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The main objective of this deliverable is to provide resources that can assist life sciences researchers and data stewards in creating reference Data Management Plans (DMPs) for their research projects. The resources provided in this deliverable are intended to promote good research data management practices across the EU research landscape. To achieve this objective, a range of activities were undertaken, with a particular focus on the needs of the different domains covered by the demonstrator use-cases. In order to create these resources, the RDMkit pages were extended to include domain-specific information, which can be used as a reference when developing DMPs for different research projects. These pages fall under the "Your Domain" category and provide specific information on the data management needs and considerations for each domain. They also highlight challenges that are specific to each domain, such as data types, species, or areas, and offer solutions and considerations to overcome these challenges. In this deliverable, the RDMkit page for the Toxicology data demonstrator use-case was completed and added to the existing RDMkit pages for the other demonstrator use-cases. Additionally, a new Tool Assembly was added to the RDMkit corresponding to the Plant Sciences demonstrator use-case, covering the entire life cycle of experimental plant phenotyping data. In addition, the general Knowledge Models (KMs) of the Data Stewardship Wizard (DSW) were adapted to address the specific DMP questions needed for each demonstrator use-case. The DSW is a collaborative tool that enables data stewards and researchers to efficiently create DMPs for their research projects and it is designed with a hierarchical KM that guides users through the creation of DMPs. Since the relevant information for DMPs can vary across different domains, these KMs can be modified to contain the information relevant for each demonstrator use-case. For this deliverable, special focus was put on two of the demonstrator use-cases, namely Toxicology and Epitranscriptomics data. Additionally, related to the Human Data use-case, separate efforts are underway to enhance the sensitive data section of the KM system to ensure the proper management of such data. The improvements and new question suggestions that were found during these sessions were incorporated into the DSW KM by the DSW team. Furthermore, DMP templates were created in DSW for the demonstrator use-case using two standard approaches: creating a KM or a project template (PT). When creating a PT, a set of answers is saved and can be used to generate a partially pre-filled questionnaire for a new project. In the ideal case scenario, the two methods can be used together to provide domain-specific recommendations by answering questions that better reflect a scientific domain, such as metadata standards. In conclusion, this deliverable provides several valuable resources for life sciences researchers and data stewards, including extended RDMkit pages, customised DSW KMs, domain-specific DMP templates, and a new KM for creating DPIAs. These resources are designed to encourage good research data management practices across the EU research landscape, ensuring that valuable research data is effectively managed before, during, and after a project.

There is a growing need for a post-graduate Data Steward curriculum in Norway due to the increasing demand for professionals with expertise in managing and curating data in both academia and industry. Many job advertisements for data steward positions require specialised knowledge in scientific fields, as well as a range of other skills related to policy, research support, and infrastructure. BioMedData is working to address this need by developing programs and initiatives to support the education and professional development of data stewards in Norway. These efforts aim to equip individuals with the necessary skills and knowledge to effectively manage and utilise data in a variety of settings, thus contributing to the advancement of research and innovation. This curriculum is the first draft for a post master or PhD certification to bring the additional necessary data stewardship skills to professionals with relevant domain knowledge in a targeted and flexible approach., Funded by the Norwegian Research Council as Forskningsinfrastruktur 295932

This work was performed by ELIXIR-Norway and Sigma2 in the context of BioMedData (RCN INFRA 295932), the ELIXIR2 (RCN INFRA 270068 ), the Centre for Digital Life Norway II (RCN 320911) and the EOSC-Nordic (EU H2020 857652) project, enabled by an advance user support agreement. The original ambition was to enable two use cases: Import of information provided by the user as answers to questions in different templates from one tool to another through an API to enable downstream processing Import of templates/questionnaires from on tool to another While use case 1 could be enabled through this exploration, we encountered major challenges on use case 2 which were not solvable within the frame of this work.

