#  EXECUTIVE SUMMARY

This plan is based on the H2020 FAIR Data Management Plan (DMP) template
designed to be applicable to any H2020 project that produces, collect or
processes research data. This is the same plan as OpenAIRE is referring to in
their guidance material. The purpose of the Data Management Plan is to
describe the data that will be created and how, as well as the plans for
sharing and preservation of the data generated. This plan is a living document
that will be updated during the project.

APPLICATE follows a metadata-driven approach where a physically distributed
number of data centres are integrated using standardised discovery metadata
and interoperability interfaces for metadata and data. The APPLICATE Data
portal, providing a unified search interface to all APPLICATE will also be
able to host data. APPLICATE promotes free and open access to data in line
with the European Open Research Data Pilot (OpenAIRE).

Within this plan an overview of the production chains for model simulations is
provided as well as an initial outline of dissemination. This version of the
plan is an update on the first version submitted in June 2017. A second update
to the plan are scheduled for October 2019\.

#  Introduction

##  Background and motivation

The purpose of the data management plan is to document how the data generated
by the project is handled during and after the project. It describes the basic
principles for data management within the project. This includes standards and
generation of discovery and use metadata, data sharing and preservation and
life cycle management.

This document is a living document that will be updated during the project in
time with the periodic reports (project months 18, 36 and 48).

APPLICATE is following the principles outlined by the Open Research Data Pilot
and The FAIR Guiding Principles for scientific data management and stewardship
(Wilkinson et al. 2016).

##  Organisation of the plan

This plan is based on the H2020 FAIR Data Management Plan (DMP) template  1
designed to be applicable to any H2020 project that produces, collect or
processes research data. This is the same plan as OpenAIRE is referring to in
their guidance material.

#  Administration details  
  
<table>  
<tr>  
<th>

Project Name

</th>  
<th>

APPLICATE

</th> </tr>  
<tr>  
<td>

Funding

</td>  
<td>

EU HORIZON 2020 Research and Innovation Programme

</td> </tr>  
<tr>  
<td>

Partners

</td>  
<td>

Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWI)
- Bremerhaven, Germany

Barcelona Supercomputing Center - Barcelona, Spain

European Centre for Medium-Range Weather Forecasts (ECMWF) - Reading, United
Kingdom

University of Bergen (UiB) - Bergen, Norway

Uni Research AS - Bergen, Norway

Norwegian Meteorological Institute (MET Norway) - Oslo, Norway

Met Office - Exeter, United Kingdom

Catholic University of Louvain (UCL) - Louvain-la-Neuve, Belgium

The University of Reading (UREAD) - Reading, United Kingdom

Stockholm University (SU) - Stockholm, Sweden

National Center for Scientific Research (CNRS-GAME) - Paris, France (with
contributions from Météo France)

European Centre for Research and Advanced Training in Scientific Calculation
(CERFACS) - Toulose, France

Arctic Portal - Akureyri, Iceland

University of Tromsø (UiT) - Tromsø, Norway

P.P. Shirshov Institute of Oceanology, Russian Academy of Sciences (IORAS) -
Moscow, Russia

Federal State Budgetary Institution Voeikov Main Geophysical Observatory (MGO)
- St. Petersburg, Russia

</td> </tr> </table>

#  Data summary

The overarching mission of APPLICATE is

_To develop enhanced predictive1 capacity for weather and climate in the
Arctic and beyond, and to determine the influence of Arctic climate change on
Northern Hemisphere midlatitudes, for the benefit of policy makers, businesses
and society_ .

Therefore, APPLICATE is primarily a project in which numerical models (for
weather and climate prediction) are used. As such it depends on observations
(e.g. for model evaluation and initialization), but the data generated by the
project is primarily gridded output from the numerical simulations.

The APPLICATE data management system will be used to collect information of
relevant third-party datasets that the APPLICATE community could benefit from,
and to share and preserve the datasets APPLICATE is generating, both
internally and externally.

A full overview of the datasets to be generated is yet not fully known, but
there is an overview of the production chains. This was prepared in the
proposal and is provided in Tables 1–3 below.

