The traditional view of data, information, and knowledge as a hierarchy fosters an understanding of information as an independent entity with objective meaning-that while information is tied to data and knowledge, its existence is not dependent upon them. While traditional conceptions assume a static nature of information, expressed by the equation information = data + meaning, we have argued that this understanding is based on an ontologization of an entwined process of sense making and meaning making. This process starts from the recognition of a pattern that is interpreted in a way that influences our behavior. At the same time, the process character of meaning making makes us aware of the fact that this ontologized hierarchy is in fact an interwoven process. We conclude that the phenomenological analysis of this ontologization that makes into being data, information, and knowledge has to go back to this process to reveal the essential underlying dependencies.The traditional view of the relations between data, information, and knowledge is often described as a data-informationknowledge hierarchy (Rowley, 2007). It sees information roughly as data plus meaning and knowledge as information plus context. This idea of hierarchy recently reappeared in Floridi's (2009) information concept, where information is defined as comprising sets of well-formed (i.e., syntactically precise) and meaningful data that has a truth function. Meanwhile, others (Machlup, 1984a;Tuomi, 1999) have raised the question whether this hierarchy really makes sense, because the understanding of data is a process that depends on knowledge-in fact, data, information, and knowledge can be "said to be a specific type of each of the others, or an input for producing each of the others, or an output of processing each of the others" (Machlup, 1984b, p. 647). We want to address this question by examining the processes