DataBio and Data Sharing Big Data Value Meet-up Sofia, 14 May 2018 http://www.big-data-value.eu/big-data-value- meet-up-sofia/ Prof. Caj Södergård, Technical Manager, VTT

Existing software & datasets from partners to serve pilots IoT components & datasets Agro Pilot 1 Agro Pilot 2 Agro Pilot 13 Forest Pilot 1 Forest Pilot 2 Forest Pilot 7 Fishery Pilot 1 Fishery Pilot 2 Earth Observation components & datasets WP4 WP1-3 Fishery Pilot 6 ... Optimal raw material production with sustaina- bility WP5 Deliverables D4.1, D4.2, D4.3 Milestone M7 D5.1, D5.2, D5.3 Milestone M9 DataBio platform with big data components and datasets

The components help in various processing phases

Data Integration and Sharing Acquire: Gather open and proprietary data from various domains, extract metadata and store into the database in standardized format Process. Process and visualize the data by deploying pipelines of (interchangable) modules with well defined interfaces Share the integrated and processed data according to the FAIR principle: Findable, Accessible, Interoperable, Reusable (NOT necessarily open) Consider data security, ownership and privacy, e.g. by using semantig tagging of data Use DataBio Hub for dissemination

One way to share components and data;DataBio Hub

DataBio HUB

Metadata, Linked Data and Graph Data Integration – a DataBio example Challenges for DataBio Different metadata standards for sensor networks, EO & geospatial data Granularity: data sets, image tiles, web services… User friendly presentation of metadata Pipeline Accesses the Copernicus SciHub Parses metadata from the obtained data Stores metadata in the GeoJSON format Visualizes metadata Deployment view in Archimate UML relating to pilot ”Machinery management”

Thank you for your attention

Extra slides

Pipelines: Pilot 1.A1.1 Precision Agriculture in olives, fruits,grapes

Experimentation - Precision agriculture event driven application

Event management

Pilot 1.2.1.A1.1 - Results for the olive trees disease alerts