6. Considerations for FAIR video material

Learning Outcomes

By the end of this session, learners will be able to:

Explain why video materials should follow FAIR principles and identify key challenges in doing so
Evaluate how FAIR a given video is, using real examples
Apply minimum FAIR-by-design practices when creating or sharing training videos
Generate and use transcripts or captions to enhance accessibility and interoperability

6.1 Presentation

Here you can find the presentation for this session:

The full presentation can be viewed in Google slides or copied for reuse under a CC BY 4.0 license

6.2 Why FAIR video materials matter

Video is one of the most powerful ways to enhance learning, but only if it can be found, accessed, reused, and understood by others. Making your video materials FAIR ensures that the effort you invest in creating them continues to have impact long after the initial training.

Reflection

Before we dive deeper, take a moment to reflect:

Have you used / are you planning to use video material in your training?
What kind of video material? (e.g., recorded lectures, interviews, demonstrations, or animations)
Why or why not?

Why video media is a great tool for learning

Video media is great for enhancing & contextualizing learning! Some advantages include:

Improved retention and understanding: combining visual and auditory information engages multiple senses → dual coding theory (1, 2)
Supports flexible, self-paced learning: learners can pause, rewind, or rewatch segments at their own pace (3, 4)
Enables asynchronous learning: learners access materials anytime, anywhere
Provides authentic demonstrations: e.g. when teaching lab techniques, workflows, or software use
Increases accessibility and inclusion: captions, transcripts, and translations make content more widely usable

Types of video materials that can be made FAIR

There are many ways to use video as a training resource, for example: voiceovers added to slides or presentations, screen recordings showing workflows/coding/software demonstrations, interviews with experts or practitioners, lecture recordings or seminars, animations and explainer videos, hands-on demonstrations in labs or fieldwork settings. All of these can be made FAIR!

Let’s now have a look at what it takes to FAIRify video material:

Exercise

Find a short video (for example on YouTube, Protocols.io, Zenodo, or another platform) that you might want to include in your own course, or use one of two sample videos that can be found here and here. For your chosen video, take 5–10 minutes to assess:

Findable → Is it hosted on a trusted platform? Does it have a DOI or persistent identifier?
Accessible → Is the access type and language defined? Can the video or transcript be downloaded?
Interoperable → Are there captions or transcripts? Is it in a standard format (e.g. .mp4, .mov)?
Reusable → Is there a clear license? Are contributors and tools properly attributed? Is there versioning information?

Document your findings in the Checklist for minimally FAIR video material. You can make a copy of this course worksheet for reuse under a CC BY 4.0 license.

Reflection

After the exercise, take a moment to reflect:

Was the video material you chose FAIR?
How easy would it be for you to reuse this material?
If not easy: what information would you need to make reuse easier?

Why FAIR video materials matter

Making your video materials FAIR increases their long-term value and educational impact:

It makes them easy to locate
It supports asynchronous learning when they can be viewed or downloaded anytime, anywhere
It enables using them across platforms and tools
It allow others to legally adapt or remix them
It ensures they remain available and understandable over time

In short: FAIR video = more impact from the effort you put into creating it
By sharing your training videos in a FAIR way, you amplify their reach, support diverse learners, and contribute to a more open and connected scientific training ecosystem.

6.3 Barriers to creating FAIR video materials

Making video materials FAIR can be highly rewarding — but it’s not always straightforward. There are practical, technical, and even ethical challenges that educators and trainers often face.

Reflection

Before we look at common barriers, take a moment to reflect:
What’s the biggest barrier for you in using and FAIRifying video material? Is it related to technology, time, or something else?

Below are some of the most common obstacles encountered when creating or sharing FAIR video materials:

Barrier	Description
Time & Resources	Creating, editing, and annotating videos takes planning and effort.
Technical Skills	Recording, editing, adding metadata, and creating captions require some know-how.
Knowledge Gaps	Limited awareness of FAIR video practices or suitable hosting platforms.
Infrastructure	Not all organizations have repositories or tools for storing videos with FAIR metadata.
Licensing & Permissions	Confusion about copyright, reuse rights, and privacy when sharing video content.
AI & Ethics	Emerging tools (e.g., for transcription or editing) raise questions about bias, transparency, and attribution.
File Size & Storage Limits	High-quality video files are large, making them harder to host on institutional repositories or platforms like Zenodo (often limited to 50 GB per upload).
Metadata Complexity	Video materials often need multiple layers of metadata (e.g., author, content, format, transcript, licensing), and it’s not always clear where or how to include these.