##  Data overview

###  Types and formats of data generated/collected

APPLICATE will primarily generate gridded output resulting from numerical
simulations and metrics based on these core datasets. The models used produce
a number of output formats which is not known in detail, but specific
requirements apply for data sharing and preservation (see below).

Self-explaining file formats (e.g. NetCDF, HDF/HDF5) combined with semantic
and structural standards like the Climate and Forecast Convention will be
used. The default format for APPLICATE datasets are NetCDF following the
Climate and Forecast Convention (feature types grid, timeseries, profiles and
trajectories if applicable). This includes the Coupled Model Intercomparison
Project (CMIP) requirements. The NetCDF files must be created using the NetCDF
Classic Model (i.e. compression is allowed, but not groups and compound data
types). The ESGF CMOR is recommended for conversion of model output.

Some datasets may be made available as WMO GRIB or BUFR. Where no clear
standard is identified initially, dedicated work will be attributed to
identifying a common approach for those data.

APPLICATE will exploit existing data in the region. In particular operational
meteorological data made available through WMO Gobal Telecommunication System
will be important for the model experiments. No full overview of third party
data that will be used is currently available, but since the start of the
project SYNOP data from WMO GTS have been available to the APPLICATE
community. Work is in proigress for more data from GTS. If necessary (required
by the scientific community in APPLICATE) metadata describing relevant
thirdparty observations will be harvested and ingested in the data management
system and through this simplifying the data discovery process for APPLICATE
scientists. There is however no plan initially to harvest the data.

Furthermore, model data produced in the context of CMIP5 and CMIP6 will be
used as a baseline against which model improvements will be tested.

###  Origin of the data

Data will be generated by a suite of numerical models, including operational
weather prediction and climate models. A preliminary list was provided in the
proposal and is included below.

APPLICATE is primarily a project in which numerical models are used. As such
it depends on observations (e.g. for model evaluation and initialization), but
the data generated by the project is primarily gridded output from numerical
simulations.

A summary of the numerical models to be used is provided in Tables 1-3.

Table 1: List of climate models.  
  
<table>  
<tr>  
<th>

Model

</th>  
<th>

AWI-CM

</th>  
<th>

EC-Earth CNRM-CM

</th>  
<th>

NorESM

</th>  
<th>

HadGEM

</th> </tr>  
<tr>  
<td>

Partner

</td>  
<td>

AWI

</td>  
<td>

BSC, UCL, SU CNRSGAME, CERFACS

</td>  
<td>

UiB, UR, Met.no

</td>  
<td>

MO, UREAD

</td> </tr>  
<tr>  
<td>

Atmosphere

</td>  
<td>

ECHAM6 T127

L95

</td>  
<td>

IFS ARPEGE-Climat

T255/T511 L91 T127/T359

L91

</td>  
<td>

CAM-OSLO 1o×1o

L32 / L46

</td>  
<td>

MetUM N216/N96

L85

</td> </tr>  
<tr>  
<td>

Ocean

</td>  
<td>

FESOM Unstruct. mesh 15-100 km L41

4.5-80 km L41

</td>  
<td>

NEMO NEMO 1o , 0.25o L75 1o, 0.25 o L75

</td>  
<td>

NorESM-O (extended

MICOM) 1o, 0.25o

L75

</td>  
<td>

NEMO 1o×1o L75 0.25o×0.25o L75

</td> </tr>  
<tr>  
<td>

Sea ice

</td>  
<td>

FESIM

</td>  
<td>

LIM3 GELATO

</td>  
<td>

CICE

</td>  
<td>

CICE

</td> </tr>  
<tr>  
<td>

Surface

</td>  
<td>

JSBACH

</td>  
<td>

HTESSEL SURFEX

</td>  
<td>

SURFEX

</td>  
<td>

JULES

</td> </tr>  
<tr>  
<td>

CMIP6

</td>  
<td>

Yes

</td>  
<td>

Yes Yes

</td>  
<td>

Yes

</td>  
<td>

Yes

</td> </tr> </table>

Table 2: List of subseasonal to seasonal prediction systems.  
  
