and sociology. The interviews were analyzed using thematic coding. Our respondents reported lack of support from ECs, absence of appropriate expertise among members of the boards, and lack of harmonized evaluation criteria between committees. To implement ECs practices we argue for updating the expertise of board members and the institution of a consultancy model between researchers and ECs.