1. DataBio and Data Sharing
Big Data Value Meet-up
Sofia, 14 May 2018
meet-up-sofia/
Prof. Caj Södergård, Technical Manager, VTT

2. 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

3. The components help in various processing phases

4. 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

5. One way to share components and data;DataBio Hub

6. DataBio HUB

7. 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”

8. Thank you for your attention

9. Extra slides

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

11. Experimentation - Precision agriculture event driven application

12. Event management

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