Implementation of a reproducible pipeline for forecasting sea ice - snapshot
type: FAIRDigitalObject
type: RoCrateNanopub
created: 2026-05-11T16:09:31.314+02:00
creator: RoCrateBot
type: Nanopublication
has assertion: assertion
has provenance: provenance
has publication info: pubinfo

sig
has algorithm: RSA
signed by: RoCrateBot

Applied sciences
type: DefinedTerm

Anne Fouilloux
type: Agent
affiliation: Simula Research Laboratory
orcid: 0000-0002-1784-2920

Jean Iaquinta
type: Agent
orcid: 0000-0002-8763-1643

forecasting sea ice
type: Phrase
norm score: 25.628140703517587
score: 35.7

Climate change
type: IPTC
path: Environment/Climate change

Arctic Zone
type: Place
wikidata: https://www.wikidata.org/wiki/Q25322

Einet Galaxy
type: Lemma
norm score: 5.8225508317929755
score: 6.3

motivation involvement
type: Phrase
norm score: 5.455850681981334
score: 7.6

work
type: Lemma
norm score: 6.284658040665434
score: 6.8

motivation
type: Lemma
norm score: 5.545286506469501
score: 6.0

EGU
type: Lemma
norm score: 7.024029574861368
score: 7.6

impact
type: Concept
norm score: 6.800286327845384
score: 9.5

environment
type: Concept
norm score: 5.511811023622048
score: 7.7

geophysics
type: NASA
norm score: 63.38268230536455
score: 0.8625994324684143

job market
type: Domain
norm score: 15.053763440860214
score: 1.4

Wireless technology
type: IPTC
path: Economy, business and finance/Economic sector/Computing and information technology/Wireless technology

forecast
type: Lemma
norm score: 5.730129390018484
score: 6.2

work
type: Concept
norm score: 5.368647100930566
score: 7.5

pipeline
type: Concept
norm score: 6.657122405153903
score: 9.3

Science and technology
type: IPTC
path: Science and technology

motivation
type: Concept
norm score: 5.440229062276307
score: 7.6

Research Object
type: Lemma
norm score: 6.3770794824399255
score: 6.9

motivation impact
type: Phrase
norm score: 10.768126346015793
score: 15.0

sociology
type: Domain
norm score: 15.053763440860214
score: 1.4

IceNet
type: Lemma
norm score: 7.116451016635859
score: 7.7

software
type: Domain
norm score: 17.204301075268816
score: 1.6

pipeline
type: Lemma
norm score: 8.13308687615527
score: 8.8

oceanography
type: NASA
norm score: 36.61731769463545
score: 0.4983392357826233

forecast
type: Concept
norm score: 13.958482462419472
score: 19.5

Unsplash
type: Lemma
norm score: 4.621072088724584
score: 5.0

Galaxy http
type: Phrase
norm score: 10.409188801148598
score: 14.5

deep learning probabilistic sea ice forecasting outperforms dynamical models
type: Sentence
norm score: 7.884097035040431
score: 11.7

implementation
type: Lemma
norm score: 6.1922365988909425
score: 6.7

Earth Modeling
type: Phrase
norm score: 7.753050969131371
score: 10.8

approach PANGEO
type: Phrase
norm score: 14.142139267767407
score: 19.7

photo
type: Concept
norm score: 3.3643521832498213
score: 4.7

sea ice
type: Concept
norm score: 18.396564065855404
score: 25.7

Motivation impacts exceed local environments, populations and economies need for climate change research accurate seasonal Arctic sea ice forecasts with IceNet:
type: Sentence
norm score: 18.059299191374663
score: 26.8

http
type: Concept
norm score: 11.52469577666428
score: 16.099999999999998

sea ice forecasting
type: Phrase
norm score: 8.542713567839195
score: 11.9

research
type: Concept
norm score: 3.937007874015748
score: 5.5

Internet
type: Domain
norm score: 31.18279569892473
score: 2.9

Einet Galaxy
type: Concept
norm score: 5.440229062276307
score: 7.6

physical geography and environmental geoscience
type: FieldOfResearch
norm score: 100.0
score: 1.9435470700263977

