Training and Consulting for Open and Reproducible Data Science.

I am in the process of making my newsletter FAIR (Findable, Accessible, Interoperable, and Reusable). Here's how.

Heidi Seibold

I am an advocate for Open Science. The FAIR priciples are very near and dear to my heart. I was excited when the Open Science folks at Jülich archived a bunch of my posts and gave them a persistent identifier (DOI, see archived posts here). This was exactly what I was still missing to make my posts more FAIR.

Making my newsletter FAIR

Too many code projects in research are done by a single person. Keep reading on why that's bad and how to do better.

It’s been a while since my last post. Founding the Digital Research Academy, holidays and LOTS AND LOTS of workshops and events have taken all my time. But it’s time to start writing again. One of the workshops I taught since my last post was on collaborative coding at the wonderful RSE summer school at KIT (click through the timetable to find all kinds of cool materials).   Image: There is more to collaboration than we see.

Collaborative Coding

Fraud in science continues to be a highly discussed topic in the scientific community and also in mainstream media. I've always seen Open Science as a way to improve rigor in science, but can it also avoid fraud?

I will not discuss cases of (alleged) fraud or scientific misconduct in this post, but focus on how I believe we can avoid it in the future. If you are interested in learning more about one of the major recent scandals, I recommend listening to the Freakonomics radio episode on the Gino case (see box below). Why Is There So Much Fraud in Academia? Freakonomics radio episode on the Gino case with wonderful interviews.

Avoiding fraud and improving rigor through Open Science

Code clubs are initiatives where people meet to improve their coding skills and help each other out. I am a big fan of them as I believe that they can help improving the quality of research. Because as we all know: Better Software, Better Research.

I recently learned more about the code club at the Max Planck Institue of Psychiatry (MPIP) in Munich and would like to share how they organize it in the hopes that it might inspire you. Thanks to the organizers Vera Karlbauer and Jonas Hagenberg for helping me write this post.

Code Clubs - good coding practices for all

The academic publishing system is broken. I think we can all agree on that. But what if you want to have an academic career and at the same time stick to your values of openness? Here's my pragmatic take.

I understand the fear of not publishing in established journals. We all want to have a good career and feel like publishing our papers in the journals that our peers and employers deem worthy seems like an important step. As a pragmatic open scientist, I generally recommend not to be too hard on yourself and start your Open Science journey with the steps that feel easy to implement.

A pragmatic Open Scientists Guide to Publishing Papers

Students and early PhD candidates often don't understand all the talk about Open Science. They think Open Science is just 'normal' science. The older researchers are the ones who teach them otherwise. Let's change that!

In the process of publishing my first PhD paper, the journal asked whether I would like to publish open access. For me that was a no-brainer. When I talked to my supervisor, he said something along the lines of “you’re gonna be an expensive PhD student”.  I want to mention that my supervisor was always supportive of my Open Science and reproducibility activities and actually taught me a lot in this regard.

Early career researchers want Open Science - what about the supervisors?

Spaces where you can gather with like minded people to discuss, learn, and collaborate can be really powerful. Could a space like this exist for Open Science?

Walking along the little stream back to Dagstuhl castle (during the seminar on Research Software Engineering: Bridging Knowledge Gaps), I thought about how inspiring this place is, how perfectly set up for collaborating, learning from each other and also for having just a fabulous time. All the rooms, from the regular meeting rooms to more special ones such as the room of armors are equipped with flip charts;

Dreaming about a perfect space to work on Open Science

The Open Science Retreat 2024 was a full success. We co-created so many things and had a wonderful time at the Dutch dunes. Read on to learn what came out of the retreat.

The Open Science Retreat follows an unconference model. Except for the plenary sessions, all activities are optional. The edition 2024 was mainly organised by OSC-NL. Here’s a few of the things we did: Unconference sessions: Collaborate on diverse topics from measuring open science to FAIR code (more below) Walks: Whether alone, with a mentor, or in a group.

Check out what happened at the Open Science Retreat 2024!

I am an advocate for Open Science. The FAIR priciples are very near and dear to my heart. I was excited when the Open Science folks at Jülich archived a bunch of my posts and gave them a persistent identifier (DOI). This exactly what I was still missing to make my posts more FAIR.

I get asked for career advice all the time (even though I am just figuring stuff out myself). Generally I try to help by listening and asking questions, but there is one thing that I tell everyone who wants to hear it: pick work where you like the people.