<table>  
<tr>  
<th>

Model

</th>  
<th>

EC-Earth

</th>  
<th>

CNRM-CM

</th>  
<th>

IFS

</th>  
<th>

HadGEM/GloSea

</th> </tr>  
<tr>  
<td>

Partner

</td>  
<td>

BSC, UCL, AWI

</td>  
<td>

CNRS-GAME

</td>  
<td>

ECMWF

</td>  
<td>

MO, UREAD

</td> </tr>  
<tr>  
<td>

Atmosphere

</td>  
<td>

IFS

T255/T511 L91

</td>  
<td>

ARPEGE Climat

T255/T359 L91

</td>  
<td>

IFS

T511-T319 L91

</td>  
<td>

MetUM

N216 L85

</td> </tr>  
<tr>  
<td>

Ocean

</td>  
<td>

NEMO

1°/0.25° L75

</td>  
<td>

NEMO

1°/0.25°, L75

</td>  
<td>

NEMO

1°, L75

</td>  
<td>

NEMO

0.25o×0.25o L75

</td> </tr>  
<tr>  
<td>

Sea ice

</td>  
<td>

LIM3

</td>  
<td>

GELATO

</td>  
<td>

LIM2/3

</td>  
<td>

CICE

</td> </tr>  
<tr>  
<td>

Land

</td>  
<td>

HTESSEL

</td>  
<td>

SURFEX

</td>  
<td>

HTESSEL

</td>  
<td>

JULES

</td> </tr>  
<tr>  
<td>

Data assimilation

</td>  
<td>

Ensemble Kalman

filter

</td>  
<td>

Extended Kalman Filter

SAM2

</td>  
<td>

4D-Var

</td>  
<td>

4D-Var, NEMOVAR

3D-Var FGAT

</td> </tr> </table>

Table 3: Numerical weather prediction systems.  
  
<table>  
<tr>  
<th>

Model

</th>  
<th>

ARPEGE

</th>  
<th>

AROME

</th>  
<th>

IFS

</th>  
<th>

AROME-Arctic

</th> </tr>  
<tr>  
<td>

Partner

</td>  
<td>

CNRS-GAME

</td>  
<td>

CNRS-GAME

</td>  
<td>

ECMWF

</td>  
<td>

Met.no

</td> </tr>  
<tr>  
<td>

Atmosphere

</td>  
<td>

ARPEGE

T1198, stretched HR

</td>  
<td>

AROME

1.3km / 500m, 90 vertical

</td>  
<td>

IFS

T1279 L137

</td>  
<td>

AROME

2.5 km L65

</td> </tr>  
<tr>  
<td>

</td>  
<td>

(7.5km on grid pole),

L105

</td>  
<td>

levels

</td>  
<td>

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Ocean

</td>  
<td>

N/A

</td>  
<td>

N/A

</td>  
<td>

N/A

</td>  
<td>

N/A

</td> </tr>  
<tr>  
<td>

Sea ice

</td>  
<td>

GELATO

</td>  
<td>

GELATO

</td>  
<td>

N/A

</td>  
<td>

SICE

</td> </tr>  
<tr>  
<td>

Land

</td>  
<td>

SURFEX

</td>  
<td>

SURFEX

</td>  
<td>

HTESSEL

</td>  
<td>

SURFEX

</td> </tr>  
<tr>  
<td>

Data assimilation

</td>  
<td>

4D-Var

</td>  
<td>

dynamical adaptation

</td>  
<td>

4D-Var

</td>  
<td>

3D-Var

</td> </tr> </table>

In the original version of this data management plan, the total amount of data
was not known. This is still not known in detail, but some information on the
expected volumes for publication is known (this is a consequence of the
“partial dissemination” term used in Table 4). The ECMWF YOPP dataset is
excluded from this overview currently.

The major volumes to be disseminated through the data management system are
the ECMWF YOPP dataset, and seasonal forecasts and potentially climate
forecasts from WP5. Preliminary estimates (maximum values) of the volumes (Tb)
planned for dissemination are currently:

  * ECMWF YOPP dataset 

  

◦ Analysis and forecast dataset, including process tendencies, amounting to a
total volume of 300 Tb.

  * WP 5 Seasonal forecasts 

  

◦ Three different models, each producing in total approximately 20 Tb
throughout the project. In total approximately 60 Tb.

