Arctic Frontiers 2019 Abstract Looking at climate change, development of activities like fishing, shipping, tourism etc together with the history of policies in the polar region in and around Svalbard applying an holistic approach, can result in new information that will help us make better decisions for the Arctic area in the future. 3 different H2020 projects INTAROS, NextGEOSS, and DataBio join forces to provide new information using the latest in big data and cloud technology, access to Copernicus data and services, and user requirements from social scientists. Through analysis of different types of met-ocean data ((e.g. ice edge, SST) and fishery statistics to investigate potential links between climate change and activity in the polar region in and around Svalbard. We evaluate if the FAIR principles are met for the chosen variables, using Copernicus, BarentsWatch and other open data resources. Accessibility and functionality of the related APIs will be assessed, and whether the chosen APIs can jointly provide new information. We will also present how one can combine available information from existing sources, such as catch reports, oceanographic measurements, oceanographic simulations, stock simulations and stock observations, can be used for improving assessment of fish stocks and their distribution. Part of these data will be derived from remote sensing, while others will be collected using vessels equipped with appropriate sensors and communication and communication tools. Together this combinations of data will provide new information that will be useful for policy making in polar regions and that take into account the different sectors and actors involved.

1. Combining Earth observations and
statistics for evidence-based policy
making in polar regions
by Bente Lilja Bye
( BLB )
Torill Hamre ( NERSC ); Markus Fiebig ( NILU ); Ståle Walderhaug, Arne-Jørgen Berre,
Peter Haro, Erlend Stav, Per Gunnar Auran ( SINTEF ); Jovanka Gulicoska ( Viderum );
Dmitrii Kozuch (LesProjekt), Raitis Berzins (4Solutions) Arnfinn Morvik, (Marine Research
Institute)

2. CONTENT
Motivation
Our Approach
Methods and Resources
Results
Next Steps

3. MOTIVATION - user requirements
It would be great to have descriptive time series of climate
change together with human activities in the Arctic, around
Svalbard, and see how the development of Arctic policies have
been developed and implemented.
On a zoomable map
Freely after Prof. Grete Hovelsrud, President of the Norwegian
Scientific Academy for Polar Research

4. ... In recent years, the distribution of cod has
shifted northwards, as shown by cod catches..
...The model used in this case study examines the
combined effects of fishing, warming, and
acidification, with the ability to vary each of
these factors independently...
AMAP, 2018. AMAP Assessment 2018: Arctic Ocean Acidification. Arctic Monitoring and Assessment Programme
(AMAP), Tromsø, Norway. vi+187pp

5. PROJECT IDEA
Sustainable aquaculture and bio-economy.
• Combine different types of met-ocean data (e.g. ice edge, SST) and fishery
statistics to investigate potential links between climate change and
activities in the polar region in and around Svalbard.
• Evaluate if the FAIR principles are met for the chosen variables, using
Copernicus, BarentsWatch and other open data resources.

6. APPROACH
Holistic
Multipurpose
Transparent

7. 2016 - 2020
Data hub and Platform
10 internal pilots
Cold Region pilot
External pilot
27 partners
2016 - 2021 2017 - 2020
Pan-Arctic
European and non-European partners
Integrate in situ, satellites and models
7 application domains, including
Sea ice and ecosystem applications
47 partners (35 European)
Data-driven bioeconomy
Big Data 15 pilots
Fisheries pilots Norway
Tuna fishing Indian Ocean
Fuel optimization
48 partners

8. EVIDENCE-BASED

9. GLOBAL - EUROPEAN - LOCAL
GEO: Global data sets though GEOSS
Copernicus: The European Earth
observation program.
EU Contribution to GEO
INSPIRE directive: interoperability,
access, visualize, transform
Enrichment of Copernicus data

10. FAIR PRINCIPLES

11. THE DATA EXAMINED
• CMEMS Sea Ice Edge (OSI TAC)
• CMEMS Sea Ice and Ocean Temperature (OSI TAC)
• Fisheries Information (BarentsWatch)
• Fishery statistics (Norwegian Directorate of Fisheries)
• Small pelagic fisheries planning and fish stock assessment
(DataBio)

12. USED OR GENERATED SOFTWARE/TOOLS
• QGIS - Open Source GIS - https://www.qgis.org/
○ Supports a wide range of APIs (e.g. WMS, WCS, …)
○ Easily extensible (plugins)
○ Many community plugins available
• CKAN - Open Source Data Portal Platform - https://ckan.org/
○ Rich feature set (e.g. datastore, dataset registration, catalogue
harvesting)
○ Defines Action API for clients to access core functionality
○ Can write own extensions (plugins)
○ Over 200 community extensions

13. PROJECT RESULTS
• Initial exploration of
data sources with
WMS API in QGIS

14. Initial exploration of
data sources
with WMS API in CKAN
PROJECT RESULTS

15. USE OF APIs
• OPeNDAP (for CMEMS data)
• OGC WMS (making maps)
• OGC WCS (getting gridded data)
• BWOpen (fisheries facilities, AIS)
• other APIs to be explored…
• APIs to be created (Fishery Directorate, others)

16. CROSS SECTORAL OR CROSS
BOUNDARY INTEROPERABILITY
• The enrichment of Arctic Copernicus data can be
applied on other areas than fisheries, e.g. shipping,
arctic tourism etc.
• Interoperability lies in i) using APIs and ii)
visualization so that new information becomes
evident (time series, trends)

17. ENVIRONMENTAL, SOCIETAL AND/OR
ECONOMICAL CHALLENGES
The resulting INSPIRE data enriched Copernicus data and services
can provide
● natural resources management
● food security monitoring
● secure activities in the Arctic both equipment (boats, fish
farms, etc) and humans
● economic foresight

18. CONCUSIONS & FOLLOW-UP
• The team has planned to combine further data sets,
like zooplankton (IMR), AIS (SINTEF) and also involve
other partners (Fishery directorate, BarentsWatch,
OECD, other)
• Further use and development of visualizations of
the combined APIs (time series animation) would
be interesting for next INSPIRE hackathons.

19. Data visualization
eSUSHI

20. THANK YOU!
This project is supported by the European Commission
GA No. 727890GA No. 730329 GA No. 732064
This project has received funding from the European Union’s Horizon 2020 research and
innovation programme under the grant agreements No 730329, No 727890 No 732064