The future of data infrastructures

In his opinion, we can stimulate and accelerate medical innovation by investing in open science and data sharing. He firmly believes this will not only improve our understanding of the cause of disease and its progression, but also help in predicting patient outcomes and even prevent certain diseases from occurring.

Frank Miedema is involved in national coordination of the Dutch research infrastructures. We asked him to share his vision on research infrastructures and data sharing. 

Producing data is one of the key tasks of researchers in the Life Sciences field. Effective use of these data is critical to improving our understanding of health risks and health benefits. Over the last 6-7 years, we started to realize that combining data sets from different sources is necessary to perform high-quality research. A holistic approach is needed. Currently, different research organizations, departments and laboratories produce their own data. If we succeed in making this information accessible to the scientific community as a whole, we can accelerate research and improve patient outcomes. There are already different research infrastructures, such as BBMRI-NL, LifeLines, EATRIS and TraIT, that are working to make data accessible. But we realized that we can really create more value when we combine all these initiatives. This was achieved some years ago under the NFU Data4lifesciences initiative, which is now part of the national plan for life science infrastructures: Health-RI.

The importance of knowledge sharing is widely acknowledged for its societal and financial benefits. Data generated in research projects has cost considerable money and manpower, and if these data were reusable, money and effort would be saved by better capitalizing on research that has already been performed. This is a win-win situation for everybody, definitely for patients.

However, to make data widely accessible there are several hurdles to overcome. One of these hurdles is making the data user-friendly. Currently, each research organization has its own policy. To make the data compatible we not only need to align each other’s efforts, we also need to align with international initiatives. The standards for data must be FAIR: Findable, Accessible, Interoperable and Reusable. We therefore need to develop a common approach, for example, to data storage, research protocols, standardization of processes, data exchange technology, etc. This means coordination in projects is crucial.

Another important aspect of such data infrastructures is patient participation. We need to always keep the patient perspective in mind when developing new infrastructures. That’s why collaboration with patient organizations is essential. Ethical questions about privacy policies should also be taken into account. How can we connect data without compromising patient privacy?

Health-RI is an initiative, involving many players in the Life Sciences, aimed at achieving coordination of initiatives at the national level. Its objective is to develop a national research infrastructure with a focus on societal impact: more value and impact from our research. With Health-RI we want to establish a focal point for all health-related data and combine different expertise. Within this initiative, we want to facilitate the combination of biological, molecular and clinical data with data related to external factors such as people’s environment, socioeconomic group, nutritional data and lifestyle. This will give us insights into all factors involved in a healthy life, giving us a more complete picture and the opportunity to understand different health risks.

To stimulate data sharing, a cultural shift is necessary in academia. Currently, universities mainly evaluate the output of researchers based on their publications. If we want to stimulate researchers to share data, we have to think about different incentives that allow for data sharing. If publications remain the main measure of success, there is no incentive for scientists to share their data. This means we need to make the evaluation of scientists’ impact more inclusive, taking into account different results and products from their academic work. In that way, we can better incentivize and reward actions that accelerate science and increase societal impact by sharing data.