  * WP 5 Climate change simulations 

  

◦ One model in standard resolution approximately 20 Tb.

◦ One model in high resolution as well, approximately 685 Tb, would be
available for dissemination. However, in practice only a subset of the data
will be useful to the wider community, and hence significant data volume
reduction is being considered for dissemination.

###  ECMWF YOPP data

Within APPLICATE, ECMWF has begun to generate an extended two-year global
dataset to support the World Meteorological Organization’s Year of Polar
Prediction (YOPP). The start of production was timed to coincide with the
official launch of YOPP in Geneva, Switzerland, on 15 May. The dataset is
intended to support YOPP’s goal of boosting polar forecasting capacity. In
addition to the usual forecast data stored at ECMWF, it will include
additional parameters for research purposes. These include ‘tendencies’ in
physical processes modelled in ECMWF’s Integrated Forecasting System (IFS).
More information on the ECMWF YOPP dataset is available from ECMWF. The actual
data is available through the ECMWF YOPP Data Portal. This are discoverable
through APPLICATE Data Portal as well as the YOPP Data Portal.

##  Making data findable, including provisions for metadata [fair data]

APPLICATE is following a metadata driven approach, utilizing internationally
accepted standards and protocols for documentation and exchange of discovery
and use metadata. This ensures interoperability at the discovery level with
international systems and frameworks, including WMO Information System (WIS),
Year of Polar Prediction (YOPP), and many national and international Arctic
and marine data centers (e.g. Svalbard Integrated Arctic Earth Observing
System).

APPLICATE data management is distributed in nature, relying on a number of
data centres with a long-term mandate. This ensures preservation of the
scientific legacy. The approach chosen is in line with lessons learned from
the International Polar Year, and the ongoing efforts by the combined
SAON/IASC Arctic Data Committee to establish an Arctic data ecosystem.

APPLICATE promotes the implementation of Persistent Identifiers at each
contributing data centre. Some have this in place, while others are in the
process of establishing this. Although application of globally resolvable
Persistent Identifiers (e.g. Digital Object Identifiers) is not required, it
is promoted by the APPLICATE data management system. However, each
contributing data centre has to support locally unique and persistent
identifiers if Digital Object Identifiers or similar are not supported.

Concerning naming conventions, APPLICATE requires that controlled vocabularies
are used both at the discovery level and the data level to describe the
content. Discovery level metadata must identify the convention used and the
convention has to be available in machine readable form (preferably through
Simple Knowledge Organisation System). The fallback solution for controlled
vocabularies is the Global Change Master Directory vocabularies.

The search model of the data management system is based on GCMD Science
Keywords for parameter identification through discovery metadata. At the data
level the Climate and Forecast Convention is used for all NetCDF files. For
data encoded using WMO standards, GRIB and BUFR, the standard approach at the
host institute is followed. All discovery metadata records are required to
include GCMD Science Keywords. Furthermore, CMOR standards will be employed
for some of the climate model simulations, especially those contributing to
CMIP6.

Versioning of data is required for the data published in the data management
system. Details on requirements for how to define a new version of a dataset
is to be agreed, but the general principles include that a new version of a
model dataset is defined if the physical basis for the model has changed (e.g.
modification of spatial and temporal resolution, number of vertical levels and
internal dynamics or physics). Integration of datasets (e.g. to create a long
time series) is encouraged, but these datasets must be clearly documented.

The APPLICATE data management system can consume and expose discovery metadata
provided in GCMD DIF and ISO19115. If ISO19115 is used, GCMD keywords must be
used to describe physical and dynamical parameters. Support for more formats
is being considered. More specifications will be identified early in the
project. As ISO19115 is a container that can be used in many contexts,
APPLICATE promotes the application of the WMO Profile for discovery metadata.
This is based on ISO19115. APPLICATE will be more pragmatic than WMO accepting
records that not fully qualify in all aspects. The dialogue on what is
required will be aligned with the ongoing efforts of the combined SAON /IASC
Arctic Data Committee to ensure integration with relevant scientific
communities.

