IndexMEED cases studies using "Omics" data with graph theory

Data produced within marine and terrestrial biodiversity research projects that evaluate and monitor Good Environmental Status, have a high potential for use by stakeholders involved in environmental management. However, environmental data, especially in ecology, are not readily accessible to various users. The specific scientific goals and the logics of project organization and information gathering lead to a decentralized data distribution. In such a heterogeneous system across different organizations and data formats, it is difficult to efficiently harmonize the outputs. Few tools are available to assist. For instance standards and specific protocols can be applied to interconnect databases. Such semantic approaches greatly increase data interoperability. This communication present the recent results and the consortium IndexMEED (Indexing for Mining Ecological and Environmental Data) activity that aims to build new approaches to investigate complex research questions, and support the emergence of new scientific hypotheses based on graph theoryAuber et al. 2014). Current developments in data mining based on graphs, as well as the potential for relevant contributions to environmental research, particularly about strategic decision-making, and new ways of organizing data will be presented (David et al. 2015). In particular, the consortium makes decisions on how i) to analyze heterogeneous distributed data spread throughout different databases combining molecular and habitat characteristics data [3], ii) to create matches and incorporate some approximations, iii) to identify statistical relationships between observed data and the emergence of contextual patterns using a calculation library and distributed calculation center at the European level, iv) to encourage openness and sharing data while complying with the general principles of FAIR (Findable, Accessible, Interoperable, Re-usable and citable) in order to enhance data value and their utilization. IndexMEED participants are now exploring the ability of two scientific communities (ecology sensu lato and computer sciences) to work together, using several studies cases. The ECOSCOPE project aims to meet the need to access structured and complementary omics-datasets to better understand biodiversity state and its dynamics. Indeed, the ECOSCOPE case study targets to visualize, through the graph approach, links between datasets and databases from genetics to ecosystems. Another case study, displaying anthrop