Abstract The biggest threshold to understand scientific knowledge, as it is stored in heterogeneous datasets today, is not the general availability of data, but the lack of transparence of its meaning and how datasets interrelate on the conceptual level. Moreover the increasing availability of research data has made it necessary to deal with a 'deluge' of information also in archaeology. Terms like 'big data', a proposed '4th paradigm' or simply the propagation of a 'digital turn' are used to describe this development. In fact, the modalities of data storage and its publication on the Internet make it possible to overlook the inherent dependencies that are part of the process from data generation to retrieval. The strangely externalized matter that data driven research seems to be confronted with, even allows for the postulation of a 'new empiricism' - a point of view that fails to acknowledge the theoretical implications of the generation of datasets and their forms of storage, assuming that the sheer quantity of data has made scientific method obsolete. In my paper I will examine the epistemological framework of data structures used in archaeological research, showing their theoretical and research strategic implications. I will argue that the relationship between archaeological data and its scientific interpretation, as reflected in the existing data models, must be understood as constituents of specific ‘infrastructures of knowledge’. In consequence it is necessary to make scientific inference formally visible. The goal is the explication of semantic values embedded in the data structures and the mapping of provenance and inference. I will discuss whether this can be done through the implementation of existing ontologies or the development of specific micro ontologies, by presenting examples from the development of the Çatalhöyük Living Archive.