sea ice
type: Lemma
norm score: 20.794824399260627
score: 22.5

abstraction
type: Concept
norm score: 3.937007874015748
score: 5.5

Implementation of a reproducible pipeline for forecasting sea ice - snapshot
type: ResearchObject
type: SnapshotRO
type: Dataset
type: ExecutableResearchObject
doi: 10.24424/vpkn-k902
is finalized: False
is snapshot of: https://w3id.org/ro-id/aab53e25-a351-46b0-bcfe-a0e0bf02f881
snapshoted at time: 2024-04-19 13:34:23.698072+00:00
snapshoted by: Anne Fouilloux
about: Applied sciences
content size: 71504702
contributor: Anne Fouilloux
contributor: Jean Iaquinta
creator: Anne Fouilloux
date created: 2024-04-09 18:50:15.660054+00:00
date modified: 2024-04-19 13:35:30.077318+00:00
date published: 2024-04-09 18:50:15.660054+00:00
description: This Research Object corresponds to the work done by Vanessa Stoeckl, and presented as a poster at EGU 2024, ESSI 2.9 "Seamless transitioning between HPC and cloud in support of Earth Observation, Earth Modeling and community-driven Geoscience approach PANGEO". - Abstract submitted and accepted at EGU: [https://doi.org/10.5194/egusphere-egu24-8343](https://doi.org/10.5194/egusphere-egu24-8343) - [Rendered Jupyter notebook](https://edsbook.org/notebooks/gallery/ac327c3a-5264-40a2-8c6e-1e8d7c4b37ef/notebook) - [Galaxy workflow showcasing the pipeline for forecasting sea ice](https://usegalaxy.eu/u/vstoeckl/w/icenet)
encoding format: application/ld+json
license: no-permission
name: Implementation of a reproducible pipeline for forecasting sea ice
creation mode: MANUAL
domain: job market
domain: sociology
domain: software
domain: Internet
domain: computer science
organization: National Oceanic and Atmospheric Administration
place: Arctic Zone
concept: impact
concept: environment
concept: work
concept: pipeline
concept: motivation
concept: forecast
concept: photo
concept: sea ice
concept: http
concept: research
concept: Einet Galaxy
concept: abstraction
concept: implementation
concept: workflow
concept: poster
field of research: physical geography and environmental geoscience
field of research: earth sciences
IPTC: Climate change
IPTC: Wireless technology
IPTC: Science and technology
IPTC: Oil and gas - upstream activities
IPTC: Hardware
IPTC: Weather
lemma: Einet Galaxy
lemma: work
lemma: motivation
lemma: EGU
lemma: forecast
lemma: Research Object
lemma: IceNet
lemma: pipeline
lemma: Unsplash
lemma: implementation
lemma: sea ice
lemma: http
lemma: environment
NASA: geophysics
NASA: oceanography
NASA: geosciences
phrase: forecasting sea ice
phrase: motivation involvement
phrase: motivation impact
phrase: Galaxy http
phrase: Earth Modeling
phrase: approach PANGEO
phrase: sea ice forecasting
phrase: reproducible pipeline
phrase: Galaxy workflow
sentence: deep learning probabilistic sea ice forecasting outperforms dynamical models

Vanessa Stoeckl
type: Agent

Alejandro Coca-Castro
type: Agent
affiliation: The Alan Turing Institute

Björn Grüning
type: Agent

tool
type: Folder
type: Dataset

biblio
type: Folder
type: Dataset

output
type: Folder
type: Dataset

input
type: Folder
type: Dataset

Galaxy Workflow IceNet sea-ice forecasting
type: Resource
type: MediaObject
type: ComputationalWorkflow
author: Anne Fouilloux
creator: Anne Fouilloux
date created: 2024-04-09 18:52:16.320626+00:00
date modified: 2024-04-19 13:34:22.939052+00:00
description: Galaxy workflow on the Galaxy Europe instance. To execute it, you would need first to get an account on Galaxy Europe (free of charge) and prepare the input dataset.
keywords: galaxy
license: no-permission
sd date published: 2024-04-09 18:52:16.320626+00:00

The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update
type: Paper
type: Resource
type: MediaObject
author: Anne Fouilloux
creator: Anne Fouilloux
date created: 2024-04-09 18:59:25.010332+00:00
date modified: 2024-04-19 13:34:23.594734+00:00
description: Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.
keywords: galaxy-platform
license: no-permission
sd date published: 2024-04-09 18:59:25.010332+00:00

Poster EGU 2024 (pdf)
type: Resource
type: MediaObject
type: Poster
author: Anne Fouilloux
content size: 772547
creator: Anne Fouilloux
date created: 2024-04-09 19:02:15.319953+00:00
date modified: 2024-04-19 13:34:19.301131+00:00
description: Poster EGU 2024 (pdf) Implementation of a reproducible pipeline for producing seasonal Arctic sea ice forecasts
encoding format: application/pdf
keywords: Poster
license: no-permission
sd date published: 2024-04-09 19:02:15.319953+00:00

