From f71a54f2d858136d0794464442a05f9084cae207 Mon Sep 17 00:00:00 2001 From: j-atkins <106238905+j-atkins@users.noreply.github.com> Date: Fri, 16 Jan 2026 11:20:41 +0100 Subject: [PATCH 1/2] adapt manuscript to new JOSS scope requirements --- docs/paper/jats/paper.jats | 42 +++++++++++++++++++++---------------- docs/paper/paper.md | 16 +++++++------- docs/paper/paper.pdf | Bin 2950351 -> 2952983 bytes 3 files changed, 33 insertions(+), 25 deletions(-) diff --git a/docs/paper/jats/paper.jats b/docs/paper/jats/paper.jats index 757f87d5..7eb8abd5 100644 --- a/docs/paper/jats/paper.jats +++ b/docs/paper/jats/paper.jats @@ -173,9 +173,6 @@ a Creative Commons Attribution 4.0 International License (CC BY Facilities Planning (MFP) tool, giving users the option to define expedition waypoints via an intuitive web-based mapping interface.
- -The software can simulate complex multidisciplinary expeditions. One example is a virtual expedition across the Agulhas Current and the South Eastern Atlantic that deploys a suite of instruments to sample @@ -257,19 +257,6 @@ a Creative Commons Attribution 4.0 International License (CC BY
A full example workflow is outlined in the
Example VirtualShip expedition simulated in July/August
- 2023. Expedition waypoints displayed via the MFP tool (a), Underway
- ADCP measurements (b), Surface drifter releases (c; 90-day lifetime
- per drifter), and CTD vertical profiles for temperature (d) and
- oxygen (e). Black triangles in b), d) and e) mark waypoint locations
- across the expedition route, corresponding to the purple markers in
- a).
Under the hood,
Example VirtualShip expedition simulated in July/August
+ 2023. Expedition waypoints displayed via the MFP tool (a), Underway
+ ADCP measurements (b), Surface drifter releases (c; 90-day lifetime
+ per drifter), and CTD vertical profiles for temperature (d) and
+ oxygen (e). Black triangles in b), d) and e) mark waypoint locations
+ across the expedition route, corresponding to the purple markers in
+ a).
Generative AI technologies (Gemini v2.0/2.5/3.0, ChatGPT + v4o/5.0/5.1/5.2 and GitHub Copilot) were used for code generation, + refactoring and test scaffolding. AI-assisted autocompletion tools + (via GitHub Copilot) were used in the writing of this manuscript. + Authors carefully reviewed and edited all AI-assisted content and made + the core desigin decisions.
+The VirtualShip project is funded through the Utrecht
diff --git a/docs/paper/paper.md b/docs/paper/paper.md
index 90cba6e9..29399259 100644
--- a/docs/paper/paper.md
+++ b/docs/paper/paper.md
@@ -47,10 +47,10 @@ Marine science relies on fieldwork for data collection, yet sea-going opportunit
`VirtualShip` goes beyond simply extracting grid-cell values from model output. Instead, it uses programmable behaviours and sophisticated interpolation techniques (with `Parcels` underpinnings) to access data in exact locations and timings, as if they were being collected by real-world instruments. `VirtualShip` shares some functionality with existing tools, such as `OceanSpy` [@Almansi2019] and `VirtualFleet` [@Maze2023], but extends capabilities to mesh many different instrument deployments into a unified expedition simulation framework. Moreover, `VirtualShip` exploits readily available, streamable data via the Copernicus Marine Data Store, removing the need for users to download and manage large datasets locally and/or arrange for access to remote servers. `VirtualShip` can also integrate coordinate files exported from the [Marine Facilities Planning](https://www.marinefacilitiesplanning.com/cruiselocationplanning#) (MFP) tool, giving users the option to define expedition waypoints via an intuitive web-based mapping interface.
-# Functionality
-
`VirtualShip` simulates the deployment of virtual instruments commonly used in oceanographic fieldwork, with emphasis on realism in how users plan and execute expeditions. For example, users must consider ship speed and instrument deployment/recovery times to ensure their expedition is feasible within given time constraints. Possible instrument selections include surface `Drifter` [@Lumpkin2017], `CTD` (Conductivity-Temperature-Depth; @Johnson2007), `Argo float` [@Jayne2017], `XBT` (Expendable Bathythermograph; @Goni2019), underway `ADCP` (Acoustic Doppler Current Profiler; @Kostaschuk2005), and underway `temperature/salinity` [@Gordon2014] probes. More detail on each instrument is available in the [documentation](https://virtualship.readthedocs.io/en/latest/user-guide/assignments/Research_proposal_intro.html#Measurement-Options).
