Oceanography | Early Online Release
OCEAN EDUCATION
OceanHackWeek
AN INCLUSIVE, COLLABORATIVE APPROACH TO DEVELOPING
OCEANOGRAPHY DATA SCIENCE SKILLS
By Catherine Mitchell, Wu-Jung Lee, Filipe Fernandes, Joseph Gum, Alex Kerney, Emilio Mayorga,
Thomas Moore, Nick Mortimer, Natalia Ribeiro, and Valentina Staneva.
INTRODUCTION
Oceanography relies on a wide range of observational platforms,
sampling strategies, and experimental and modeling approaches
to drive discovery and deepen our understanding of the ocean’s
role in the Earth system (Lee et al., 2017; McMahon et al., 2021).
Over the past few decades, there has been a significant increase in
both the volume and variety of oceanographic data (Tanhua et al.,
2019; Brett et al., 2020). Advancements in computational power
over the last decade have further enhanced the efficacy of models,
fueling a surge in modeling studies (Stewart and Thompson, 2015;
Morrison et al., 2020; Huneke et al., 2022). As a result, compu-
tational methods and resources are becoming essential tools in
oceanography (Reichstein et al., 2019; Robinson et al., 2020), with
numerous examples of advanced computational usage across the
field (Hemming et al., 2020; Kiss et al., 2020; Chapman et al., 2022;
Roughan et al., 2022).
Despite these advancements, ocean science courses have tra-
ditionally focused on domain-specific knowledge, often lacking
comprehensive training in computational skills (Campbell et al.,
2024). Though introductory-level data science training is increas-
ingly being incorporated into oceanography curricula, students
and researchers are left with significant gaps in advanced computa-
tional skills (Greengrove et al., 2020; McGovern and Allen, 2021).
The education and equipment required to develop these computa-
tional skills can be expensive and time consuming (Barber et al.,
2023), with marginalized students often forced to forgo training
opportunities and internships (Kreuser et al., 2023). Scientific pro-
gramming skills, particularly the ability to collaborate effectively
on computational projects, are highly valuable in both academic
and non-lab-work environments (McNutt, 2014).
OceanHackWeek was established in 2018 with three core
goals: (1) to provide a pathway for ocean scientists to acquire
the computational and data science skills necessary for advanc-
ing modern data-intensive oceanographic research; (2) to foster
an open and sharing culture among ocean science research-
ers, spanning a wide range of technical expertise, career stages,
educational backgrounds, and personal experiences; and
(3) to promote open science, reproducible research practices,
and adherence to FAIR (findable, accessible, interoperable,
reusable) data principles. Open, reproducible science encourages
greater inclusivity, enabling broader participation from research-
ers worldwide and creating opportunities to engage in ground-
breaking science, regardless of institutional affiliations or finan-
cial resources (Martin et al., 2025). In this paper, we focus our
main discussion on the OceanHackWeek event, with details on
the organization of OceanHackWeek provided in the online
Supplementary Materials.
THE OCEANHACKWEEK WORKSHOP
The hackweek model (Duncombe, 2018; Huppenkothen et al.,
2018; Rokem and Benson, 2024) was designed to fill a gap between
traditional summer schools, which are typically instructor-led
ABSTRACT. Over the last two decades, there has been an explosion of oceanographic data from a broad array of ocean observ-
ing platforms, as well as dramatic improvements in the ability of ocean models to resolve processes across multiple temporal and spa-
tial scales. Ocean researchers’ ability to leverage computing tools and resources are key to effectively understanding and monitoring
our ocean, the marine ecosystems it supports, and the response of the Earth system to climate change. Therefore, data science skills
have become essential in the scientific discovery process, and it is becoming increasingly important to have computational skills in our
research toolbox. OceanHackWeek was launched in 2018 to build an inclusive community that promotes data and software proficiency
in oceanography. With a mission to meet, collaborate, and learn at the intersection of ocean and data sciences, OceanHackWeek pro-
vides a vibrant, diverse, and inclusive community that embodies the vision of an open ocean science future. In this article we present the
OceanHackWeek model, provide an overview of the curriculum and formats of the events, and discuss the lessons learned and recom-
mendations for implementing an OceanHackWeek-style event.
