A Data management plan is a structured document that describes what research data is created, how it will be managed during and after the project and the different responsabilities.
Documentation about the origin of data and data collection is part of the DMP as well as possible restrictions on access to the data.
When starting with your DMP, please observe the following scheme:

comitato.etico@unimi.it – infoprivacy@unimi.it
tto@unimi.it
The TTO at UNIMI guides you throughout the entire process of protecting intellectual property and looks for industrial partners that want to bring a
patented technology to market. We help you to assess the market potential of an invention, determine a protection strategy, file a patent application,
follow up on patent procedures, etc.
A DMP is conceived and written at the very beginning of a research project and modified whenever the need arises.
How to write a DMP
Each research funding body has its own template for DMP and it is advisable to use that template. The minimum requirements for a template can be found here
1. Data description and collection or re-use of existing data
a. How will new data be collected or produced and/or how will existing data be re-used?
b. What data (for example the kinds, formats, and volumes) will be collected or produced?
2. Documentation and data quality
a. What metadata and documentation (for example the methodology of data collection and way of organising data) will accompany data?
b. What data quality control measures will be used?
3. Storage and backup during the research process
a. How will data and metadata be stored and backed up during the research process?
b. How will data security and protection of sensitive data be taken care of during the research?
4. Legal and ethical requirements, codes of conduct
a. If personal data are processed, how will compliance with legislation on personal data and on data security be ensured?
b. How will other legal issues, such as intellectual property rights and ownership, be managed? What legislation is applicable?
c. How will possible ethical issues be taken into account, and codes of conduct followed?
5. Data sharing and long-term preservation
a. How and when will data be shared? Are there possible restrictions to data sharing or embargo reasons?
b. How will data for preservation be selected, and where will data be preserved long-term (for example a data repository or archive)?
c. What methods or software tools will be needed to access and use the data?
d. How will the application of a unique and persistent identifier (such as a Digital Object Identifier DOI) to each data set be ensured?
6. Data management responsibilities and resources
a. Who (for example role, position, and institution) will be responsible for data management (i.e. the data steward)?
b. What resources (for example financial and time) will be dedicated to data management and ensuring that data will be FAIR (Findable, Accessible, Interoperable, Re-usable)?