{"id":1464,"date":"2025-02-27T14:56:51","date_gmt":"2025-02-27T13:56:51","guid":{"rendered":"https:\/\/wp.unil.ch\/dsbu\/?page_id=1464"},"modified":"2025-05-25T15:48:49","modified_gmt":"2025-05-25T13:48:49","slug":"consulting-dmp","status":"publish","type":"page","link":"https:\/\/wp.unil.ch\/dsbu\/consulting-dmp\/","title":{"rendered":"Data Management Plan (DMP) preparation and reading"},"content":{"rendered":"\n

The DSBU provides tailored templates and guidance ensuring that FBM UNIL-CHUV researchers<\/strong> have access to customized life-science and biomedical models suited to their needs. Our service has set-up templates and questionnaires facilitating the creation of SNFS-compliant DMPs <\/strong>by aligning with research cycle phases and integrating responses into the SNFS template. Additionally, the DSBU provides a DMP review service before submission to the funding agency<\/strong>, ensuring compliance and quality.<\/p>\n\n\n\n

Data Management Plan Description<\/h2>\n\n\n\n

A DMP is a crucial document in research projects that outlines how data will be managed throughout its entire life cycle<\/strong>. The aim of a DMP is to provide a structured approach to ensure that data is effectively collected, processed, stored, shared, and preserved in a way that promotes data quality, accessibility, and long-term usability<\/strong>. By creating and following a well-structured Data Management Plan, researchers can enhance the quality of their research, facilitate collaboration, comply with funding agency requirements, and ensure the long-term value and accessibility of their data.<\/p>\n\n\n\n

Key components of a Data Management Plan<\/strong><\/summary>\n

Data Description:<\/em><\/strong> A detailed description of the data to be collected or generated, including its format, structure, and potential volume.
Data Collection:<\/em><\/strong> Information about how the data will be collected, including methodologies, instruments, and tools.
Data Documentation:<\/em><\/strong> Plans for documenting the data, such as metadata standards, data dictionaries, and annotations, to ensure that others can understand and use the data.
Data Organization and Storage:<\/strong> <\/em>Details about how the data will be organized, named, and stored during the project. This may involve considerations of file formats, folder structures, and storage locations.
Data Sharing and Access:<\/em><\/strong> Plans for making the data accessible to others, which might involve repositories, embargo periods, access controls, and licensing arrangements.
Data Preservation and Archiving:<\/em> <\/strong>Strategies for preserving the data beyond the project\u2019s completion, including considerations of data formats, storage options, and potential repositories or archives.
Data Security and Ethics:<\/em> <\/strong>Measures to ensure data security and ethical handling, such as anonymization, encryption, and compliance with relevant regulations or standards.
Roles and Responsibilities:<\/em> <\/strong>Clearly defined roles and responsibilities for individuals involved in data management, including researchers, collaborators, and data stewards.
Budget and Resources:<\/em> <\/strong>Allocation of resources, both financial and human, needed for effective data management throughout the project.
Data Disposal<\/strong>:<\/em> Plans for the secure disposal or retention of data, taking into account legal and ethical considerations.
Data Management Training:<\/strong><\/em> Details about any training that will be provided to researchers to ensure they understand and follow proper data management practices.<\/p>\n<\/details>\n\n\n\n

DMP Creation with the DSW Tool as Key Resources<\/strong><\/strong><\/h2>\n\n\n\n

We help you develop, implement, and maintain a robust Data Management Plan (DMP)<\/strong> that underpins every stage of your research. <\/p>\n\n\n\n