Early Online Release | Oceanography
lessons, and hackathons, collaborative events focused on a specific
problem. Hackweeks combine instructor-led tutorials and collabo-
rative project work that enables peer learning (Figure 1).
OceanHackWeek originated as an adaptation of this hackweek
model and is typically run as a five-day workshop that is a bal-
ance between tutorials and project work. The design and scope of
the OceanHackWeek event has evolved since its inception, becom-
ing broader and more inclusive over time with the introduc-
tion of a virtual option and multiple in-person events in differ-
ent locations run concurrently—see Supplementary Table S1 and
details of OceanHackWeek en Español in Martin et al. (2025). The
OceanHackWeek approach emphasizes the value of both scientific
research and software contributions, recognizing that science and
software development are interconnected forces that drive prog-
ress. Diversity is essential in this process, that is, bringing together
individuals with varied backgrounds and insights to enrich the
research, foster innovation, and create stronger solutions. To
ensure broader participation and inclusivity, OceanHackWeek
is run at no, or very minimal cost, to the participants. Thanks
to the generous support of our sponsors (see list provided in the
Acknowledgments section), and the time volunteered by many of
the organizers, instructors, and mentors, we have no registration
fees, provide accommodation free-of-charge, and subsidize travel
and meal costs.
SOFTWARE AND INFRASTRUCTURE
OceanHackWeek uses both the Python and R programming lan-
guages. Initially, the focus was on Python due to its growing prom-
inence in oceanographic research and the broader geosciences
(Irving, 2019; Esmaili, 2021), but R was later included, recogniz-
ing its importance in ecological and biological research (Lai et al.,
2019). We embraced both Python and R because (1) the core com-
puting and data analysis ideas are independent of and transfer-
able between programming languages, (2) many software tools are
language-specific and flexibility in switching between languages is
advantageous, and (3) working alongside others with expertise in
a different language can be inspiring and facilitates collaboration
across ocean science sub-domains.
OceanHackWeek has relied on customized JupyterHub deploy-
ments hosted on commercial cloud services since its inception,
providing a shared platform accessible to all participants through
a web browser, in the form of JupyterLab and RStudio interfaces.
TIME (EDT)
MONDAY
TUESDAY
WEDNESDAY
THURSDAY
FRIDAY
0830 - 0900
Welcome, Logistics
Tutorial: Git Primer
Project Standup
Project Standup
Project Standup
0900 - 0915
Introduction +
Code of Conduct +
Icebreaker
Project Setup
(finalize project
selection, then create
plans and Git repo for
each project)
Tutorial: AI-Assisted
Programming
Tutorial: R Application
(species distribution
modeling)
Updates /
Check-Out Information
0915 - 0930
Project Work /
Wrap-Up
0930 - 0945
0945 - 1000
Tutorial: Reproducible
Work and Managing
Projects
1000 - 1015
AI Use Case Discussion
1015 - 1030
Break
1030 - 1045
Break
Break
Break
Project Work
1045 - 1100
Introduction to Projects
Tutorial: Data Access
Tutorial: Stresses in the
Geosciences
1100 - 1115
Project Ideation Step 1
(solo and neighbor
discussion)
1115 - 1130
1130 - 1145
Project Ideation Step 2
(full group, stickies,
and flipboards)
1145 - 1200
Project Work
Discussion
1200 - 1300
Lunch
Lunch
Lunch
Lunch
Lunch
1300 - 1400
Tutorial: Conda and
JupyterHub
Tutorial: xarray
Tutorial: Deep Learning
Project Work
Project Wrap-Up
1400 - 1430
Project Slide /
Pitch Workup
Tutorial: Data
Visualization
Project Work
1430 - 1500
Project Presentations
Round 1
1500 - 1530
Project Pitching
Project Work
1530 - 1600
Snacks and Feedback /
Post-Workshop Survey
1600 - 1630
Project Presentations
Round 2
1630 - 1700
Group Activity
FIGURE 1. Example schedule from the 2024 OceanHackWeek workshop. General activities are in gray, tutorials are in orange, discussions are in green, and
project related activities are in blue.