+# Software design
+
The software can simulate complex multidisciplinary expeditions. One example is a virtual expedition across the Agulhas Current and the South Eastern Atlantic that deploys a suite of instruments to sample physical and biogeochemical properties (\autoref{fig:fig1}). Key circulation features appear early in the expedition track, with enhanced ADCP speeds marking the strong Agulhas Current (\autoref{fig:fig1}b) and drifters that turn back toward the Indian Ocean indicating the Agulhas Retroflection (\autoref{fig:fig1}c). The CTD profiles capture the vertical structure of temperature and oxygen along the route, including the warmer surface waters of the Agulhas region (\autoref{fig:fig1}d, early waypoints) and the Oxygen Minimum Zone in the South Eastern Atlantic (\autoref{fig:fig1}e, final waypoints).
The software is designed to be highly intuitive to the user. It is wrapped into three high-level command line interface commands using [Click](https://click.palletsprojects.com/en/stable/):
@@ -61,15 +61,13 @@ The software is designed to be highly intuitive to the user. It is wrapped into
A full example workflow is outlined in the [Quickstart Guide](https://virtualship.readthedocs.io/en/latest/user-guide/quickstart.html) documentation.
-
-
-# Implementation
-
Under the hood, `VirtualShip` is modular and extensible. The workflows are designed around `Instrument` base classes and instrument-specific subclasses and methods. This means the platform can be easily extended to add new instrument types. Instrument behaviours are coded as `Parcels` kernels, which allows for extensive customisability. For example, a `Drifter` advects passively with ocean currents, a `CTD` performs vertical profiling in the water column and an `ArgoFloat` cycles between ascent, descent and drift phases, all whilst sampling physical and/or biogeochemical fields at their respective locations and times.
Moreover, the data ingestion system relies on Analysis-Ready and Cloud-Optimized data (ARCO; @Stern2022, @Abernathey2021) streamed directly from the Copernicus Marine Data Store, via the [`copernicusmarine`](https://github.com/mercator-ocean/copernicus-marine-toolbox) Python toolbox. This means users can simulate expeditions anywhere in the global ocean without downloading large datasets by default. Leveraging the suite of [physics and biogeochemical products](https://virtualship.readthedocs.io/en/latest/user-guide/documentation/copernicus_products.html) available on the Copernicus plaform, expeditions are possible from 1993 to present and forecasted two weeks into the future. There is also an [option](https://virtualship.readthedocs.io/en/latest/user-guide/documentation/pre_download_data.html) for the user to specify local `NetCDF` files for data ingestion, if preferred.
-# Applications and future outlook
+
+
+# Research impact statement
`VirtualShip` has already been extensvely applied in Master's teaching settings at Utrecht University as part of the [VirtualShip Classroom](https://www.uu.nl/en/research/sustainability/sustainable-ocean/education/virtual-ship) initiative. Educational assignments and tutorials have been developed alongside to integrate the tool into coursework, including projects where students design their own research question(s) and execute their fieldwork and analysis using `VirtualShip`. Its application has been shown to be successful, with students reporting increased self-efficacy and knowledge in executing oceanographic fieldwork [@Daniels2025].
@@ -77,6 +75,10 @@ The package opens space for many other research applications. It can support rea
Both the customisability of the `VirtualShip` platform and the exciting potential for new ARCO-based data hosting services in domains beyond oceanography (e.g., [atmospheric science](https://climate.copernicus.eu/work-progress-our-data-stores-turn-arco)) means there is potential to extend VirtualShip (or "VirtualShip-like" tools) to other domains in the future. Furthermore, as the `Parcels` underpinnings themselves continue to evolve, with a future (at time of writing) [v4.0 release](https://docs.oceanparcels.org/en/v4-dev/v4/) focusing on alignment with [Pangeo](https://pangeo.io/) standards and `Xarray` data structures [@Hoyer2017], `VirtualShip` will also benefit from these improvements, further enhancing its capabilities, extensibility and compatability with modern cloud-based data pipelines.
+# AI usage disclosure
+
+Generative AI technologies (Gemini v2.0/2.5/3.0, ChatGPT v4o/5.0/5.1/5.2 and GitHub Copilot) were used for code generation, refactoring and test scaffolding. AI-assisted autocompletion tools (via GitHub Copilot) were used in the writing of this manuscript. Authors carefully reviewed and edited all AI-assisted content and made the core desigin decisions.
+
# Acknowledgements
The VirtualShip project is funded through the Utrecht University-NIOZ (Royal Netherlands Institute for Sea Research) collaboration.
diff --git a/docs/paper/paper.pdf b/docs/paper/paper.pdf
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