This webinar on the 31th of January (13.00 CET) from ELIXIR Norwa provides you with information on Open Data and Data Management requirements for research applications to the Research Council of Norway (RCN) call for proposals with deadline February 8th. For projects funded by RCN open science is now one of the assessment criteria and all funded projects must assess the need for a Data Management Plan. In this webinar we will highlight the RCN requirements for Open Data and Data Management from a Life Science perspective and provide a short introduction to the Data Management Planning tool "Data Stewardship Wizard" by ELIXIR Norway. Show notes: ELIXIR Norway RDMkit National strategy on access to and sharing of research data - regjeringen.no The Research Council of Norway’s Policy for Open Access to Research Data The Research Council of Norway’s assessment of open science in grant applications The Research Council of Norway: Sharing research data Practical Guide to the International Alignment of Research Data Management - Extended Edition - Science Europe Zenodo RIO Journal DS Wizard ELIXIR-Norway FAIRsharing https://doi.org/10.7717/peerj.175/fig-1 https://doi.org/10.1371/journal.pone.0230416 Data submission | Services | EMBL’s European Bionformatics Institute Federated EGA Norway node European Genome-phenome Archive Referencing and citing content - GitHub Docs Sacha Beniamine / gitlab2zenodo · GitLab WorkflowHub EU Grants: HE Programme Guide: V2.0 – 11.04.2022 EU Grants: HE MGA — Multi & Mono: V1.1 – 15.04.2022, This work was funded by the ELIXIR (3322392) and BioMedData (295932) infrastructure grants and the Centre for Digital Life Norway (248810/O70) through the Research Council of Norway. Trademarks, service marks, trade names, logos, icons, and domain names in this presentations are proprietary to their respective owner and are not subject of this license. Reuse of illustrations is indicated on the individual presentation slides.

The scope of this deliverable was to provide final best practice recommendations incorporating use of data brokering, business models and pan-European operations, with the aim of capturing, collating, and disseminating the collective research data management (RDM) expertise that resides across the ELIXIR member Nodes. The data management guidelines aim to promote knowledge sharing and capacity building among the member Nodes, as well as harmonising the guidance across Nodes, while at the same time taking the varying local circumstances at different ELIXIR Nodes into account. The best practice content has been a deeply integrated effort by many partners in most of the Nodes through the work of WP1, WP2, WP3, WP5, WP7, WP8 and WP9, and through the establishment of the Data Management Network. Through the strong position of the RDMkit information resource as a major authority source of life science RDM knowledge, it was also possible to engage contributors beyond those that were participating in the CONVERGE project. Establishing services to broker data submissions is an effective way to facilitate the flow of FAIR data from life science research to Core Data Resources (CDR), ELIXIR Deposition Databases (EDD) and ELIXIR Community data resources. With the aim to explore existing practice and develop models around brokering data (including the tools, services and training around this) to specific ELIXIR Deposition Resources, three main brokering explorations have been investigated. The discipline of data stewardship is a relatively new one that will become increasingly more important over time. Data management support services will have to operate for the foreseeable future, and consequently the means by which e.g. an ELIXIR Node can provide sustainable long-term services needs to be explored. To this end, surveys have been conducted to scope the current business model landscape, and put together as a Business Model Catalog to serve as inspiration for sustaining node service operations for data management. Existing business models that were currently implemented by the ELIXIR Nodes, as well as current levels of data management service provisioning, have been reviewed to investigate long-term sustainability strategies for supporting the provision of data management/data stewardship services . To encourage harmonisation in the way ELIXIR Nodes provide data management support to research projects, an operating model for harmonised data management in European projects has been developed as a guide for data managers and data stewards to assist researchers in offering advice on responsible management approaches in life-science domains. The model itself is a set of recommendations and best practices in data management applicable in European projects, guaranteeing an overall harmony in data management practice. Conclusions: A pan-European network of data experts that meets monthly, serving as a conduit for information exchange between individuals in the network and researchers/data stewards within institutions represented by the node. This community of practice can serve future and sustained projects within ELIXIR, with a synergistic international exchange of solutions, thus contributing with training and documenting of best practices even after the project CONVERGE ends. A comprehensive collection of best practice guidelines relevant to the life science domain has been developed and refined over the years, and has been made available through the RDMkit resource that has been designed and established by WP3. The content of the guidelines is presented through several orthogonal entryways – the Data life cycle, Your role, Your domain, Your tasks, Tool assembly, and National resources. The RDMkit has become a major authoritative source of life science RDM knowledge. The guidelines have served to help in identifying and prioritising data management training needs and the development of training material. Contributions of content have come from a large number of Nodes and experts, including members not only in WP1, but also WP2, WP3, WP5, WP7, WP8 and WP9, from the broader Data Management Network, as well as experts outside of ELIXIR. Content has been generated in a crowdsourcing manner, both during hackathons and contentathons organised in topic-specific focus groups. This process has sparked discussions that in themselves are an important part of the knowledge-sharing and capacity building process and the results from these discussions are available in an accessible manner in the RDMkit. Through WP1 T1.2, extensive discussions have been had to devise brokering models for a variety of different life science groups. This has allowed valuable insight into the needs of those who openly share / would like to openly share data on a large-scale. These discussions also benefit the target repositories through feedback as to how their services can be improved. Ultimately, T1.2 highlights a brokering landscape, showing a variety of ways that data brokering can be performed, the different roles brokers can take on, and the ways in which these can benefit the scientific community (e.g. by enhancing data sharing and/or metadata quality). Most Nodes are in an establishment phase in their data management operations with frequent lack of established business models, and services delivery are only supported by public subsidisation in almost all the Nodes. Nodes are moving towards the exploration of new sustainability strategies and models where part of the costs are recovered from final users. A single one-size-fit-all sustainability strategy can not be advocated for all Nodes. The implemented business model strategies can be grouped according to the gradient of public subsidisation and user/customer contribution under three business models (in the so called Business Model Catalog): Free, Freemium and Pay per use. A harmonised operating model for providing data management support to projects has been designed, that follows these steps: i) Establishment of Data Expert Network, ii) Implementation of Data Life Cycle into the operating model, iii) Application of Best Practices reflected in RDMkit, iv) Mapping of supporting IT infrastructure and computational resources availability and utilisation, and v) Funding model of the data management as an ELIXIR Service.