Oceanography | Early Online Release
The platform is provisioned with the software libraries and
resources used in the tutorials and light project work and thus pro-
vides a consistent environment to all participants.
OceanHackWeek uses GitHub for access to the JupyterHub,
sharing of tutorial materials, and collaborative project work. In
addition, we use Slack as a communication platform for all event
types (in-person, virtual, and hybrid). Each project has a dedicated
Slack channel and a GitHub repository, and there are Slack chan-
nels for sharing logistics and coding help. A video conferencing
platform is necessary for virtual and hybrid events, but we disable
the chat feature of these platforms and direct all communication
through Slack, in a tutorial Q&A channel.
CURRICULUM OVERVIEW
Figure 1 shows a typical schedule for a five-day OceanHackWeek
workshop, beginning with tutorials and project team forma-
tion; project time increases as the week progresses. In the early
years, our tutorials focused on accessing data from ocean observ-
ing networks (e.g., the Ocean Observatories Initiative and the
US Integrated Ocean Observing System) or specific software
libraries for data manipulation and visualization (such as Python’s
xarray). Since 2023, we have included tutorials that demonstrate
data analysis challenges associated with research questions and
provide participants with a broader overview on how to approach
a computational research project. A list of the past tutorials is pro-
vided in Table S2, with the majority of these available on GitHub
and in recordings on our YouTube channel.
In addition to programming tutorials, we engage participants
in sessions on broad, culturally oriented topics including code
of conduct in collaborative research, reproducible and replicable
research, and open science challenges and ethics, and we host an
open discussion session on mental health in climate science. These
sessions are important for cultivating an inclusive, collaborative,
and open culture.
PROJECTS
Group-based “hack” projects are a crucial component of
OceanHackWeek, with learning and collaboration as the goal,
rather than complete project solutions. Participants are encour-
aged to propose (“pitch”) a project and form a project team with
other participants. Project goals and individual contributions are
negotiated and adjusted throughout the week as challenges arise
and time progresses. The week concludes with presentations from
each project group, where participants are asked to explain what
was accomplished and what lessons were learned, regardless of the
original objectives.
Due to the organic nature of project formation, the proj-
ect groups tend to be diverse in terms of skill levels and domain
knowledge. We encourage this, as we have found it results in
peer-to-peer learning, with tasks distributed within the team to
the appropriate participants. Those with higher coding skill lev-
els often practice their teaching skills by helping others in their
group; likewise, participants with a deeper background in the
project’s science goals or relevant data sources often provide crit-
ical guidance to the group. The group-based setting of the hack
projects aims to foster an open and collaborative scientific pro-
cess, with participants encouraged to continue using these
approaches in their work beyond OceanHackWeek. Box 1 shows
examples of two OceanHackWeek projects that demonstrate
the breadth of the projects. All projects are accessible from the
OceanHackWeek website.
APPLICATIONS AND
PARTICIPANT SELECTION
We have strived to build a diverse cohort with outreach to appli-
cants from underrepresented groups through institutional,
national, and international mailing lists; minority-led societies;
and social media. Applications are open to all, but participants
are expected to have some experience with Python and/or R.
