 The emergence of systems biology and synthetic biology in the 21th century is to a large extent driven by the development of techniques and strategies for producing, digitalizing, collecting, disseminating, and standardizing data. A first step in these research practices is often to consult online databases or bio-ontologies that are used for data sharing, data integration, annotation, and curation of experimental datasets (Leonelli 2016). For instance, the search for network motifs  (Section 1.1.1)  started with the development of network models based on data downloaded from the database RegulonDB as well as other sources (Shen-Orr et al. 2002). Numerous databases, bio-ontologies, and software tools have been developed, emphasizing the ideals of Open Data and large-scale collaborative efforts (Leonelli 2013). These practices raise questions as to whether some projects within systems and synthetic biology may be described as ‘big science’ (Vermeulen 2010), and about the epistemic and social implications of data-intensive research practices and collaborations.