APPLICATE will integrate with the YOPP Data Portal to make sure that APPLICATE
datasets are discoverable through the YOPP Data Portal. This will be
implemented letting the YOPP Data Portal harvest the relevant discovery
metadata from the APPLICATE data catalogue.

##  Making data openly accessible [fair data]

All discovery metadata will be available through a web based search interface
available through the central project website (applicate.met.no  2  ). Some
data may have temporal access restrictions (embargo period). These will be
handled accordingly.

Valid reasons for an embargo period on data are primarily for educational
reasons, allowing Ph.D. students to prepare and publish their work. Even if
data constrained in the embargo period, data will be shared internally in the
project. Any disagreements on access to data or misuse of data internally are
to be settled by the APPLICATE Executive Board.

Data in the central repository will be made available through a THREDDS Data
Server, activating OPeNDAP support for all datasets and OGC Web Map Service
for visualisation of gridded datasets. Standardisation of data access
interfaces and linkage to the Common Data Model through OPeNDAP  3  is
promoted for all data centres contributing to APPLICATE. This enables direct
access of data within analysis tools like Matlab, Excel  4  and R. Activation
of these interfaces to data are recommended for other contributing data
centres as well.

Metadata and data for the datasets are maintained by the responsible data
centres (including the central data repository). Metadata supporting unified
search is harvested and ingested in the central node (through
applicate.met.no) where it will be made available through human (web
interface) and machine interfaces (OAI-PMH, support for OpenSearch is
considered).

Datasets with restrictions are initially handled by the responsible data
centre. Generally, the metadata will be searchable and contain information on
how to request access to the dataset. An example of a dataset with access
restrictions is the ECMWF YOPP dataset where user registration is required.
Access to information about the dataset does however not require registration

##  Making data interoperable [fair data]

In order to be able to reuse data, standardisation is important. This implies
both standardisation of the encoding/documentation, as well as the interfaces
to the data. Further up in the document, it is referred to documentation
standards widely used by the modelling communities. This includes encoding
model output as NetCDF files, following the Climate and Forecast convention or
the WMO GRIB format. The WMN formats are table driven formats where the tables
identify the content and makes it interoperable. NetCDF files following the CF
convention is self-describing and interoperable. Application of the CF
conventions implies requirements on the structure and semantic annotation of
data (e.g. through identification of variables/parameters through CF standard
names). Furthermore, it requires encoding of missing values etc.

To simplify the process of accessing data, APPLICATE recommends all data
centres to support OPeNDAP. OPeNDAP allows streaming of data and access
without downloading the data as physical files. If OPeNDAP is not supported,
straightforward HTTP access must be supported.

In order to ensure consistency between discovery level and use level metadata,
a system for translation of discovery metadata keywords (i.e. GCMD Science
keywords) to CF Standard names is under development. This implies that e.g.
controlled vocabularies used in the documentation of data may be mapped on the
fly to vocabularies used by other communities. This is in line with current
activities in the SAON/IASC Arctic Data Committee.

##  Increase data re-use (through clarifying licenses) [fair data]

APPLICATE promotes free and open data sharing in line with the Open Research
Data Pilot. Each dataset needs a license attached. The recommendation in
APPLICATE is to use Creative Commons attribution license for data. See
https://creativecommons.org/licenses/by/3.0/ for details.

APPLICATE data should be delivered in a timely manner meaning without un-due
delay. Any delay, due or un-due, shall not be longer than one year after the
dataset is finished. Discovery metadata shall be delivered immediately.

APPLICATE is promoting free and open access to data. Some data may have
constraints (e.g. on access or dissemination) and may be available to members
only initially. Furthermore, some of the data will be used for modelling
development purposes and are thus of limited interest to the broader
community; these data will not be made publicly available. A draft
dissemination plan was outlined in the proposal and is provided in Table 4.
This will be updated as the project progresses.

Table 4: Draft dissemination plan.  
  