Participants are typically graduate students, but we welcome (and
have had) participants from all academic stages, as well as from
outside of academia. Over the years we have honed our selec-
tion process, settling on a holistic approach to reduce bias and
the impact of disparities among applicants that arise from differ-
ent backgrounds and opportunities (Huppenkothen et al., 2020;
Young et al., 2022). Holistic reviews consider a broad range of cri-
teria but minimize dependence on quantitative metrics (such as
grade point averages for graduate school admissions) and put a
greater emphasis on skills, experiences, and personal attributes
(Megginson, 2009; Wilson et al., 2019). In our participant selec-
tion, we focus on three categories: motivation (why does an appli-
cant want to participate), impact (what impact OceanHackWeek
would have on an applicant’s research interests and beyond), and
ability to work in a team. In 2024, we followed the approach of
Rotjan et al. (2023), with participants classified as either eligible
or ineligible to attend OceanHackWeek, and final participants
selected randomly from the eligible pool. In prior years, partici-
pants were ranked, with places offered to the highest scoring appli-
cants. We have found the holistic approach to reviewing applicants
helps reduce our biases, and coupled with a purposeful outreach,
helps OceanHackWeek achieve a diverse cohort.
EVALUATION OF THE PROGRAM
AND LESSONS LEARNED
OceanHackWeek conducts a post-workshop survey to assess the
success of the workshop and identify areas for improvement. The
individual survey responses are confidential, so we present the
collective lessons we have learned from seven years of surveys as
well as conversations with participants, instructors, mentors, and
organizing committee members. The participant testimonials and
alumni stories provided in the Supplementary Material demon-
strate the value of the program to these participants, particularly
regarding OceanHackWeek’s community-building, positive atmo-
sphere, and the group projects.
Early Online Release | Oceanography
FIGURE B1-2. A screenshot from the video of the turtle detection project presentation identifies turtles
detected in the drone imagery. Click on the video icon to view the full video.
colocate
The colocate module started as an OceanHackWeek project in
2019 and is now a module managed by the US Integrated Ocean
Observing System. The project was created to leverage the efforts
of many groups by serving valuable data via common ERDDAP
interfaces and a community-maintained index of such servers
and enabling a single set of search criteria to be applied across
servers. This module has a user interface that is used to search
ERDDAP servers in order to locate all oceanographic data within a
given region over a set time period (Figure B1-1).
BOX 1. EXAMPLE PROJECTS
Turtle Detection Using
Deep Learning
The 2021 Turtle Detection Using Deep
Learning project used an established
neural network segmentation model to
identify turtles in videos taken by drones.
This project demonstrates the power of a
diverse team, with someone providing the
dataset and scientific knowledge behind
it, some team members supplying exper-
tise in data wrangling, and others offering
experience working with neural networks.
Together, in a short period of time, they
successfully built a model that identified
turtles (Figure B1-2).
41°N —
40°N —
39°N —
38°N —
37°N —
36°N —
78°W
76°W
72°W
74°W
70°W
68°W
FIGURE B1-1. Results from a colocate search. Different colored lines show
where available data have been found. Figure created from code available in
the colocate module.
PARTICIPATION AND ENGAGEMENT ACROSS
EVENT FORMATS
A virtual option for OceanHackWeek enabled the participation
of a more diverse and global community. Table S1 shows partici-
pant demographics for each workshop, with larger percentages of
gender and ethnic/racial minorities, as well as international par-
ticipants, in the years conducted as fully virtual or hybrid events.
Participants appreciated the virtual option, but despite the positive
feedback we received regarding the virtual/hybrid model, in the
last two years there was less interest in participating virtually, sug-
gesting that participants currently prefer in-person interactions
and workshops.
Further, planning and running a hybrid workshop that aims to
provide equitable experiences to all the participants, irrespective
of their mode of participation, is challenging. To host a success-
ful hybrid workshop requires a lot of additional infrastructure and
coordination (Rokem and Benson, 2024). For OceanHackWeek,
this includes our standard infrastructure plus a video conferencing
Oceanography | Early Online Release
platform, consistency in facilitating project work, and any in-
person logistics. Given the wide range of tasks, we have found that
a large team of organizers is necessary, with some focused on the
in-person component and others dedicated to the virtual com-
ponent. In the case of the “distributed” model with multiple in-
person locations, we suggest a separate organizing group for each
of the satellites.