Open Access Week 2022 session dedicated to research data and its FAIRly new superheroes: the data stewards and their role as experts in data handling throughout all phases of the data life cycle.

Slides from 2022-09-26/27 online workshop

In this webinar, we will present a new feature of the Data Stewardship Wizard (DSW) for creating data management plans (DMPs) compliant with best practices in specific domains in the life sciences. This new implementation allows the user to start from a pre-filled questionnaire ("Exemplar DMP") containing recommendations provided by domain experts participating in the BioMedData infrastructure coordinated by ELIXIR Norway. We will show and discuss exemplar DMPs from national research infrastructures working within: genomics (NorSeq, NIMG) proteomics (NAPI) imaging (NALMIN; NorMOLIM), biodiversity (GBIF Norway) macromolecular crystallography (NorCryst) molecule screening (NOR-OPENSCREEN). We encourage research advisors and support staff to attend this webinar to learn about this solution and how to improve data management planning in critical phases.

Growth of omics disciplines has significantly increased the researchers' demand for support in the field of data management. It follows that long term sustainability of existing data management services and platforms is of critical importance to the research community. The ELIXIR-CONVERGE Task 1.3-Business model aims at investigating long-term sustainability strategies for supporting the provision of said data management/data stewardship services. In order to achieve this goal, the authors reviewed existing business models that were currently implemented by the ELIXIR Nodes. Data collection was performed by means of on-line surveys and interviews, investigating how DM/DS services are delivered and how they are financially supported. The current investigation was performed at different time points along the implementation of the ELIXIR-CONVERGE action, allowing the authors to sketch an analysis of the delivered services, and their financial sustainability in a two years time frame. The investigation revealed how in almost all the Nodes, the delivery of data management services depends on public subsidies, usually by means of a mix of institutional, national and European Union/European Commission funded projects. Likewise, the current work highlighted how Nodes are exploring new sustainability strategies and models where part of the costs are recovered from final users. Considering the gradient of public subsidisation and user/customer contribution, the authors of the current report characterised the implemented sustainability strategies under three (plus one) business models: Free, Freemium, Pay per use (Pay per use +). Although a growing number of Nodes are moving towards exploring and implementing sustainable business models, our investigation highlights how in most cases the resulting strategies can be considered only experimental. In several instances transactions are only virtual and cost recovery often never happens in full. The main outcome of the effort presented in the current document is the definition of a portfolio of fact sheets describing all the alternative funding strategies other than the full public subsidisation implemented by the Nodes: the Business Model Catalog.

