Ope-Source-in-Research_otter.ai.srt

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Helena Rasche: My name is Helena Rasche
, I've been working in

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open source for quite some time
now I'm currently employed by

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the hospice Medical Center and
the Avans Hogeschool in

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Breda. And I'm here to tell
you a little bit about open

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source in research. So first,
what is free and open source

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software, the term is a bit
important. Because open source

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software and free software are
not necessarily the same things

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free software doesn't mean open.
So you can many of us remember

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freeware on the internet from
when we were younger. This is

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software where you have no
access to source code and you

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can't work with it, you can't
modify it due to license. This

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is not great for science. On the
other hand, open source doesn't

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mean free. So for those of you
who are producing research

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software, just because you're
making your software open

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source, it doesn't mean it has
to be free software. And this

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together, the intersection of
these two is often known as free

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and open source software, or
FOSS Free and open-source software

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And this just
refers to software that's

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both open and free. Open source
is simply licensing your work so

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it can be used how you want.
Making your software, open

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source is just a matter of
setting out the terms of how you

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want your software to be used,
it doesn't mean that you have to

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give up control of your
software, it doesn't mean that

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you're putting it out to the
community forever. It just means

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you're choosing and saying for
yourself setting boundaries on

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how you want your software to be
used. So it's very important

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step all the time. For those who
want you open source also makes

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it easy for others to remix your
software to reuse it to build

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upon your software, add new
features if they want. And if

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you're building a project where
community is important, where

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you want your software to be
used by a lot of people, making

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it open source in such a way
that people can reuse and work

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with you can be a really great
boost for your software just in

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terms of visibility and people
who want to use it, things like

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that. So why use and promote
open source. Open source is part

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of the ethics of scientists and
hackers a little bit when you're

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writing the software when you're
working on projects together. A

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lot of the libraries you use for
Python, things like this, if

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you're using different
programming languages, a lot of

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Python libraries you use will be
open source, you're benefiting

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from a lot of work that other
people have done so far. And

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it's a nice feeling to
collaborate and give back. Now

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you've built your software or
your project on years and years

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of free work that was produced
before and now you're giving

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back to the community. It also
means distributed innovation. So

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when you're making software open
source and free so that other

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people can work on it. This
means that other people will

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give back contributions, they'll
report bugs, when they have

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issues running your software,
they will tell you new features

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that they want. You don't have
to implement them. But you're

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able to take all of these good
ideas from the community and

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things like this. Importantly,
for science, open source is

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easier to review, reuse and
integrate. And when we talk

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about open source in science, if
you want your software to be

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distributed widely to be used in
a lot of systems, one of the

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best things you can do for it is
licensing it in such a way that

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everyone can use it and set it
up on their own system. Things

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like Galaxy so I'm of course
very biased here, and we'll talk

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a lot about Galaxy. But in the
Galaxy community, we can give a

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huge platform of you know,
unused Galaxy, you 30,000 users

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to free source, it's free
advertising. But we can only do

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that for open source software.
There are a lot of risks

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associated with closed code to
when you have closed source

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software that's used in science,
you can't review it very easily,

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the community can't review it
very easily only the reviewers

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of the paper sometimes. And if
there are errors in the

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software, if there are bugs,
then these can be missed for

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years and years. And these
effects a lot of scientific

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results downstream. So having
open source reviewable software,

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it's very important for
reproducible, good quality

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science. A lot of the journals
are adopting this and starting

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to require disclosure or
publishing have your source code

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for all of your software to this
is from a scientific

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perspective, really a good thing
for the community. So how do you

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know if something is open
source? You'll see on a lot of

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GitHub repositories, which I
think everyone here is familiar

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with, thanks to OLS is a little
license icon on the right hand

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side of the repository. Also on
things like slides, so you can

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see the CC by of these, this
slide deck at the top, you can

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look for a couple of different
files within the license. And

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these files need to be there if
it's going to be open source

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software that she can reuse. But
it's not just for software. I

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know I talk a lot about software
but it's also for data. There

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are different licenses for data
for things like databases that

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you want to make accessible for
photos or training materials,

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things like this. All these are
options. And if you want people

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to be able to use them, you need
to license

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them. One of common fears I hear
about a lot is, if I published

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my software online, if I do it
in the open, it'll be I'll be

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scooped someone will take my
software and claimants thrown.