How do you pick the research group you want to work with? My recommendation is to pick based on two things: Do you like the topics they work on? Do you get along with the people in the group (in particular your boss/supervisor)?  The first is quite obvious for most people, but the fact that the second may be even more important is not as clear. Team dynamics matter so much!

How to pick a research group to apply to?

Making your research or code project FAIR (Findable, Accessible, Interoperable, Reusable) and reproducible can feel like a chore. But if you have access to the right templates and resources, it can be quite the simple and rewarding task. Let's make it easy for ourselves to do the right thing!

So today let me share some templates for setting up #FAIR and #reproducible projects. I asked folks on social media what suggestions they had and got so many that I was not able to put them all here without making everyone’s head explode ;). Please do follow the respective social media links if the links here are not enough for you (especially Mastodon). Thanks to everyone who contributed to this list!

Setting up a FAIR and reproducible project

I am excited to share that the Digital Research Academy incorporation is almost done. We had our notary appointment last week, set up the bank account and are now waiting for the official registration of the DRA Digital Research Academy GmbH.

I published my first post about the initial idea for the Digital Research Academy in May 2023. Now, just a year and a few months later, the Digital Research Academy is becoming not only an initiative but a company. Last week Joyce Kao, Melanie Imming and I went to the notary and signed all the relevant documents.

Incorporation of the Digital Research Academy

I have volunteered for many initiatives and was always happy to do so. Recently I started to realize that being able to volunteer is a privileged position to be in. To be truly fair and allow all enthusiasts to join an initiative we have to rethink the way we do things. A constructive criticism.

I’ve got to get this off my chest, you all! I’ve received yet another email asking whether I could speak at an event. For free.
<strong>
 “Why for free?”
</strong>
you ask? I am a fan of a lot of the volunteer-based initiatives in the research community, but
<strong>
 I think we have gone too far.
</strong>
Too many things are expected to be done for free in the scientific community.

Volunteerism has gone too far!

Have you complained about the inefficiency of public administration before? I think, you're not alone. In this post I want to share my journey with trying to help increase efficiency through data literacy in the public sector.

I am a person who likes to solve problems. Most of my time is spent solving problems in academia, but I decided to leave my usual grounds for a special project where I can help solving problems in the public sector. Why do I care about solving problems in the public sector? Public service is for us, the public. If it’s inefficient, we are all harmed.

Data literacy in the public sector

What are good strategies to develop an Open Science Policy? Here's our opinionated guide. This post was co-created with Sander Bosch, Open Science Programme Coordinator at VU Amsterdam.

At the Open Science Retreat 2024 Sander and I had a conversation about his experience in policy development. Since we believe that his experience is valuable for a lot of people out there, we decided to write down three simple rues to create an Open Science policy: Develop output policies first and combine them into an Open Science policy later.

3 simple rules for creating Open Science Policies

A new year always comes with the feeling of a new beginning. Let's look at what's to come this year. What are you up to? Do you have any resolutions? Ready to take the next step towards more open and collaborative research?

On new year’s eve, my husband and I have a habit of looking back on the year. It’s incredible how my life changed in 2023 compared to the years before, especially my professional life. Yet my professional drivers have stayed the same:
<strong>
 improve the quality of research
</strong>
.  I am happy to report that I feel like I had more impact on the quality of research in 2023 than any other year.

Ready to improve research quality this year?

At the [Open Science Retreat 2024](https://openscienceretreat.eu/)
Sander and I had a conversation about his experience in policy
development. Since we believe that his experience is valuable for a lot
of people out there, we decided to write down three simple rues to
create an Open Science policy:

1.  Develop output policies first and combine them into an Open Science
    policy later.
2.  Policies are about the "what" and "why". The "how" belongs elsewhere
    (e.g. guidelines).
3.  Don't start with the policy, start with the guidelines.

## Rule 1: Develop output policies first and combine them into an Open Science policy later.

Let's say you are in charge of creating an Open Science policy for your
institution. If you create an Open Science policy from the get go, this
will usually lead to a minimal consensus. Too many people need to be
involved and forward thinking ideas may be shut down. Instead do the
following:

- **Develop output policies first:** a policy for open source, a policy
  for FAIR/open data, a policy for open access, ...
- **Develop the Open Science policy second:** it's really easy, contains
  a statement at the top ("We value open scholarship and apply best
  research practices...") and then essentially just links to the output
  policies.

