Data Management Plan 2.0

The PAUL project aims to create Urban Greenhous Gas Observatories to provide high quality and high-resolution temporal and spatial measurements. Measurements and observations are combined with existing data from the cities like emission inventories and 3D representation of the cities. This will provide the basis to run models, like inversion models, large eddy simulations, or Lagrangian stochastic models. In addition, PAUL has a co-design approach to integrate the needs of the cities and citizens. For this reason, we will conduct surveys and interviews, amounting to a collection of unstructured data. Data gathered through interviews and questionnaires are anonymised and we follow ethical guidelines under the supervision of the European Social Survey Research Infrastructure. Regarding data used and produced within the project, we can divide them in four categories:

• Measurements which include greenhouse gas concentrations, meteorological parameters like wind speed & direction, humidity, air pressure, boundary layer height, etc., and ecological data like soil water content, soil temperature, sap flow, etc.
• City Emission inventories, including spatial and temporal representations of people, green spaces within the city boundaries, traffic monitoring density, etc.
• Results of models and simulations
• Unstructured data from surveys All datasets uploaded to the repository are automatically backed up, linked to a unique persistent identifier, and annotated with a rich set of meta data. It is expected that all data is published under a CC BY 4.0 licence. The results are provided through a dedicated data repository hosted at the ICOS Carbon Portal, based on a mature source code and established services, providing backup, persistent identifications like PID and DOI minting, API endpoints, virtual research environments, etc. The ICOS Carbon Portal provides a solid base to have a ‘FAIR’ provision of data to the public and scientific communities. We would like to remind at this point, that the Data Management Plan contains projections and assumptions and represents a snapshot of the current knowledge of data products and development of our data repository. The DMP is a living document and is continuously updated.