The BioMedData project, initiated by ELIXIR Norway, aims to connect the largest research infrastructures (RIs) within the Life Sciences in Norway with the scope of improving their data management practises, aiming at the production of findable, accessible, interoperable and reusable (FAIR) data. This deliverable aims at describing and defining the contents of the first BioMedData end-user course, to take place in spring 2022. This activity builds upon two pillars: the existing training activity on Data Management Planning currently offered by ELIXIR Norway and Digital Life Norway and the report on data management gaps published by the BioMedData participants in March 2021. The latter provides a set of field-specific data management recommendations that enrich the content of the former, thus providing the end-users with concrete knowledge on FAIR data based on their domain. The course aims to cover topics covering the whole data life cycle (as shown in the Research Data Management kit by ELIXIR Europe) with a specific focus on the implementation of the FAIR data principles., The course is funded by the Norwegian Research Council through BioMedData as Forskningsinfrastruktur 295932.

The BioMedData project was established in 2020 to connect the largest research infrastructures within the Life Sciences in Norway with the scope of improving their data management practices, aiming at the production of findable, accessible, interoperable and reusable (FAIR) data. This report marks the conclusion of the first phase within the project, aimed at assessing the data management routines at these infrastructures and the gap with respect to the FAIR data principles. This study is supported by a questionnaire, compiled by all the infrastructures involved, covering international requirements (Science Europe, Horizon2020) as well as the FAIR data principles. The investigation revealed a lack of internationally recognised metadata standards and repositories within specific domains. In other cases, the international metadata standards lack attributes representing provenance information of steps prior to data generation. On top of this, the main responsibility for data management implementation is found to often lie with individual researchers and not infrastructures. A more systematic organisation of data management duties and associated budgeting by the research projects would allow the infrastructures to operate a cost recovering support model., Funded by the Norwegian Research Council as Forskningsinfrastruktur 295932

Be ready to receive funding! Why is Data Management important for my application? This webinar on the 5th of February (10.00 CET) from ELIXIR Norway will provide you with information on Data Management requirements for research applications to the Research Council of Norway (RCN) call for proposals with deadline February 10th. The RCN requires that all funded projects must assess the need for a Data Management Plan. In this webinar we will highlight the RCN requirements for Data Management from a Life Science perspective and give a short introduction to the Data Management Planning tool "Data Stewardship Wizard" by ELIXIR Norway. This 45 minutes webinar will be presented by Korbinian Bösl (ELIXIR Norway, BioMedData & Centre for Digital Life Norway)

