Overview issue [Nicolas Travnicek]

nicolastravnicek commented 5 months ago

Introduction

Hi, my name is Nicolas Travnicek and I am a PhD in Biotechnology.

Describe your research in 2-3 sentences to someone that is not from your field (please avoid abbreviations) My research focuses on biocatalysis. This includes the engineering (modification) of enzymes to enable reactions which were not able to execute with the natural enzyme. Goal is to open up new reactions and to increase the sustainabilty of chemical reactions.

My research entails the following aspects:

Fill out Yes or No's to the aspects that apply to your research project.

Research Aspect	Answer
Use/collect personal data (health data, interviews, surveys)	No
Use/collect experimental data (lab experiments, measurements with instruments)	Yes
Collaborate with industry	No
Write/develop software as the main output of the project	No
Use code (as in programming) for data analysis	No
Work with large data (images, simulation models)	Yes
Other:	N/A

Reflections on the importance of RDM videos

I completely agree with the statements made in the video. Proper organization of data is essential to ensure reproducibility. I experienced the same issues while reproducing data which were reported in literature. Since all the reported data were poorly described and no deeper insights to the results were given, I spent a huge amount of time on trying to reproduce these results because my data showed huge deviations from the ones described in the paper. Consequently, I spent a huge amount of time trying to reproduce the results which was simply impossible since I did not get the results reported in literature. If the researchers in the paper would have explained and reported all their data, I would not have faced those problems from the beginning and had saved myself a lot of time.

What would you like to learn during this course?

Are there any things in particular that you would like to get out of this course? Do you have any goals that you would like to work on?

Checklist assignments

Use the checklist below for yourself to check off your progress in this course.

[x] Assignment 1: creating a GitHub issue (the overview issue) (before 15 February, 10:00)
[x] Respond to the GitHub issue #101
[x] Assignment 2: Data Flow Map 1 (share a link in this issue before 22 February 13:00). Link:
[x] Provide feedback to at least one Assignment 2 from another participant
[x] Respond to the GitHub discussion #103
[x] Respond to the GitHub discussion #102
[x] Assignment 3: Data Flow Map 2 (share a link in this issue before 5 March 13:00). Link:
[x] Provide feedback to at least one Assignment 3 from another participant
[x] Assignment 4: Data Management Plan (before 8 March, 13:00)
[ ] Respond to the GitHub discussion #104 if you have any questions (optional)
[x] Assignment 5: Data Flow Map 3: submit your slide (before 11 March, 17:00)

EstherPlomp commented 5 months ago

Hi @nicolastravnicek! Thanks for already submitting your overview assignment! If you remove the #<!-- signs before and after your answers, they will show up in the submitted assignment. I removed it for you for the first answer as an example. Please let me know if you have any issues with that and we can go over it together!

nicolastravnicek commented 5 months ago

Attached you will find the link to my second assignment https://surfdrive.surf.nl/files/index.php/s/Mq4rTzHWfusplXp

EstherPlomp commented 5 months ago

Thanks for sharing your assignment 2 @nicolastravnicek! It looks clear!

A question:

You use the closed access flag for all your data: why is this? In the overview assignment above you do not indicate that you work with industry? Why is the data confidential?

And some suggestions:

Files stored locally on your laptop or measurement computers are not backed up, unless you're using network drives! Which network drive is the section using for the data?
You mention labbooks in your notes but not in the data workflow: do you work with a lab book? If so it would be better to see that as a separate dataflow for the next assignment.

xxmeryl commented 4 months ago

Hi @nicolastravnicek ! Thanks for sharing your assignment, looks clear and very concise. I do have two questions:

Is this the only data you will be dealing with over the whole course of the project, or only just now?
How do you make the distinction about what is important enough to write electronically down versus 'only' in your labjournal? Wouldn't it be saver to somehow have an electronic back-up of your whole labjournal? Possibly scanning the pages every now and then, or using e-Labjournal?

Adarsh-Shajimon commented 4 months ago

Hi Nicolas! Thanks for sharing your Data Flow Map. It is concise. Do you store confidential data only on your private laptop? If yes, I would suggest having a secure backup of it. @nicolastravnicek

nicolastravnicek commented 4 months ago

The second assignment can be found here: https://surfdrive.surf.nl/files/index.php/s/Mq4rTzHWfusplXp (basically the same link as for the first assignment)

SiemEerden commented 4 months ago

Hey Nicolas! I've been looking into your data flow map, and overall it looks clear and concise! One suggestion:

If you are going to publish data (i.e. a supplementary dataset to a paper), then consider saving it in .csv format rather than .xlsx with interoperability in mind. This way, excel is not needed to open this file format. Excel allows you to export your spreadsheets in this format. .csv is a basic file format where the values of the cells are separated by commas, and it is often used by automated data mining programs. Formulas will be replaced with the actual values in these cells, though, so the choice also depends on what you want to publish of course.

EstherPlomp commented 4 months ago

Thanks for sharing assignment 3 @nicolastravnicek! It looks clear! And thanks for your feedback as well @SiemEerden: great point about file formats and also the risks of file format conversions!

I'm still interested why all of your data is flagged as confidential? Even if you're part of a consortium at least part of your data (underlying articles and thesis chapters) should be allowed to be shared (as seems to be the case for the first dataset in slide 5?)

Some other thoughts/comments, of which the last point is particular important:

I like the self explanatory file naming style in the slides!
Regarding documentation: do you also not work with protocols and/or labnotes?
For slide 6 the questions are about publicly sharing data and preserving data for the long term: your local laptop is not a solution for this. Project Drive is indeed better for long term preservation but does not provide public access. GitHub can indeed be publicly available, but it is not the same as a data repository as it does not have a long term preservation policy and it also doesn't assign DOIs to repositories (needed for data and code to be FAIR!). I'd recommend to have another look at the Data Publication materials!

ezgidemiroz commented 4 months ago

Hi Nicolas! Nice stucture for assignments 2 and 3. Looks very clear to me!

EstherPlomp / TNW-RDM-101