Annalisa Minelli, Caterina Bergami, Elisa Camatti, Mauro Bastianini, Fabrizio Bernardi Aubry, Alessandro Oggioni, Alessandro Sarretta, Alessandra Pugnetti, 2020, EcoNAOS: Open Science for marine long term data., EuroLag 9, Venezia, 20-24/01/2020,
URL: http://www.cnr.it/prodotto/i/418619

Open Science is increasingly pervading scientific communities, since the worth of sharing, beyond the results, research ideas, methods and tools, data and metadata is more and more recognized. Open Science principles applied to data, translate in FAIRness of data_ data must be Findable, Accessible, Interoperable and Reusable. We present a case study on the Open Science approach applied to the valorization of a long term dataset, composed of abiotic parameters, phyto- and zooplankton, collected in 50 years (1965 to 2015) in the Northern Adriatic Sea (NAS), one of the Long Term Ecological Research (LTER) sites of the LTER-Italy network. We describe and discuss the different operational parts of the case study that are all connected in defining the "open research project lifecycle". Starting from the data, the lifecycle includes each step of the entire research project, with specific sharing strategies. Two main types of actions were undertaken_ (i) on data (e.g. data harmonization, metadatation, repository choice) and (ii) on the whole research process (e.g. publication of research ideas and results, sharing of source code and models, other dissemination actions). The lessons learned through the realization of this case study, in particular the assessment of the strengths and weaknesses of the solutions adopted at each stage of the "project lifecycle", might be usefully generalized and extended also to other types of LTER transitional and marine sites. In particular, this might be the case of the Lagoon of Venice (LoV), another LTER-Italy site adjacent and connected to the NAS, where comparable data have been gathered as well. The more the time series on plankton and related variables are made available, according to the FAIR principles, the more it is possible to reconstruct and compare trends and dynamics, providing precious tools for detecting significant changes in response to global or local pressures and impacts.

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