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But this isn't necessarily true.
If someone steals your software,

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there is at least a traceable
log in GitHub, or which we'll

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get to in a minute. There is a
copy of your software already

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online. And if you already have
a community around that, it'll

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be very obvious that someone
took it. And if you're still

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worried, I've heard some people
saying that they publish

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preprints as a way to document
that, hey, they were first write

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the software, and to really make
sure they stake their claim on

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that software. So don't worry
about that just work in the

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open, it's better for the
community, it's better for the

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world. And it's good for
science, publishing, sharing

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open source code. One of the
easiest and most effective ways

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to do this is version control.
I'm sure you're all learning

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about getting GitHub if you
haven't already. But version

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control is fantastic way to
publish and share code with

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others. It gives you a whole
timeline of your software, and

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it makes it easy to reuse,
contribute and make

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modifications to your software.
So why collaborating is easy.

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One of the common things is
reverting accidents. If you make

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some bad changes in your code,
or one of your collaborators

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does, you can always revert you
can always go back to before

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then it makes it easy to
integrate the changes from

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multiple developers. Like with
galaxy, there are some 200

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contributors to the code base or
the training materials as well.

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And all of us can work together
collaboratively because we use

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version control. Also offsite
copies of your software,

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everyone has computer issues,
everyone loses a hard drive at

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some point or gets their
harddrive encrypted by some

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hackers things like this. If you
have all of your work in the

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open in public, then you can
just download a new copy again

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and start working in Git and
GitHub are very common, a very

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common choice. Git is one of the
most common version control

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systems, there are others.
GitHub, likewise, is one of the

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most common git hosts. But
there are others depends on what

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you want to use. One of the nice
things you get with GitHub is a

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large existing user base and
large community of people who

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will be able to contribute to
your software to low barrier for

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entry. If you need to learn more
about git, there is a great set

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of lessons from software
carpentries. But one of the

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important notes is that Git is
very, very complex. My partner

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teaches a get together session
where they teach how to use Git

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to the colleagues in our office.
And there is just so much to

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learn about git, but you don't
need to learn all of it. Now.

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Just start with the important
parts, the rest comes later.

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There, you'll see a lot of
guides online that will say oh,

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you need to learn about how the
commit craft works and things

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like this. But if you just want
to publish your code, you don't

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need any of the fancy stuff. So
a few steps to make your work

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open source. It README is a very
important part of us. If you

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want people to know what your
software is and how to start

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using it. That's the number one
thing people will see. So be

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sure to include lots of good
images there. License, if it

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has, if it's going to be open
source, it needs a license file.

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So it takes two minutes
to add a license to GitHub,

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it's really easy just doing same
thing with the contributing guide, GitHub

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has some template contributing
guides that make it really easy

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to tell people how you want them
to contribute to your to your

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repositories. Having a public
roadmap, we aim to talk about

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the Kanban boards and the agile.
Having a public roadmap is a

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great way to tell community,
what you're working on what

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features you're going to
implement things like that, that

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can help people get excited for
your software. Publishing list

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of issues same, it feels bad to
say, hey, my software has bugs.

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But at least putting them out in
the open, you can track the

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things you've done or not done.
A Code of Conduct assumptions

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you've learned from OLS is very
important thing. Contact and

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citation can be very useful as
well. If you have a GitHub

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repository, you can easily get
those from Zenodo and Figshare.

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If you need a DOI, there's a
nice website for how to choose a

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license. There are lots of
different license choices. And

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they give you a lot of different
freedom to choose what you want

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your software to be able to do
or what you want other people to

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be able to do with your
software. Some people don't want

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businesses to use their software
for free. And there are licenses

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that support this or some people
want everyone to use it for

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free. Lots of different choices.
But the ultimate goal, of

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course, is full reproducibility.
And we're getting a lot closer

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with things like Jupiter and
binder where you can publish

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your software but also a
notebook where people can run

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your software online, which is a
fantastic way to get people to

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use your software.

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Taking it further. There's a lot
of ways for you to contribute if

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you're a first time contributor
and to get involved in the open

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Source Software movement and
contributing to the open source

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communities. So there are lots
of nice links here if you want

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to explore them. And lastly is
the Turing way has a nice

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handbook on reproducible data
science and making software open

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source and publishing and making
accessible to people. So with

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that, thank you