MaMoDaR: Management of Molecular Data within the Research Data Life Cycle

• Applicants: Privatdozent Dr. Linus Grabenhenrich, since 12/2020; Professorin Dr. Heike Neuroth
• Subject Area: Bioinformatics and Theoretical Biology ; Epidemiology and Medical Biometry/Statistics ; Parasitology and Biology of Tropical Infectious Disease Pathogens ; Virology
• Term: from 2018 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 416783714

Our MaMoDaR proposal aims at developing, documenting and making publically available a sustainable concept and an integrative software solution that will offer a low-key interface for managing research data and integrating them with existing solutions such as RDMO for data management plans or repositories such as GenBank. Thanks to the direct support of a publication workflow to public repositories, MaMoDaR supports the structured publication of results in an open science perspective and simplifies scientific exchange on a national and international level. The concepts and software produced in this concept will be publically available. During the project, we will initiate a user community, which will follow a one health approach from the first step on and include institutions focused on human health / veterinary medicine and the environment. The results of MaMoDar can particularly serve as a blueprint for efficient research data management for mid-sized research institutions with a hierarchical structure. MaMoDar particularly comprises the development, testing, evaluation, documentation and publication of the following aspects:- To enable end users to directly interlink raw data files with metadata from their usual user interface, we will provide a user-friendly software solution. To increase the acceptance of research data management, the focus lies on intuitive useability and the reduction of additional data handling steps.- To offer a visible added value in the usage of research data management procedures to data producers and to thereby increase acceptance, we will provide search, import and export functionality for (meta-)data.- To increase compliance and to allow easy categorization and analysis of research data, we will compile standard operating procedures for the complete life cycle of a project from data management plans to data publication. - To use research data management as a steering mechanism, we will develop rule-based decision criteria. These will allow making strategic IT decisions (e.g. on growth of storage devices), complying with legal contexts (e.g. data protection or patents) or handling sensitive data with regard to dual use directly based on research data management. Thereby, MaMoDar will generate added value from research data management beyond the reuse of data

• DFG Programme: Research data and software (Scientific Library Services and Information Systems)
• Participating Institution: Freie Universität Berlin; Fachbereich Mathematik und Informatik; Institut für Bioinformatik; Max Rubner-Institut; Bundesforschungsinstitut für Ernährung und Lebensmittel; Stiftung Tierärztliche Hochschule Hannover
• Ehemaliger Antragsteller: Professor Dr. Bernhard Renard, until 12/2020