![main lego block: open science, pieces: open source, data, open access,
\...](https://heidiseibold.com/assets/images/posts/2024-04-26_os-policy.jpeg)

## Rule 2: Policies are about the "what" and "why". The "how" belongs elsewhere.

Policies are about what to do and why to do it. The implementation steps
(how to it), belong in guidelines or similar support documents.

For example:

- **Policy**: We want all publications from members of our organization
  to be openly accessible (WHAT), because we believe that open access
  promotes equity and increases effectiveness of scientific progress
  (WHY).
- **Guideline**: To ensure that your publication is open access, you can
  publish an open access preprint version, publish in an open access
  journal, or discuss alternatives with the open access support team
  (HOW).

The "what" and "why" will stay relatively constant over time, but the
how may change rather quickly depending on technological advances,
changes in publication venues, or the organization's support structure.

## Rule 3: Don't start with the policy, start with the guidelines.

In order to know what a policy should encompass, it is helpful to
understand best practices first. Let's say you are developing an open
source policy. It's good to know what good strategies for open source
development are and what the organization's members already do before
you get to the "what" and "why" of the policy. If you do this, you can
make sure that there's no huge gap between what the policy demands and
what is **feasible, supported and useful in practice** (gaps like these
are there surprisingly often!). You can first develop the guidelines
(HOW) and then the policy (WHAT and WHY) or develop them simultaneously.

![Option 1: First guidelines, then policy, Option 2: Simlutaneous
development](https://heidiseibold.com/assets/images/posts/2024-04-26_guidelines-policy.jpg)

Example: Open Source Policy development

- Run a workshop with people who write code and support with code at
  your organization. Ask them about best practices and also what the
  reasons for applying these practices are to them.
- Depending on what you learn, you might decide to jointly develop a
  guideline for best practices on (1) open source software development
  and licensing and (2) FAIR code scripts.
- During these discussions you might notice values coming up over and
  over again: quality (over quantity), reusability, equity, or simply
  openness. Take these and use them for the policy.

We hope these 3 rules help you create policies for your organization.
Please forward this information to anyone who might benefit.

This post and all images are licensed under CC-BY 4.0. Feel free to
reuse them. Please link back to this post.

All the best,  
Sander and Heidi


So today let me share some templates for setting up \#FAIR and
\#reproducible projects. I asked folks on social media what suggestions
they had and got so many that I was not able to put them all here
without making everyone's head explode ;). Please do follow the
respective social media links if the links here are not enough for you
(especially Mastodon). Thanks to everyone who contributed to this list!
🫶

[MASTODON](https://fosstodon.org/@HeidiSeibold/111805033271869754) \|
[LINKEDIN](https://www.linkedin.com/posts/dr-heidi-seibold_fair-reproducible-activity-7155522228040654849-KnzI?utm_source=share&utm_medium=member_desktop)
\| [TWITTER](https://twitter.com/HeidiBaya/status/1749756437117432008)

Please note that the following research project templates generally
assume that you work with data and code. The templates for code projects
further down focus on research software projects.

## 🗃️ Research projects

- GIN-Tonic [standardized research folder
  structure](https://gin-tonic.netlify.app/standard)
- The Turing Way [reproducible project
  template](https://github.com/the-turing-way/reproducible-project-template)
- My research [project
  template](https://github.com/HeidiSeibold/research-project-template)
- R [analysistemplates](https://github.com/jonas-hag/analysistemplates)
  from the MPIP code club
- The [TIER
  Protocol](https://www.projecttier.org/tier-protocol/protocol-4-0/)
- R user project [template](https://github.com/crsh/template) by
  Frederik Aust & Marius Barth
- [R project
  template](https://github.com/startyourlab/r-project-template) by start
  your lab
- [This template](https://osf.io/59gte/) from Crystal Lewis will help
  you if you want to reorganize your project for sharing it at the end
- R packages for project templates
  - [WORCS](https://cjvanlissa.github.io/worcs/index.html) - Workflow
    for Open Reproducible Code in Science for R users
  - [workflowr](https://workflowr.github.io/workflowr/) - organized +
    reproducible + shareable data science in R
  - [starter](https://www.danieldsjoberg.com/starter/) - a toolkit for
    starting new projects
  - [rrtools](https://github.com/benmarwick/rrtools) - Tools for Writing
    Reproducible Research in R
  - [targets](https://docs.ropensci.org/targets/) - Function-oriented
    Make-like declarative workflows for R