<table>  
<tr>  
<th>

Purpose

</th>  
<th>

Model systems

</th>  
<th>

Experimental design

</th>  
<th>

Data

</th> </tr>  
<tr>  
<td>

Determine the impact of model enhancements on process representation and
systematic model error

(WP2)

</td>  
<td>

  * AWI-CM 

  

  * EC-Earth 

  

  * CNRM-CM 

  

  * NorESM 

  

  * HadGEM 

  

</td>  
<td>

Baseline data: CMIP6-DECK experiments

Implement the model changes suggested in WP2 in coupled models: • 200-yr pre-
industrial control experiments • CMIP6 historical experiments •

1% CO 2 increase experiments

</td>  
<td>

Partial Dissemination

</td> </tr>  
<tr>  
<td>

Determine Arctic- lower latitude linkages in atmosphere and ocean

(WP3)

</td>  
<td>

Coupled models

  * AWI-CM 

  

  * EC-Earth 

  

  * CNRM-CM 

  

  * NorESM 

  

  * HadGEM 

  

</td>  
<td>

Large ensembles (50-100 members) of 12-months experiments starting June 1st
with sea ice constrained to observed and projected sea ice fields Multi-
decadal experiments with and without artificially reduced Arctic sea ice
(enhanced downwelling LW radiation over sea ice); use of tracers for the ocean
Repeat with enhanced models

</td>  
<td>

Full Dissemination

</td> </tr>  
<tr>  
<td>

Atmospheric models

  * ECHAM6 

  

  * IFS 

  

  * ARPEGE- Climat 

  

  * CAM-OSLO 

  

  * MetUM 

  

</td>  
<td>

Large ensembles (50-100 members) of 12-months experiments starting June 1st
with sea ice constrained to observed and projected sea ice fields Various
corresponding sensitivity experiments to explore the role of the background
flow, and the prescribed sea ice pattern Repeat with enhanced models

</td>  
<td>

Full Dissemination

</td> </tr> </table>  
<table>  
<tr>  
<th>

</th>  
<th>

Seasonal prediction systems • EC-Earth

• CNRM-CM

</th>  
<th>

Seasonal prediction experiments with and without relaxation of the Arctic
atmosphere towards ERA-Interim reanalysis data: 9-member ensemble forecasts
with members initialized on Nov 1st, Feb 1st, May 1st and Aug 1st for the
years 1979-2016 and 19932016 for EC-Earth and CNRM-CM, respectively.

</th>  
<th>

Full Dissemination

</th> </tr>  
<tr>  
<td>

Arctic observing system development (WP4)

</td>  
<td>

Atmospheric model

• IFS

</td>  
<td>

Data denial experiments with the IFS for key observations (snow, surface
pressure, wind, moisture) and different seasons.

</td>  
<td>

Partial dissemination

</td> </tr>  
<tr>  
<td>

Seasonal prediction

  * EC-Earth 

  

  * HadGEM 

  

  * GloSea 

  

</td>  
<td>

\- Perfect model experiments to characterize basic sensitivity of forecasts to
initial conditions. - Different configurations of initial conditions using
reanalyses, new observations, ocean reruns forced by atmospheric reanalyses. -
Experiments focused on sea-ice thickness, snow and spatial data sampling

</td>  
<td>

Partial dissemination

</td> </tr>  
<tr>  
<td>

Determine the impact of APPLI-

CATE model enhancements on weather and climate prediction

(WP5)

</td>  
<td>

Atmospheric model

  * ARPEGE 

  

  * AROME 

  

  * IFS 

  

  * AROME-Arctic 

  

</td>  
<td>

Test recommendations for model enhancements made in WP2 in pre- operational
configurations Explore the impact of nesting, driving model and resolution

</td>  
<td>

Partial dissemination

</td> </tr>  
<tr>  
<td>

Seasonal prediction

  * EC-Earth 

  

  * CNRM-CM 

  

  * HadGEM 

  

</td>  
<td>

Test recommendations for model enhancements made in WP2 in pre- operational
configurations

</td>  
<td>

Partial dissemination

</td> </tr>  
<tr>  
<td>

</td>  
<td>

Climate change

  * AWI-CM 

  

  * EC-Earth 

  

  * NorESM 

  

  * AWI-CM 

  

</td>  
<td>

Establish the impact of model enhancements developed in WP2 on climate
sensitivity by carrying out experiments using the same initial conditions and
time period (1950—2050) employed in HiResMIP climate sensitivity by carrying
out experiments using the same initial 2050) employed in HiResMIP climate
sensitivity by carrying out experiments using the same initial conditions and
time period

(1950—2050) employed in HiResMIP

</td>  
<td>

Partial dissemination

</td> </tr> </table>

The quality of each dataset is the responsibility of the Principal
Investigator. The Data Management System will ensure the quality of the
discovery metadata and that datasets are delivered according to the format
specifications.

