Undeniably “Big Data” plays a crucial role in the ongoing evolution of health care and life science sector innovations. In recent years U.S. and European authorities have developed public platforms and infrastructures providing access to vast stores of health-care knowledge, including data from clinical trials and chosen patient information. The rising demand for access to data is to be expected given the mounting dependence of innovation on market data and market information. It is uncontentious to state that innovation is a competitive market activity reliant on information and knowledge, especially in the life science sectors where competitive innovation and research and development (R&D) resources are persistent considerations. For private actors, the like of pharmaceutical companies, health care providers, laboratories and insurance companies, it is becoming common practice to accumulate R&D data making it searchable through medical databases. This trend is advanced and supported by recent initiatives and legislation that are increasing the transparency of various forms of data, such as clinical trials data. As a result, researchers, companies, patients and health care providers gain access to an increased volume of personal and biological data. In light of these developments and rapid technical advances that have greatly facilitated the collection and analysis of information and knowledge from multiple sources, the protection of such data but also the access thereto has become ever critical to the innovation narrative. For the purposes of this paper this information is regarded as “big data,” i.e. not only because of the greater volume, but also for its’ increased variety, velocity, and veracity . Researchers can mine big data to identify the most effective treatments for particular conditions, to find 2nd and further medical uses, to detect patterns related to drug side effects or hospital readmissions, and gain other important information that can help patients, reduce treatment costs, channel R&D expenditure and influence innovations. It is expected that these developments will push the trend towards precision medicine and help industry and practitioners address pressing problems related to discrepancies in healthcare quality and escalating pressures to reduce and control healthcare expenditure. The vast prospects of Big Data and the gradual shift to more “personalized”, “open” and “transparent” innovation models highlight the importance of an effective and well-calibrated regulation, governance, and use of biological and personal data. At the same time, the translation of Big Data science into safe and efficient “real world” applications raise complex legal challenges relating to public-private research collaborations, data integrity, privacy, ethics and commercialization amongst others. One such challenge arises from the intersection between the Big Data narrative and intellectual property rights (IPRs). The interplay with IPRs comes into play when research needs to be translated into safe and efficient “real world” applications. Data analytics or data mining will often involve the copying of, or references to, information or databases, all of which might be protected by various forms of intellectual property rights in relevant jurisdictions. Where data is not owned or licensed the user will need to rely on an exception to IPR infringement to use data. This has given rise to fierce controversies between data “owners”, data researches, and entities that provide enabling technologies, large research infrastructures and standardization platforms . These tensions at the interface of Big Data and IPRs involve complex considerations relating to innovation economics, ownership, licensing and exceptions to IPRs. Seemingly there is convincing evidence that the current Intellectual Property regime needs re-calibration in certain areas to harness the full potential of Big Data in the health and life science sectors. Unfortunately, there seems to be much confusion and little agreement about the availability of IPRs and their legal effects among the multiple stakeholders in Big Data science. Against this background, this Chapter offers insights into challenges resulting from the intersection between the Big Data narrative and IPRs. Section 2 provides a brief summary of the most relevant IPRs for data-based life science research. Due to space constraints, we will concentrate on IPRs and related “sui generis” rights protecting commercially relevant data, rather than legislation protecting personal data integrity or regulating data transfer. This serves as the basis for section 3, which briefly discusses selected areas, where emerging tensions between IPRs and Big Data crystallize. Recognizing that the choice of how to address and interact with IPRs varies between different settings and technical applications, our concluding remarks in section 4 argue that these tensions need to be discussed and addressed on a case-by case basis