📦 Code projects

- [Python cookiecutter
  template](https://github.com/Materials-Data-Science-and-Informatics/fair-python-cookiecutter)
- [R devtools](https://devtools.r-lib.org/)

![](https://embed.filekitcdn.com/e/7cms4RU2BCZob5MkVBeTcm/5e34FAQcUkicwLeVrvJLwD)

## Setting up a FAIR and reproducible project repository

There are a couple of building blocks that you will see in (almost) all
templates above:

- A README describing the project
- A coherent folder structure
- Names for files and folders that are (1) human readable, (2) computer
  readable, and (3) consistent

One more thing I want to mention: Since we are talking about project
standards, check out the [YODA
principles](https://handbook.datalad.org/en/latest/basics/101-127-yoda.html)
which are a set of organizational standards for datasets used for data
analysis projects.

Today's post is probably the richest post I've shared so far. Full of
super useful templates. I hope that makes up for the past weeks of
silence from my end. I was very busy and in the upcoming weeks will
share with you what has kept me from writing newsletter posts. I
promise: it was worth it!

All the best,  
Heidi


I've got to get this off my chest, you all! I've received yet another
email asking whether I could speak at an event. For free.

**"Why for free?"** you ask?

> **It's an event from and for enthusiasts.**

I am a fan of a lot of the volunteer-based initiatives in the research
community, but **I think we have gone too far.**

- Too many things are expected to be done for free in the scientific
  community.
- Too many things are not budgeted into grants as they could be.
- Too many groups think about the actual costs of work and time too late
  or not at all.

Enthusiasm for something does not mean that you can and want to work for
it for free.

<table>
<colgroup>
<col style="width: 33%" />
<col style="width: 33%" />
<col style="width: 33%" />
</colgroup>
<tbody>
<tr class="odd">
<td as="td"><div>
<figure>
<p><img
src="https://embed.filekitcdn.com/e/7cms4RU2BCZob5MkVBeTcm/cnGiHo7FjUAtn9F6xGnCj5"
width="200" height="200" alt="Shrugging stick figure" /></p>
</figure>
</div></td>
<td></td>
<td as="td"><div>
<h2 id="give-everyone-a-chance-to-contribute">Give everyone a chance to
contribute</h2>
<p>Many people are passionate about something but still do not have the
possibility to volunteer. Let's stop building upon volunteer work only,
as it excludes people.</p>
<p>"It will look good on your CV" or "it will give you visibility" is
not enough for some of us.</p>
</div></td>
</tr>
</tbody>
</table>

## How do we fix it?

I'm gonna be honest: the first version of this newsletter was an angry
rant. It felt good to write, but it wasn't true to my goal of creating
positive impact (in a positive way). So let me try to provide
constructive criticism and share some ideas on how to fix the
over-reliance on volunteer work.

<table>
<colgroup>
<col style="width: 20%" />
<col style="width: 20%" />
<col style="width: 20%" />
<col style="width: 20%" />
<col style="width: 20%" />
</colgroup>
<tbody>
<tr class="odd">
<td as="td"><div>
<h3 id="section">💸</h3>
<h3 id="ask-for-more-money"><strong>Ask for (more) money</strong></h3>
<p>If we provide services (e.g. training, software, project management),
we can ask for money - or at least donations - from the institutions and
people who benefit.</p>
<p><em>Ask for money. If you already are and it's not enough, ask for
more. Pay the people who contribute a fair share.</em></p>
</div></td>
<td></td>
<td as="td"><div>
<h3 id="section-1">📊</h3>
<h3 id="plan-for-the-work-in-grant-applications"><strong>Plan for the
work in grant applications</strong></h3>
<p>In grants we sometimes forget how much time developing training,
organising community events, or mentoring costs.</p>
<p><em>Put in the real numbers and pay people for the actual work they
put in.</em></p>
</div></td>
<td></td>
<td as="td"><div>
<h3 id="section-2">👩💼</h3>
<h3 id="think-like-a-business-not-like-a-charity"><strong>Think like a
business, not like a charity</strong></h3>
<p>Initiatives who provide relevant services for research, are not doing
charity. Let's stop acting like it.</p>
<p><em>Write a business plan, do marketing, sales, and learn from
businesses how to make money and pay people.</em></p>
</div></td>
</tr>
</tbody>
</table>

What do you think? Do these make sense?