Project work in a hybrid setting can be extremely successful but
requires significant facilitation—more than a solely in-person or
virtual event requires. For most of the projects, in-person and vir-
tual participants interacted with each other and collaborated asyn-
chronously around the clock and around the globe. Participants
enjoyed these interactions and working across those traditional
boundaries. This success was based on project-facilitator skills
and the project-specific communication avenues (dedicated Slack
channels) and GitHub repositories available on our shared cloud-
based computational platform. The project facilitators helped
ensure communication was flowing among all team members by
actively checking in with virtual participants to encourage their
continuing involvement. We found that if the project team was
mostly composed of in-person participants in a single location, it
was often harder for the external participants to engage (even with
the facilitation).
FOSTERING AN OPEN, SHARING CULTURE
Scene setting is important for cultivating a welcoming, inclu-
sive environment. Each year, a collaborative Code of Conduct is
developed as one of the workshop’s opening activities, and the
website is updated with the new Code of Conduct. In addition,
we give a presentation that explains our project philosophy and
offers tips for smooth teamwork. We have found these activi-
ties help participants feel welcome, encourage participants to be
inclusive, and build a supportive environment where participants
feel comfortable contributing (see participant testimonials in the
Supplementary Material).
SOFTWARE
OceanHackWeek projects tend to use one main programming lan-
guage, although some participants take this as an opportunity to
work in their less-dominant language, or in a different sub-domain,
to expand their knowledge and skillsets. We have conducted tuto-
rials in both languages, experimenting with duplication of tutorial
topics (e.g., “Data access in Python” and “Data access in R”), sepa-
rate tutorials that focus on a Python- or R-specific tool (e.g., xarray
or oce, respectively), and more general tutorials that address a
problem and how to approach solving it. As it can be challenging
to keep the attention of participants during the tutorials in their
non-dominant language, we have found more engagement with
the “addressing-a-problem” approach, which tends to be agnostic
regarding the language and more about the process.
Using a shared computational environment brings many advan-
tages for this type of workshop (Rokem and Benson, 2024; Sauthoff
et al., 2024): we do not need to factor time into our schedule to
ensure all the participants have the correct environments installed,
allowing us to focus on our learning goals; it helps project teams
have consistent environments; and it gives participants the oppor-
tunity to (potentially) try out a new coding language without hav-
ing to install it on their local machines (Martin et al., 2025).
RECOMMENDATIONS
Based on our experience, we offer five recommendations for run-
ning an OceanHackWeek style event.
1. Conduct a five-day, immersive workshop. Five days allows time
for tutorials but still gives participants ample time for project
brainstorming, group formation, and project work.
2. To promote inclusive, productive project teams, set the scene
at the start of the session and check in frequently with partici-
pants. For example, discuss tips for effective teamwork and cre-
ate a code of conduct.
3. If the desire is to teach or encourage multiple programming lan-
guages, think carefully about the tutorial approach. Language
agnostic tutorials are good if everyone is listening to the same
tutorial, but if the setting allows, splitting into groups for more
language/tool specific tutorials could be beneficial.
4. Choose computing infrastructure that works for the program/
lesson goals. We recommend a shared computing platform
(e.g., a JupyterHub) to minimize time troubleshooting partic-
ipants’ individual systems. However, depending on the goals
(e.g., if one goal is enabling participants to work locally beyond
the event), walking through installations and environment set-
ups may be appropriate.
5. If the workshop will be hybrid, have materials and clear guide-
lines to help with facilitation of the event across the different
modes of participation. It is important to have a project facilita-
tor for every project, and some organizing committee members
focused on either the in-person component or the virtual com-
ponent rather than having everyone trying to organize both.
A virtual-only workshop can provide the benefit of expanded
accessibility while reducing the burden of coordination between
in-person and virtual modes of participation.
