WP4: Databases for integrated sustainability assessment at multiple scales


Leader : Erling Andersen, Danish Centre for Forest, Landscape and Planning, Hørsholm, Denmark

[Publications] [Reports]


Work Package 4 provides a smooth support to the integrative goals of SEAMLESS. The main objective of WP4 is to populate the knowledge base of SEAMLESS designed in WP1 and WP5 with databases. The SEAMLESS knowledge base will adopt a uniform representational paradigm that can represent knowledge in both structural (data) and functional (model) forms, and allow a transparent and fully automatic flow of information between the two. In WP4 the knowledge base will be populated with data and with the information needed to access and combine the data in different formats and at different spatial levels. The data includes model inputs, source data for queries and statistics, metadata and SEAMLESS-IF analysis outputs. The relevant and available farming system, environmental, economic and social data sets – with coverage for EU-25 and at the global level – will be collected and adapted. The adaptation includes developing typologies of farming systems and of regions to be used for organising the data in the knowledge base. Specific routines, procedures, protocols and knowledge rules will be developed to facilitate access and inclusion in the domain editor developed in WP5. This includes developing protocols for combining spatial and statistical data. In summary, the main aims of this WP are:


·  Populating the SEAMLESS knowledge base with data and metadata;

·  Reporting metadata for available data sets;

·  Collection and adaptation of spatially explicit environmental data at EU-25 level;

·  Collection and adaptation of data on farming systems at EU-25 level, including development of a farming systems typology;

·  Collection and adaptation of socio-economic data at EU-25 level;

·  Collection and adaptation of economic data and data on natural resource use at the global level;

·  Protocols for spatial analysis;

·   Defining data gaps and setting the agenda for data collection.