The Horizon Europe Model Grant Agreement requires that a data management plan (DMP) is established and regularly updated. This DMP describes how research data are managed both throughout the lifecycle of the project and after the end of the project. It identifies procedures and minimum requirements to collect, store, analyse, and publish data in a consistent way according to the FAIR (Findable, Accessible, Interoperable and Reusable) principles. This document is a living document and will be regularly updated when necessary. Milestones are scheduled for M24 and a final report on M48. All project partners will be informed of the changes made to this document via the project Steering Group meetings and made available via the internal information processes and during the meeting of the next General Assembly. The basis for this document is the Horizon template for a Data Management Plan.

This assembly focused on improving food labelling policies to support healthier and more sustainable consumer choices, aligning with the EU Farm-to-Fork Strategy. 70 participants were recruited country-wide by stratified random selection, representative in terms of age, gender, education and region. The assembly took place during one weekend, with facilitation guided by feminist moderation principles. It was preceded by an expert stakeholder roundtable, which contributed to the development of an informational booklet for the assembly. The recommendations were discussed with a panel of governmental representatives during the assembly.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

Complex systems such as cities, energy grids, or the global climate have many plausible futures. Scenarios, or structured narratives of decision-relevant futures, are a common decision support tool for making the complexity and uncertainties of complex systems humanly interpretable. However, the effectiveness of scenario-based decision support depends in part on the usefulness of the selected scenarios. Here we show an optimization-based approach for generating scenarios that are specifically designed to be diverse, plausible, and comprehensive. We establish the advantages of our method by evaluating it against three previously proposed methods: scenario matrices, generic archetypes, and clustering. Our case study is Schelling’s segregation model, a tractable yet behaviorally rich simulation of a complex system. Our results show the proposed optimization-based approach can generate more diverse, plausible, and comprehensive scenarios than existing approaches. The resulting scenarios may provide a more insightful and robust basis for policy decisions, especially for complex systems with emergent behavior or where substantial uncertainties are present.

This plan outlines the workflow for data management, including the creation, curation and sharing of data. The responsibilities of the file managers are outlined, along with the guidelines for creating and curating data on the RestPoll drive.

Multicomponent and high-aspect ratio nanomaterials (MCNMs and HARNs) have various industrials applications. MCNMs and other chemical compounds containing ZnO are applied in sunscreens and cosmetic products and, therefore, are valuable substances. However, the potential toxic effect of these (nano)materials on various biological systems is uncertain. Differentiating between uptake of true metal NMs and that of released ions is essential to assess the actual role of these two metal forms in toxicity over time. Therefore, toxicokinetic experiments were conducted to assess the implications of ZnO containing NM and their components on earthworms in soil, daphnia in fresh water, and biofilm in sediment. These experiments comprised an uptake phase in which these organisms were exposed to a ZnO containing NM or one of its (ionic) components, after these organisms were transferred to a clean environment to depurate themselves from the NM or their components in the elimination phase. Earthworms exposed to the ZnO:Mn MCNM showed a rapid increase in Zn and Mn concentrations, followed by a rapid decline after transfer to clean soil. Earthworms exposed to MnCl2 showed increases and decreases in Mn concentration after exposure and transfer to clean soil that were similar to worms exposed to ZnO:Mn. Daphnids exposed to ZnO:Mn and ZnO also showed a rapid increase in Zn concentration, but a negligible decline after transfer to clean media. The Mn concentration in daphnids exposed to ZnO:Mn indicated a gradual increase and decline after exposure and transfer to clean media, respectively. Toxicokinetic one-compartment models were fitted to the earthworm and daphnid data and enable the estimation of uptake and elimination rate parameters along with the computation of the bioaccumulation factor. Moreover, in this deliverable a protocol to evaluate the toxicodynamics of ZnO and ZnO:Mn nanoparticles in biofilms is described, as well as the results obtained.

The WUR research data sharing guidelines infographic is developed to help researchers determine, by means of questions, whether the research data from their research can be shared openly or not.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

<p>Detailed background data on own husband, parents and ex-husband / religious attitude / experiences during courtship / premarital sexual relations / what happened after divorce ( house, children ) / relationships with both families / friends / problems in financial matters / different hobbies / children / drinking problems of self and husband / personality descriptions of former husband and self / reasons for divorce ( also for husband's wife ).</p><p>Background variables: basic characteristics/ household characteristics/ occupation/employment/ education/ religion</p>