## How does the Digital Research Academy do things?

If I know a group of enthusiasts, it's the folks in the [DRA
community](https://digital-research.academy/trainers/). We're in this,
because we believe that research could be better and we want to make it
so. But - and this is important - we don't want to do it for free. Why?
Because not all of us can work for free. **Basing what we do on
volunteer work would hinder our endeavor of being an open and inclusive
community.**

Two of our [guiding
principles](https://digital-research.academy/principles/#guiding-principles)
are:

- Together we aim to be an active, inclusive and open community of
  trainers and learners based on trust, making it a common practice to
  listen to and support each other and embed inclusive and open
  practices in our trainings; and
- We ensure everyone in the network is paid or rewarded for their
  efforts, we use clear licences for our materials and a clear pricing
  structure that includes tailored training.

**Have we figured it all out? Of course not!** Some of us have to
volunteer for now to get the [Digital Research
Academy](https://digital-research.academy/) started until we earn the
money to pay ourselves. Also, we are struggling with reactions from our
training clients who did not expect our prices (which would be a cheap
in industry, especially since our courses are custom).

Some folks want to volunteer their time. That's ok, too. We just don't
want to be dependent on it.

I hope that I managed to turn the post this week into something
constructive and I am happy to discuss with anyone to find even better
solutions. Because I think we can.

All the best,

Heidi


I will not discuss cases of (alleged) fraud or scientific misconduct in
this post, but focus on how I believe we can avoid it in the future. If
you are interested in learning more about one of the major recent
scandals, I recommend listening to the [Freakonomics radio
episode](https://freakonomics.com/podcast/why-is-there-so-much-fraud-in-academia/)
on the Gino case (see box below).

<table>
<colgroup>
<col style="width: 33%" />
<col style="width: 33%" />
<col style="width: 33%" />
</colgroup>
<tbody>
<tr class="odd">
<td as="td"><div>
<figure>
<p><img
src="https://embed.filekitcdn.com/e/7cms4RU2BCZob5MkVBeTcm/iUauns5JJHeeRUn8QGfRKc"
style="width:100.0%" /></p>
</figure>
</div></td>
<td></td>
<td as="td"><div>
<h2 id="why-is-there-so-much-fraud-in-academia">Why Is There So Much
Fraud in Academia?</h2>
<p>Freakonomics radio episode on the Gino case with wonderful
interviews. (I fully disagree with the hosts assessment of the quality
of research in economics, but otherwise a great episode)</p>
<a
href="https://freakonomics.com/podcast/why-is-there-so-much-fraud-in-academia/">Listen
to the podcast</a>
</div></td>
</tr>
</tbody>
</table>

## Focus on the solution

Scientific fraud hurts everyone. It hurts the trust in science, it hurts
the scientists who build upon problematic research, and of course it
hurts the people who were supposed to benefit from the research (think
e.g. medical research).

So how do we avoid fraud? In my opinion, **Open Science can be part of
the solution**. If we work on setting better standards in science that
promote **openness, collaboration and success based on quality rather
than quantity**, we would get a long way already.

As long as we hype single researchers, allow them to work in their ivory
tower without sharing relevant details of their research, and promote
based on the number of "high impact" publication, we will see scientific
misconduct and fraud over and over again.

## Open Science: Avoiding fraud and improving rigor

The cool thing about Open Science is that it goes much beyond just
avoiding fraud. **Open Science is all about scientific rigor and good
scientific practice**. I, as and Open Science advocate, don't just
advocate for openness, I advocate for better quality in research.

Let me share some thoughts on how Open Science avoids fraud
[and]{.underline} improves rigor at the same time.

<table>
<colgroup>
<col style="width: 33%" />
<col style="width: 33%" />
<col style="width: 33%" />
</colgroup>
<tbody>
<tr class="odd">
<td as="td"><div>
<h2 id="avoid-fraud">Avoid fraud</h2>
<ul>
<li><span>Openness and good practices allow you to stay on top of what
your are doing.</span></li>
<li><span>Openness provides the possibility for others to check your
work.</span></li>
<li><span>An open and fair error culture give the possibility to allow
saying you were wrong in the past.</span></li>
<li><span>...</span></li>
</ul>
</div></td>
<td></td>
<td as="td"><div>
<h2 id="improve-rigor">Improve rigor</h2>
<ul>
<li><span>Open Science promotes good practices such as preregistration
and version control.</span></li>
<li><span>Openness allows you to build on sources you can check and
trust.</span></li>
<li><span>A collaborative culture allows for many people to work
together successfully.</span></li>
<li><span>...</span></li>
</ul>
</div></td>
</tr>
</tbody>
</table>

And let me make one thing clear: **Scientific rigor does not mean being
right all the time, but doing your best with good intentions.** We are
all humans and we make mistakes. My research has been far from perfect,
but I did my best and I focused on good research rather than pushing out
as many papers as possible.