The aim of this deliverable is to start capturing, collating, and disseminating the collective data management expertise that resides across the ELIXIR member Nodes. This first version of the guidelines aims to promote the knowledge sharing and capacity building among the member Nodes when it comes to data management, as well as harmonising the guidance across Nodes, while at the same time taking the local circumstances into account. It should also help in identifying and prioritising data management training needs and the development of training material. Furthermore, this resource should highlight how ELIXIR services can solve data management issues for the research community. The work of establishing best practice guidelines to a great extent interacts with the work done in WP2 Training, WP3 Toolkit, and WP5 Demonstrators. The work has been coordinated by a subgroup of the Data Management Coordinators group. It was decided that the primary focus audience for the guideline content should be the professionals in a research-supporting Data Steward role. The emerging “RDMKit” web resource designed and established by WP3 was selected as the medium for disseminating the best practice guidelines content. The best practice guidelines content has been developed in a crowdsourcing manner by the members of WP1 and the broader Data Management Network , in large parts through the “Hackathons” and “Contentathons” organised by WP3. The work of WP1, WP2, WP3 and WP5 to produce this resource has been deeply integrated with each other, as many of the network membersare involved in several different WPs of the project, and because the subject matter covered in the different WPs overlap. Hence: ● A first version of best practice guidelines, relevant to the life science domain, has been developed. The content of the guidelines focuses on the different data life cycle stages, as well as key data management issues related to them. The content is targeted to research-supporting Data Stewards. ● The best practice guidelines content is being made available through the RDMKit resource, that has been designed and established by WP3. ● Contributions of content have come from a large number of Nodes and experts, including members not only in WP1, but also from WP2, WP3 and WP5. ● Content has been generated in a crowdsourcing manner; much of it during hackathons organised by WP3. This process has sparked discussions that in themselves are an important part of the knowledge-sharing and capacity building process.

An ELIXIR Common Data Management Toolkit is intended to support researchers and data stewards to enable lifecycle management for their research data, according to international standards, and integrated in the national context. The goal is to support FAIR by Design: from the first steps of producing FAIR data and Data Management Planning to the final steps of depositing data in public archives through data brokerage pathways from data management systems (Task 1.2) and enabling its reuse. The vision of the Toolkit has matured into three, interlinked, streams: 1. The RDMKit, a website-based toolkit designed to guide life scientists and data stewards in their efforts to better manage their research data. 2. Tool Assemblies, which are examples of combining tools to cover stages of the RDM Lifecycle and assembly patterns to report how tools can be combined and replaced by local specialisations. 3. Data Stewardship Wizard, which leads data stewards through decision trees to choose the right tools, resources and practices when planning their data management. WP3 has concentrated on the RDMKit. This provides rapid and maximum benefit to the Node’s Life Science communities and effectively coordinates and integrates the work of the CONVERGE WPs around a common goal. It also provides a timely resource for funders such as the EC’s Open Science Unit during development of the HorizonEurope programme. The RDMKit is targeted at researchers, data managers and data stewards in laboratories, facilities or universities; project consortium coordinators and funding agencies and policy makers. The RDMKit’s underlying technical infrastructure has been established using GitHub (https://github.com/elixir-europe/rdmkit) and the contribution and editorial processes put in place. Content has been assembled through hackathons/contentathons. This deliverable reports on the conception, design, implementation of the RDMKit, its open contribution, review and editorial processes, gives screenshot examples and lays out the next steps. The RDMKit is available at https://rdm.elixir-europe.org/ and https://rdmkit.elixir-europe.org/ (aliases) and will be internally beta released for review and awareness raising on 31 January 2021 and publicly released on 31 March 2021.

From: DMP writing workshop, Ås 11.03.2020, CC-BY 4.0 if not indicated else wise

Viruses are one of the major causes of acute and chronic infectious diseases and thus a major contributor to the global burden of disease. Several studies have shown how viruses have evolved to hijack basic cellular pathways and evade innate immune response by modulating key host factors and signaling pathways. A collective view of these multiple studies could advance our understanding of virus-host interactions and provide new therapeutic perspectives for the treatment of viral diseases. Here, we performed an integrative meta-analysis to elucidate the 17 different host-virus interactomes. Network and bioinformatics analyses showed how viruses with small genomes efficiently achieve the maximal effect by targeting multifunctional and highly connected host proteins with a high occurrence of disordered regions. We also identified the core cellular process subnetworks that are targeted by all the viruses. Integration with functional RNA interference (RNAi) datasets showed that a large proportion of the targets are required for viral replication. Furthermore, we performed an interactome-informed drug re-purposing screen and identified novel activities for broad-spectrum antiviral agents against hepatitis C virus and human metapneumovirus. Altogether, these orthogonal datasets could serve as a platform for hypothesis generation and follow-up studies to broaden our understanding of the viral evasion landscape., Frontiers in Immunology, 10, ISSN:1664-3224