Numerical simulations and analysed products will be preserved for at least 10
years after publication.

#  Allocation of resources

In the current situation, it is not possible to estimate the cost for making
APPLICATE data FAIR. Part of the reason is that this work is relying on
existing functionality at the contributing data centres and that this
functionality has been developed over years. The cost of preparing the data in
accordance with the specifications and initial sharing is covered by the
project. Maintenance of this over time is covered by the business models of
the data centres.

A preliminary list of data centres involved is given in Table 5.

Table 5: As of autumn 2018, the following data centres are contributing to the
APPLICATE project.  
  
<table>  
<tr>  
<th>

Data centre

</th>  
<th>

URL

</th>  
<th>

Contact

</th>  
<th>

Comment

</th> </tr>  
<tr>  
<td>

BSC

</td>  
<td>

https://www.bsc.es/

</td>  
<td>

Pierre-Antoine Bretonniére

</td>  
<td>

</td> </tr>  
<tr>  
<td>

ECMWF

</td>  
<td>

https://www.ecmwf.int

</td>  
<td>

Manuel Fuentes

</td>  
<td>

</td> </tr>  
<tr>  
<td>

DKRZ

</td>  
<td>

http://www.dkrz.de

</td>  
<td>

Thomas Jung

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Norwegian Meteoro-

logical Institute/Arctic

Data Centre

</td>  
<td>

https://applicate.met.no/

</td>  
<td>

Øystein Godøy

</td>  
<td>

This subsystem will provide a unified search interface to all the data
APPLICATE is generating. It will also host data not being hosted by other data
centres contributing to APPLICATE. Metadata interfaces are available, data
interoperability supported using OGC WMS and OPeNDAP. Will integrate relevant
data from WMO GTS.

</td> </tr> </table>

Each data centre is responsible for accepting, managing, sharing and
preserving the relevant datasets. Concerning interoperability interfaces the
following interfaces are required:

  1. Metadata 

    1. OAI-PMH serving either CCMD DIF or the ISO19115 minimum profile with GCMD Science Keywords. Dedicated sets should be available to identify APPLICATE data in large data collections. 

  
  

  

  2. Data (will also use whatever is available and deliver this in original form, for those data no synthesis products are possible without an extensive effort) 

    1. OGC WMS (actual visual representation, not data) 

  

    2. OPeNDAP 

  
  

  

  

In the current situation, long-term preservation of 50 Tb for 10 years is
covered. Volumes to be preserved are still somewhat uncertain and the storage
costs for some of the data produced in the project are covered by other
projects/activities, e.g. the CMIP6 data and operational models. For some of
these data only preservation of minor datasets is required by APPLICATE.

All data that will contribute to CMIP6 will be stored in data centres
contributing to the Earth System Grid Federation (ESGF). APPLICATE data
centres contributing to this will be shown in the table above. For APPLICATE,
the experiments contributing to the Polar Amplification Model Intercomparison
Project (PA-MIP) will be managed in a ESGF data centre.

#  Data security

Data security relies on the existing mechanisms of the contributing data
centres. APPLICATE recommends ensuring the communication between data centres
and users with secure HTTP. Concerning the internal security of the data
centre, APPLICATE recommends the best practises from OAIS. The technical
solution will vary between data centres, but most data centres have solutions
using automated check sums and replication.

The central node relies on secure HTTP, but not all contributing data centres
support this yet.

#  Ethical aspects

APPLICATE is not concerned with ethical sensitive data and follows the
guidance of the IASC Statement of Principles and Practises for Arctic Data
Management.

#  Other

APPLICATE is linked to WMO’s Year of Polar Prediction activity. In this
context APPLICATE is relating to the WMO principles for data management
identified through the WMO Information System.