ELIXIR-CONVERGE D5.5 Report on the remaining four DMP processes
Creators: name: Portell-Silva, Laura
name: Haurheeram, Vanita
name: Adam-Blondon, Anne-Françoise
name: Capella-Gutierrez, Salvador
name: Popleteeva, Marina
name: Bianchini, Federico
name: Åberg, Espen
name: Hooft, Rob
name: Schuánek, Marek
name: Slifka, Jan
name: Hospital, Adam
name: Willassen, Nils-Peder
name: Piñero, Janet
name: Sanz, Ferran
name: Ramirez-Anguita, Juan Manuel
name: Pastor, Manuel
name: Angel Mayer, Miguel
name: Picardi, Ernesto
name: Alper, Pinar
name: Ded, Vilém
name: Djenaba Barry, Nene
name: Lieby, Paulette
name: D'Altri, Teresa
name: Faria, Daniel
name: Le Floch, Erwin
name: Rocca-Serra, Philippe
name: Droesbeke, Bert
name: Bösl, Korbinian
name: Vidak, Marko
name: Pommier, Cyril
name: Beier, Sebastian
name: Lange, Matthias
name: Arend, Daniel
name: Zlender, Nadja
name: Alic, Isabelle
Publisher: name: Zenodo
Year: 2023
Subjects: ELIXIR-CONVERGE
ELIXIR
Data Management
DMPs
Data Management Plans
RDMKit

description: 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.