ABSTRACT
Our scientific culture is driven by the need for constantly producing headlines and getting recognized by scoring high in measures like impact factors for journals and H factors for individuals. However, this has led to very inefficient usage of resources by not encouraging sharing and the reuse of data from others. Additionally, there are areas where individuals or even individual groups are not able to provide all evidence to come to conclusive results. One of these areas is toxicology and the related topics of risk assessment and especially nanosafety. The paradigm shift from an animal-experiment-based to a mechanistically-driven science based on in vitro and in silico studies made it necessary to combine data from many different experiments to describe hazard, risk and, for nanomaterials extremely important, physicochemical characterization into integrated approaches to testing and assessment (IATA). Large EU funded consortia developing such approaches clearly demonstrated that early, well documented data sharing is the only possible way to cover this complexity and validate the approaches to achieve regulatory acceptance.
Many sophisticated systems for data management exits developed by companies, infrastructure or individual research projects and initiatives like NanoCommons, ELIXIR and now the European Open Science Cloud (EOSC) are bringing these together into larger and larger data platforms spanning multiple communities. However, this is only one part of the story. Researchers generating the data are still reluctant to share their data fearing to lose their competitive advantage. Additionally, collecting a sufficient amount of metadata to describe the data to be understandable by others is a time consuming task and is often postponed until the last minute. In this talk, I will present how a designated data shepherd can support the data providers and data curators to prepare the datasets for upload, discuss with database managers and management/sharing tool developers on how to best support the generation, annotation and upload, and generate a clear legal and ethics framework to remove sentiments on losing control and intellectual properties. In a forthcoming paper [1] the data shepherd is defined as “an enhanced version of a data steward, who not only oversees the data management, handling and quality control processes, but can communicate in a clear and simple language with all parties and resolve any misunderstandings”.
[1] Metadata stewardship in nanosafety research: community-driven organisation of metadata schemas to support FAIR nanoscience data, Anastasios G. Papadiamantis, Frederick C. Klaessig, Thomas E. Exner, Sabine Hofer, et al., in preparation.
