Structure and Workplan
By the end of a five-year set up phase of DataPLANT, our goal is to have achieved the following:
Knowledgeable researchers in the field, all students, PhDs, postdocs and PIs have a clear understanding of data management in the domain of plant research and are committed to produce perfectly reusable data sets.
There is a well-established first-point-of-contact in all relevant regards for researchers to learn about data management, relevant standards and research workflows in fundamental plant science. This hub is the established link between community members for further standard evolvements, it is the entry point to search for data in wide contexts. It is the link of plant research into the NFDI and the connector of the discipline specific data sets to the whole scientific community.
There is a sustainable set of base level services available to the wider community to publish their data in a stable research data repository equipped with persistent identifiers.
There is a viable long-term access service to past research contexts shared with other consortia in the NFDI and the wider scientific community.
There is a search portal to make the provided research data findable according to the FAIR-principles.
We propose an organization of the necessary work into several closely coupled task areas, organized around plant researchers, and following a workflow-centric, bottom up approach. DataPLANT workplan
Task Area 1 - Standardization, Quality, and Interoperability
Task Area 1 will work towards developing the envisioned plant-research (meta)data standards. We believe that for an efficient standardization with respect to ensuring data quality and data/workflow interoperability, an integrative effort is needed that considers these aspects simultaneously through three work packages.
Standardization - DataPLANT builds on a large network of existing co-operations and projects within fundamental plant research to be leveraged to spur plant domain adequate standardization and norms. Thus DataPLANT focuses on the accommodation of the wide variety of necessary metadata and standards within the fundamental plant domain. Uniform standards and procedures as well as a jointly organized and technically distributed data management platform creates added value, both for the DataPLANT community as well as for other disciplines within the whole NFDI. The providers in the consortium can broaden the scope of their services and make use of the knowledge gained from service operation for various communities. Conversely, successful offers for the DataPLANT community can be transferred to other scientific communities via the NFDI cross-cutting activities. Thus, to foster reusability und long-term access to data sets, the archiving and repository landscape will be evaluated for existing approaches falling back to basic elements from the “Dublin Core” specification as a minimal stop gap solution. DataPLANT will expand and further harmonise existing ontologies and metadata initiatives and/or emerging standards. This includes ontologies, identifiers and interfaces, as well as the establishment of a flexible metadata schema for findability of data sets.
Quality - One of the main aims of DATAPlant is to provide FAIR data and workflows to the community that provides an added benefit. Hence, data quality and especially metadata completeness are of a high importance to safeguard not only FAIR data principle and access but also to be able to empower the community to mine data and to develop added value services.
Interoperability – to ensure maximal data (re)usability and to allow for meta-analysis and data aggregation, interoperability is a major issue that will be tackled by DataPLANT. Thus, DataPLANT will build on existing infrastructure providing unique identifiers, authorization and workflows where possible and re-use extant and accepted data formats. In addition, DATAPlant will together with its user base collaborate with third party providers to improve future data standards, services and workflows.
These efforts will be conducted to strengthen and coordinate standardization efforts in plant research-related data and workflow annotation and will be closely linked with other relevant NFDIs nationally, and e.g. ELIXIR, EOSC, EMPHASIS, iPLANT and MIAPPE internationally.
Task Area 2 - Software, Service, and Infrastructure
Task Area 2 is aimed at providing software tools, software services, and infrastructure services for (meta)data, and workflow creation, management, sharing, and evolution providing the basis for collaborative plant research. The Task Area will provide improvements to data and workflow management across the entire lifecycle of plant research (meta)data. The technical implementation of the NFDI DataPLANT is organized through this task area. The DataPLANT consortium must find answers to the challenges of current and future developments in the field and ensure long-term, productive access to research data. This includes an extension of competencies on all facets of data management as well as the implementation of concepts for sustainable, reproducible scientific methods. All activities described in the following sections rely on existing infrastructure brought in by the consortium.
Task Area 3 - Transfer, Application, and Education
Task Area 3 will focus on developing mechanisms for interaction and education with stakeholders (plant researchers) and community-building towards furthering collaborative research in plant biology. These efforts will be directed towards:
Provide a faceted support infrastructure combining on demand face-to-face consulting with a broad range of assistive services. We follow a holistic approach addressing several target groups including legal advice. Building on the successful Galaxy and ELIXIR education services and fully established training courses and channels, developing new training programs for specific user communities in data and workflow standards and management, data literacy, scientific data analysis, and computational methods, in the context of the to-be-developed specifications and infrastructures. This includes both education of young researchers as well as the ongoing qualification of researchers and practitioners in plant biology.
Building communities through active communication of developed standards, platforms and infrastructure resources. Comprehensive training of the plant research community through workshops and summer schools and providing open training material to support a guided data collection and curation and the recording of the complete data context. Application of the objectives to a bioinformatic research infrastructure.
Dissemination of the developed standards, software, and infrastructures at and beyond participating research centres through partnering in international communities.
Task Area 4 - Project governance
DataPLANT is designed to be user-centric, thus it requires specific measures for coordination, consensus seeking and the implemented organisational structures. Data champions and developers should be relieved of administrative tasks to a large extent and be able to concentrate on the implementation of their interests and the coordination of important issues. Thus, central objectives of the task area are:
Implement and adapt the planned governance and control structures for DataPLANT in order to reconcile the interests and ideas of the community and other stakeholders. There will be regular evaluations and if required - updates of the governance and control structures.
Together with the general NFDI and the other consortia there will be suitable business and operation models in place for sustainable operation of the identified core services.
This means developing communication and organisational structures that enable an effective exchange of information between the stakeholders involved and the wider NFDI community.
At the same time, processes for the comprehensive participation of user groups in corresponding decision-making processes are accompanied during implementation.
The goal is the early and comprehensive integration of all relevant research and interest groups into the processes in order to make strategic decisions and identify possible obstacles or risks at an early stage. In this context, service development with process and business modelling and the integration of external resources is also being promoted. In the overall view of the actors involved, the project positions itself as a specialist centre of bioinformatics around relevant research infrastructures70 . It moderates the processes necessary for the coordination of all participants by involving the entire NFDI and international structures. This includes the integration of existing or the development of new accounting models, for example in order to map third-party funding flows to resources used.