Data Standards

The life sciences have been revolutionized by technical advances in experimental methodology. Nowadays, researchers not only generate huge amounts of data in a single experiment but the types of data they are collecting have also become highly divergent. Thus, biology is making the transition towards a data science and a ‘life cycle’ view of research data. Researchers now face the challenges associated with handling large amounts of heterogeneous data in a digital format. Some of these challenges include consolidating the data; translating it into a format that can be read by complex analysis pipelines; determining the most suitable analysis parameters; and making the data publicly available for reuse. There is growing evidence to suggest that many published results will not be reproducible over time. Thus, robust data management and stewardship plans are essential to ensure the long-term sustainability of digital data.

The Findable, Accessible, Interoperable, and Reusable FAIR data initiative was created in 2016 to address these issues by providing a framework for defining the minimum elements required for good data management. However, adopting FAIR principles is not straightforward as it requires knowledge of metadata, schemata, protocols, policies, and community agreements. Moreover, the lack of exactness in the original FAIR principles means that is a lack of clear guidelines regarding implementation of different elements. Even when robust solutions exist, data providers may have to choose among different and not necessarily compatible implementations.

The organ on chip research environment is one area where FAIR concepts are needed, but are yet to be incorporated. Organ on chip seeks to simulate the activities, mechanisms and physiological response of organs or organ systems. A major data challenge is that organ on chip research collects huge amounts of highly diverse types of data that need to be integrated to understand the mechanics of an organoid design. Currently, no standards exist in the field and, in addition to the challenges of integrating the data, there is also the problem of how to compare results among different research groups. For example, there are several Liver on Chip designs, but no way to compare performance.

Within the Hybrid Technology Hub Organ on Chip centre of excellence at the University of Oslo, we are developing the Global Accessible Distribution Data Sharing (GADDS) platform, an all-in-one cloud platform to facilitate data archiving and sharing with a level of FAIRness. GADDS uses decentralization technologies and a tamper proof blockchain algorithm as a metadata quality control. By providing a browser-based client interface, GADDs can simplify the implementation of FAIRness in the data collection and storage process. The platform is specifically developed for the Organ on Chip environment but has general application in any data collection and integration process requiring a level of data FAIRness. GADDS integrates version control, cloud storage and data as an all-in-one platform.