While the discussion in this paper focuses on a five-day work-
shop format, aspects of OceanHackWeek can be translated to a
classroom environment. Indeed, past organizers and participants
have already successfully adapted the model to more specific con-
texts (Martin et al., 2025). Data science and oceanography skills
could still be taught with our tutorial and project-work approach
but spread out over a different time frame; the group projects could
be done in the classroom, or a hackweek could be held within a
research team, a department, or an institution.
With more than 450 participants over seven years, Ocean
HackWeek has catalyzed intellectual and technical exchanges
among ocean scientists from diverse backgrounds. The balance of
tutorials and participant-driven project work provides attendees
Early Online Release | Oceanography
with new technical skills and collaboration opportunities that
extend beyond the event, accelerating discovery and innovation in
the ocean sciences.
SUPPLEMENTARY MATERIALS
The supplementary materials are available online at https://doi.org/10.5670/
oceanog.2026.e104.
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AUTHOR CONTRIBUTIONS
OceanHackWeek is a collaborative project, with each member of the team contribut-
ing in many different ways. All authors are/were members of the 2023 and/or 2024
OceanHackWeek Steering Committee, and all have been involved in organizing
the annual event for one or more years. For this article specifically, we list roles fol-
lowing the CRediT system: Conceptualization, CM, WL. Writing – original draft and
project administration, CM. Writing – review and editing, CM, WL, FF, JG, AK, EM,
TM, NM, NR, VS.
ACKNOWLEDGMENTS
Over the past seven years, many people have played roles in OceanHackWeek,
from shaping the direction of the program to organizing one (or more) of the annual
events. There are too many to call out individually, but we are extremely grateful
for the contributions of all. We also sincerely appreciate the sponsorship and fund-
ing that has supported the event over the past seven years, enabling participants to
attend at minimal cost: Integrated Ocean Observing System (IOOS), NSF Division of
Ocean Sciences, NASA, Schmidt Ocean Institute, University of Washington eScience
Institute, University of Washington Applied Physics Laboratory, Ocean Carbon and
Biogeochemistry Program, NOAA Global Ocean Monitoring and Observing, Integrated
Marine Observing System (IMOS), Commonwealth Scientific and Industrial Research
Organisation (CSIRO), ACCESS-NRI.
AUTHORS
Catherine Mitchell (cmitchell@bigelow.org), Bigelow Laboratory for Ocean Sciences,
East Boothbay, ME, USA. Wu-Jung Lee, Applied Physics Laboratory, University
of Washington, Seattle, WA, USA. Filipe Fernandes, Integrated Ocean Observing
System (IOOS), USA. Joseph Gum, Computational and Information Systems
Laboratory, NSF National Center for Atmospheric Research, Boulder, CO, USA.
Alex Kerney, Ocean Data Products, Gulf of Maine Research Institute, Portland,
ME, USA. Emilio Mayorga, Applied Physics Laboratory, University of Washington,
Seattle, WA, USA. Thomas Moore, CSIRO Climate Science Centre, Hobart, TAS,
Australia. Nick Mortimer, CSIRO Environment, Crawley, WA, Australia. Natalia Ribeiro,
Integrated Marine Observing System, University of Tasmania, Battery Point,
TAS, Australia. Valentina Staneva, eScience Institute, University of Washington,
Seattle, WA, USA.
ARTICLE CITATION
Mitchell, C., W.-J. Lee, F. Fernandes, J. Gum, A. Kerney, E. Mayorga, T. Moore,
N. Mortimer, N. Ribeiro, and V. Staneva. 2026. OceanHackWeek: An inclusive, collabo-
rative approach to developing oceanography data science skills. Oceanography 39(1),
https://doi.org/10.5670/oceanog.2026.e104.
COPYRIGHT & USAGE
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Commons Attribution 4.0 International License, which permits use, sharing, adapta-
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materials appropriately, provide a link to the Creative Commons license, and indicate
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