BioMedData Deliverable D3.5 Establish monitoring of adherence to data management routines at Norwegian life science research infrastructures
Creators: name: Fatima, Nazeefa
name: Bösl, Korbinian
name: Bianchini, Federico
name: Fritz-Wallace, Katarina
name: Xian, Hu
name: Sjøbakk, Torill Eidhammer
name: Torma, Michal
Publisher: name: Zenodo
Year: 2024
Subjects: subject: Data processing
subject: Research Data Management
subject: Data Management
subject: Metadata
subject: Microscopy
subject: Microscopy Imaging
subject: Genomics
subject: Proteomics
subject: Norwegian e-Infrastructure for Life Sciences
subject: High Throughput Sequencing
subject: High Throughput Screening

description: Research Infrastructures (RIs) play a critical role in facilitating scientific advancements through the provision of specialised services, resources, and technologies. Regularly monitoring outputs that are a direct result of these services, such as sample depositions to repositories, publications generated from projects, and other data management routines are important for a multitude of reasons. First, it ensures data quality and integrity; regular monitoring helps in identifying potential discrepancies in the data, thereby enhancing its precision and reliability. Secondly, it assists in evaluating the performance and productivity of the facilities; tracking allows to collect key metrics that in result helps to assess impact of data management services provided by the infrastructures. Monitoring data management routines also aids in demonstrating accountability and transparency, which allows to gain trust from existing and potential stakeholders including funding bodies. In this report, we focus on monitoring of data management routines at Norwegian RIs and their core facilities and highlight strengths and weaknesses, in the context of the life sciences ecosystem and the adoption of metadata.

 Metadata adoption is crucial for ensuring interoperability and reusability of datasets, which are central to the FAIR data principles (Findable, Accessible, Interoperable, and Reusable). However, the onus for creating, collecting and managing metadata is usually on researchers/users that may lack the necessary support and knowledge. This can lead to inconsistencies and reduced data quality, making monitoring more critical to maintain data integrity.

 We highlight the importance of ELIXIR's deposition databases that facilitate API-based monitoring, which can streamline the process of tracking data submissions and usage across multiple platforms. We showcase how this can work in practice (see sections on NAPI and NorSeq, pages 10-15). However, it is worth noting that the lack of a specific repository or centralised system for endpoint monitoring can be a hindrance - without such a system, it's challenging to provide comprehensive oversight and ensure compliance with standards.

 In addition to tracking data and metadata, we believe the implementation of a national strategy is necessary to uniquely identify and connect projects, institutions, funders, and researchers. Persistent Identifiers (PIDs) such as Digital Object Identifiers (DOIs) for publications and datasets, enable tracking of research outcomes with a higher accuracy. However, some domain-specific repositories currently lack PID support, which hampers the ability to effectively monitor the dissemination and impact of research. Similarly, there is currently no consistent national use of PIDs for researchers (e.g. ORCIDs) and institutions (e.g. Research Organisation Registries (RORs)) for data deposition.

To address these challenges, we believe there is a need for systematic efforts to enhance metadata quality and to incorporate PIDs into all facets of the research data lifecycle. This would entail educating and providing resources to RI users, considering and establishing suitable toolkits and standards for monitoring and reporting, and developing policies that mandate adherence to these practices. Properly addressing these elements will significantly improve services as well as the transparency and quality of data generated and processed at the RIs, ultimately contributing to the progress of Norwegian life science research data management.