Integration and dissemination of aquatic biodiversity and ecosystem services data for case studies focusing on ecosystem-based management
Aquatic ecosystems –from marine and coastal to freshwater– are rich in biodiversity and home to a diverse array of species and habitats, providing numerous economic and societal benefits to the European population. Many of these valuable ecosystems are at risk of being irreversibly damaged by human activities and pressures, including pollution, contamination, hydromorphological alterations, invasive species, overfishing and climate change. These pressures threaten the sustainability of these ecosystems, their provision of ecosystem services and ultimately human well-being. AQUACROSS (Knowledge, Assessment, and Management for AQUAtic Biodiversity and Ecosystem Services aCROSS EU policies – http://aquacross.eu) seeks to advance the application of ecosystem-based management for aquatic ecosystems in an effort to support the timely achievement of the EU 2020 Biodiversity Strategy and other international conservation targets. In this regard, AQUACROSS aims to develop and test an assessment framework through a series of cases studies which considers the full array of interactions within aquatic ecosystems, including human activities. Following the Horizon 2020 Open Research Data Pilot, AQUACROSS addresses the challenge of bringing together newly generated as well as existing data used in the framework of the case studies, while at the same time supporting the project partners in terms of data integration and harmonisation. Through a lightweight CKAN-based information platform, we aim on one hand to support project partners in terms of discovery and data access (in interoperable formats), while on the other hand we offer operational support to open up raw and processed data for use in other contexts and disseminating these data and results. The latter is facilitated by the capabilities of the CKAN software which includes on-the-fly analysis and visualisation tools and enables easy data access through external software and tools such as R, QGis and Phyton. During this presentation we will report on the main lessons learned during this data integration exercise and focus on selected case study examples.