If you are interested in avoiding fraud and promoting rigor at your
institution, feel free to [reach out to
me](https://heidiseibold.com/contact/). I am **happy to help with
training and support**.

All the best,

Heidi


I recently learned more about the code club at the Max Planck Institue
of Psychiatry (MPIP) in Munich and would like to share how they organize
it in the hopes that it might inspire you. Thanks to the organizers Vera
Karlbauer and Jonas Hagenberg for helping me write this post.

## CodeClub at MPIP

**Target audience:** researchers who use code but may have quite varying
programming skills (from wet-lab scientists to bioinformaticians).

**Goal:** increase the quality of their research software and code
scripts for better reproducibility and fewer errors.

**Structure:**

Meetings: 1x per month, ca. 1h

Format:

- Short presentations (ca. 10 min) about a relevant topic
- Short exercises in small groups

Code Review:

- Platform to find a partner
- Help with how to perform a code review
- Discuss problems and experiences in the group

**Implementation:**

- Ask everyone to present -- does not need to be polished
- Set realistic goals (only 1h)
- Use breakout rooms for exercises when online
- Mix experienced with less experienced participants
- Collect presentations at one place

**Organizers:** Two PhD students (currently Vera and Jonas). They
recruit a new candidate from the attending students when one of the two
PhD students graduates.

Implementing a code club can be challenging. In their talk, Vera and
Jonas mentioned the problems, but they also found some solutions:

- Beginners are reluctant to join:
  - Communicate and advertise during onboarding
  - Low entry barrier and easy first wins (use a [project
    template](https://github.com/jonas-hag/analysistemplates)!)
- Wide range of different projects and software.
  - Topics that are programming language agnostic but useful for many,
    e.g. literature review tools.
  - Promote a [project
    template](https://github.com/jonas-hag/analysistemplates) for better
    comparability.
  - Best practice template scripts for R and Python (still work in
    progress).
- Often data analysis scripts instead of software development.
  - Be pragmatic. E.g. instead of full documentation or github code
    reviews, code comments may be enough.
- Code review is time-consuming and is not considered an important
  contribution.
  - Long-term solution: change culture and recognize achievements.
  - Clear [code review guide](https://zenodo.org/records/8432946).

![Vera presenting the project template that came out of their code club
inspired by a template I mentioned to her in a workshop. Made me really
happy!](https://embed.filekitcdn.com/e/7cms4RU2BCZob5MkVBeTcm/nh6c7cBnGiY6UPfQtA5mMT)

## Other code clubs

There are many similar initiatives and quite some useful resources. Here
is a list of a bunch of them. Please check them out and consider
starting join a code club or even starting one ;)

- [HackyHour](http://hackyhour.github.io/) projects (see if there is one
  near you!)
- [ROpenSci coworking](https://ropensci.org/blog/2023/06/21/coworking/)
  sessions
- [TidyTuesday](https://github.com/rfordatascience/tidytuesday) for R
  users
- [DataDojo](https://ddojo.github.io/) (Würzburg)
- [ResBaz](https://resbaz.github.io/resbaz2021/) = Research Bazaar (e.g.
  the one in [Arizona](https://researchbazaar.arizona.edu/))
- Mozilla Study Groups (see their
  [handbook](https://mozillascience.github.io/studyGroupHandbook/)!)

## Support needed?

Need help with starting a code club or implement other strategies in
your group/institution/project to improve the quality of your code? The
[Digital Research Academy](https://digital-research.academy/) does just
that. [Get in touch!](https://digital-research.academy/contact/)

All the best,

Heidi

------------------------------------------------------------------------

P.S. If you're enjoying this newsletter, please consider supporting my
work by leaving a tip.


On new year's eve, my husband and I have a habit of looking back on the
year. It's incredible how my life changed in 2023 compared to the years
before, especially my professional life. Yet my professional drivers
have stayed the same: **improve the quality of research**.

I am happy to report that I feel like I had more impact on the quality
of research in 2023 than any other year.

