Virtual exchange between NFDI4BioDiversity and DataPLANT

Envisioning the collaboration within all NFDI-consortia, members of NFDI4BioDiversity and DataPLANT met at the beginning of the new year for a virtual exchange to discuss cross-cutting issues such as standardization, teaching and qualification, common base level infrastructure, the role of data experts and support in research data management, sustainable financing and consortia extension strategies and common strategies of life sciences-related NFDI consortia.

The conversation on the challenging topic of standardization made the common vision clear that the goal is rather to help users to find existing standards than developing new ones. The objective of DataPLANT is to allow researchers in the lab a convenient ontology extension without having to contact standardization committees. Both consortia will cooperate on standards development in the field of plant biology and tools in the future.

Furthermore, NFDI4BioDiversity convinces with its expertise in the field of data training of junior scientists, even if its no concrete formation yet. However, we are sure that with combined efforts a great concept for a professional training of so-called "DataStewards" can be created and implemented.

Both consortia, like others in the field of life sciences, depend for their infrastructure on the de.NBI cloud, which provides compute and storage hardware in various forms on which to execute workflows and manage (large scale) data sets. The long term perspective of this resource in respect to the NFDI still needs to be refined.

When considering a sustainable NFDI, it came up that a central HR pool would be advantageous for a proper support of new participants. The community could make use of it if supported by the DFG through future grant applications. For the moment, this idea remains a conceptional construct that needs to be substantiated after consultation with the  appropriate contributors.

In any case, the meeting has encouraged to tackle difficult topics jointly and helped to identify the respective counterparts within both consortia.

We look forward to a follow-up exchange.


Weihnachtsgrüße 2020


DataPLANT participates in the CfP for the "E-Science-Tage 2021: Share Your Research Data"

DataPLANT submitted three proposals following the Call for Papers of the "E-Science-Tage 2021: Share Your Research Data" scheduled for beginning of March in Heidelberg. The consortium plans to participate in the workshop suggested by the NFDI directorate to present the fundamental plant research community as part of the future research data management landscape. Such an integrated RDM landscape and services enables reproducible research, the linking of interdisciplinary expertise, the sharing of research for comparison and integration of different analysis results and metadata studies, taking advantage of the immense additional knowledge gained from them. Additionally, we suggested a short paper on the DataPLANT data steward model, as a core element of a holistic strategy for managing research data in the field of plant research. Research groups will profit from direct support in their daily tasks ranging from data organization to the selection of the proper tools, workflows and standards. Data stewards play a special hinge role between service providers, individual researchers, groups and the wider community. They also help bridging the gap between researchers and technical systems. The coordinated deployment of data stewards supports the adherence to good scientific practice among the research community.

Following the Kick-Off Task Area 2 "Software / Services" we started to draft an outline for the Annotated Research Context (ARC) as a starting point for experiments. An ARC  captures the complete research cycle in a structured way, meeting the FAIR requirements whilst trying to mimic the way an  individual researcher experimentsworks. ARCs are self-contained and include assay and /measurement data, workflows and computation results, accompanied by metadata in one package. Their structure allows full user-control over all metadata and facilitates usability, access, publication and sharing of the research. Thereby, ARCs are a practical implementation of existing standards leveraging the advantages of the “ISA model”, “research crates” and the “Common Workflow language”. The ARC concept relies on a structure that partitions assay, workflow and results for granular reuse and development. Assays cover biological, experimental and instrumental data including its self-contained description using the ISA model. Similarly, workflows describe all digital steps of a study and contain application code, script and/or any other executable description of an analysis providing the highest degree of flexibility for the scientists.