When more and more data became available, some researchers were convinced that ever greater questions would become answerable in the immediate future, and that theories and hypotheses would no longer be necessary. Big Data would simply uncover all sorts of new information, and subsequently provide people with new knowledge. According to Melvin Wevers from the University of Amsterdam, this "holy grail" of Big Data is not nearly as fantastic as many people think. The archives that are being used as data display and (re)produce the world from specific perspectives, and incorporate particular ideological beliefs. For instance, one of the research projects he worked on showed how gender biases affected the content of newspapers over a period of forty years. Furthermore, historical archives are often incomplete and imbalanced — they, for instance, contain relatively much information about white elites, and little or no information about other groups of people —, and the tools, methods and approaches that are used to access and analyse these archives often neglect to consider the temporal dimension of the data. In that sense, Wevers believes that the field of History might be able to learn scholars from other disciplines how to think more critically about archives, historical data and the spatial and temporal dimensions of their research.