![](https://embed.filekitcdn.com/e/7cms4RU2BCZob5MkVBeTcm/a8QoBWk2ZoY5VKvYn1iYgc){happy=""
new="" year!\"="" letters="" next="" to="" researcher="" in="" a=""
labb\"=""}

## 2024

Let's look forward, to 2024: What can we do to go even further? Both you
and I. How can we improve the quality of research in 2024? Here are some
ideas.

<table>
<colgroup>
<col style="width: 33%" />
<col style="width: 33%" />
<col style="width: 33%" />
</colgroup>
<tbody>
<tr class="odd">
<td as="td"><div>
<h2 id="you">You</h2>
<ol>
<li><span>Learn about ways to make your research better.</span></li>
<li><span>Help other people improve their work.</span></li>
</ol>
</div></td>
<td></td>
<td as="td"><div>
<h2 id="heidi">Heidi</h2>
<ol>
<li><span>Offer possibilities to learn about good research
practices.</span></li>
<li><span>Give others who do good work visibility and possibilities to
share.</span></li>
</ol>
</div></td>
</tr>
</tbody>
</table>

## You

### Learn about ways to make your research better.

There is so many ways you can make your research better. There is always
something to learn. For example, you could...

- take a course on open and reproducible research (reach out to me if
  you are interested 😉),
- participate in the [Open Science
  Challenge](https://heidiseibold.ck.page/opensciencechallenge) and
  learn more about your own goals,
- check out [The Turing
  Way](https://the-turing-way.netlify.app/index.html), a free online
  book on reproducible, ethical and collaborative data science,
- join the [Open Science Retreat](https://openscienceretreat.eu/apply/)
  and discuss with like-minded people,
- join/organize a [ReproducibiliTea](https://reproducibilitea.org/)
  journal club or a code club,
- and many more...

### Help other people improve their work

You probably already know a thing or two about good research practices.

- Are you the nerd who knows how to improve coding practices? Help
  someone by going through their code together.
- Are you an open access hero? Share your story with others.
- Want to share your knowledge more broadly? Consider teaching (e.g. by
  [joining the Digital Research Academy as a
  trainer](https://digital-research.academy/trainers-join/)).

## Heidi

### Offer possibilities to learn about good research practices.

This year I want to support people in research in the fields of open
science, reproducible research, research software engineering and data
literacy. How? Various ways:

- Organize workshops and trainings for PhD programs, research groups,
  and other interested parties.
- Send out ideas and advice through my newsletter.
- Bring these topics to events (see e.g. our workshop on [FAIR and
  reproducible code at
  deRSE24](https://events.hifis.net/event/994/contributions/7987/),
  organized with the German Reproducibility Network)
- Offer easily accessible online courses through the Digital Research
  Academy [basic
  membership](https://digital-research.academy/learners/#membership).
- ...

### Give others who do good work visibility and possibilities to share.

Through the [Digital Research
Academy](https://digital-research.academy/) we have created the
possibility for experts to share their expertise and become part of a
trainer network. This year I want to spend a good amount of my energy to
giving these wonderful people the visibility and possibilities they
deserve.

Through our website and social media accounts you'll soon be able to
learn more about the types of trainings the DRA trainers offer.

|                                                      |                                                                        |                                                                       |
|------------------------------------------------------|------------------------------------------------------------------------|-----------------------------------------------------------------------|
| [Mastodon](https://mastodon.social/@digiresacademy/) | [LinkedIn](https://www.linkedin.com/company/digital-research-academy/) | [Website](https://www.linkedin.com/company/digital-research-academy/) |

An we'll onboard even more trainers this year. Our next
Train-the-Trainer program starts end of January and we're already
planning another for summer. Interested in becoming a trainer? Sign up
for [this mailing list](https://www.listserv.dfn.de/sympa/subscribe/dra)
to not miss any upcoming opportunities!

Each training will be bespoke to fit the needs of the respective
learners. I am sure this will be a fun endeavor for learners, trainers,
as well as us in the core team.

## Your input needed

Before I close this post, let me ask you for your help.

In one of the upcoming newsletter posts, I want to write about code
clubs and hacky hours. Do you have any experience, know of any (besides
the ones listed
[here](https://fosstodon.org/@HeidiSeibold/111261036485336617)), or know
of good resources on how to organize them? Please message me or respond
to [this toot](https://fosstodon.org/@HeidiSeibold/111261036485336617)
on Mastodon. Thank you!

All the best,

Heidi