Presentation
type: Resource
type: MediaObject
type: VideoObject
doi: 10.24424/tckn-et23
content size: 323417298
date created: 2024-04-12 19:22:32.134693+00:00
date modified: 2024-04-19 13:34:23.287670+00:00
encoding format: video/mp4
license: no-permission
sd date published: 2024-04-12 19:22:32.134693+00:00

sketch (based on the poster)
type: Sketch
type: Resource
type: MediaObject
author: Anne Fouilloux
content size: 1260982
creator: Anne Fouilloux
date created: 2024-04-11 11:31:09.064376+00:00
date modified: 2024-04-19 13:34:22.725438+00:00
description: Sketch used in RoHub to illustrate the Research Object created for the poster at EGU 2024.
encoding format: image/png
license: no-permission
sd date published: 2024-04-11 11:31:09.064376+00:00

Presentation slides
type: Document
type: Resource
type: MediaObject
content size: 1473306
date created: 2024-04-12 19:24:37.138056+00:00
date modified: 2024-04-19 13:34:20.251203+00:00
encoding format: application/pdf
license: no-permission
sd date published: 2024-04-12 19:24:37.138056+00:00

Abstract EGU24-8343 (poster)
type: Resource
type: MediaObject
type: ConferencePaper
author: Anne Fouilloux
creator: Anne Fouilloux
date created: 2024-04-09 18:57:09.049029+00:00
date modified: 2024-04-19 13:34:20.491838+00:00
description: EGU abstract submitted.
license: no-permission
sd date published: 2024-04-09 18:57:09.049029+00:00

Sea ice forecasting using IceNet (Jupyter Notebook) published in the Environmental Data Science book
type: ResearchObject
type: Resource
type: MediaObject
author: Anne Fouilloux
creator: Anne Fouilloux
date created: 2024-04-09 18:54:45.057065+00:00
date modified: 2024-04-19 13:34:22.131841+00:00
description: Research Object with the Jupyter Notebook showcasing Sea ice forecasting in the Environmental Data Science book [https://edsbook.org/welcome.html](https://edsbook.org/welcome.html)
license: no-permission
sd date published: 2024-04-09 18:54:45.057065+00:00

Oil and gas - upstream activities
type: IPTC
path: Economy, business and finance/Economic sector/Energy and resource/Oil and gas - upstream activities

http
type: Lemma
norm score: 10.720887245841034
score: 11.6

implementation
type: Concept
norm score: 5.082319255547603
score: 7.1

reproducible pipeline
type: Phrase
norm score: 10.050251256281406
score: 14.0

Hardware
type: IPTC
path: Economy, business and finance/Economic sector/Computing and information technology/Hardware

computer science
type: Domain
norm score: 21.50537634408602
score: 2.0

Weather
type: IPTC
path: Weather

Implementation of a reproducible pipeline for forecasting sea ice.
type: Sentence
norm score: 19.20485175202156
score: 28.5

earth sciences
type: FieldOfResearch
norm score: 100.0
score: 1.9435470700263977

geosciences
type: NASA
norm score: 36.61731769463545
score: 0.4983392357826233

Galaxy workflow
type: Phrase
norm score: 7.2505384063173
score: 10.1

Implementation of a reproducible pipeline for forecasting sea ice
type: Sentence
norm score: 6.738544474393531
score: 10.0

workflow
type: Concept
norm score: 2.43378668575519
score: 3.4

https://w3id.org/ro-id/ebc9dc8b-2cab-49c1-84ad-7db71b8e5250
type: Sentence
name: This Research Object corresponds to the work done by Vanessa Stoeckl, and presented as a poster at EGU 2024, ESSI 2.9 "Seamless transitioning between HPC and cloud in support of Earth Observation, Earth Modeling and community-driven Geoscience approach PANGEO". - Abstract submitted and accepted at EGU: [https://doi.org/10.5194/egusphere-egu24-8343](https://doi.org/10.5194/egusphere-egu24-8343) - [Rendered Jupyter notebook](https://edsbook.org/notebooks/gallery/ac327c3a-5264-40a2-8c6e-1e8d7c4b37ef/notebook) - [Galaxy workflow showcasing the pipeline for forecasting sea ice](https://usegalaxy.eu/u/vstoeckl/w/icenet)
norm score: 48.113207547169814
score: 71.4

poster
type: Concept
norm score: 2.1474588403722263
score: 3.0

geosciences
type: NASA
norm score: 63.38268230536455
score: 0.8625994324684143

National Oceanic and Atmospheric Administration
type: Organization
wikidata: https://www.wikidata.org/wiki/Q214700

environment
type: Lemma
norm score: 5.6377079482439925
score: 6.1