Even though these barriers exist, many can be overcome with planning, collaboration, and the right tools. In the next section, we’ll look at practical steps and minimum FAIR-by-design practices to help make your video materials more FAIR without requiring expert-level skills.

6.4 AI and FAIR video material

A workflow for making FAIR video material with the use of AI

A potential way to mitigate some of the barriers to FAIR video materials is to use AI tools at different stages of video creation. The workflow below illustrates which tools, some of which use AI, can support each stage:

As the workflow illustrates, AI tools can help overcome several common barriers in creating FAIR video materials, from generating scripts to editing, transcribing, and hosting videos. While AI can speed up production and reduce workload, it’s important to remember that using AI does not automatically make content FAIR. For example, an AI-generated transcript may improve accessibility, but if it is not properly formatted, licensed, or shared with metadata, it will not be findable or reusable. Likewise, AI platforms may store outputs in proprietary formats or behind authentication walls, limiting accessibility and interoperability. Ensuring FAIRness thus requires deliberate steps by the creator, such as applying open licenses, adding persistent identifiers, using open formats, and providing rich, structured metadata.

Reflection

Use AI with caution!

Is AI-generated content FAIR?
How can you ensure quality and accuracy?
How might AI affect creativity and learner engagement?
How should we credit AI contributions?

Indicating AI contributions

If you do decide to use AI tools in your video creation process, it is important to indicate its contribution properly to ensure transparency, maintain trust, and support FAIR principles. Properly stating AIs contribution makes the provenance of your materials understandable for both humans and machines, and helps others to responsibly reuse or adapt your video content.

General guidelines for indicating AI contribution:

Aspect	Guidelines / Examples
Crediting AI	For AI tools that had a creative or technical role: “Script generated with ChatGPT (OpenAI, 2025)”
Describing the role of AI	Explain how an AI tool was used, e.g., “Voiceover synthesized using Microsoft Azure TTS”
Crediting AI in metadata or end credits	“Video created by [Name], 2025. Script drafted with ChatGPT (OpenAI, version x.x). Captions generated using Whisper (OpenAI). Edited in CapCut.”
Citing AI in reference lists / FAIR records	Luijten, I. (2025). Creating FAIR video materials [Video]. Script generated with ChatGPT (OpenAI). Captions via Whisper (OpenAI). Zenodo. https://doi.org/10.xxxx/zenodo.xxxxx
Licensing AI-generated content	License with CC BY or CC BY-SA to allow reuse with attribution. State if remixing or AI reuse is permitted.

Adding transcripts to videos: WhisperAI

One essential step in FAIRifying video training materials is adding captions or a transcript, because it transforms the spoken content into machine-readable and searchable text. This improves findability, as search engines and repositories can index the text and help others discover your content. It also enhances accessibility, ensuring that people with hearing impairments or those who prefer reading can still engage with the material. In addition, transcripts and captions promote interoperability by allowing the content to be reused across different platforms, formats, or languages. Finally, they increase reusability, since the text can be cited, translated, remixed, or integrated into other learning materials, all while preserving the original meaning and context.

The following exercise is designed to give you hands-on practice with generating transcripts and captions. There are three levels of difficulty available, but for this course, we recommend you complete Level 1, which is suitable for beginners and covers the core skills needed to make your videos FAIR by adding a transcript or caption.

Easy technical level
Basic computer skills required

Intermediate technical level
Some experience installing and using desktop applications

Advanced technical level
Intermediate knowledge of GitHub and using the terminal required

For this exercise, you’ll need a short video. You can download our sample video from the course website or record a 1-2 minute video on your smartphone or laptop to use.

Warning

Ensure you do not record anyone without their permission!

Using the SciLifeLab serve instance of Whisper (easy)

Go to https://whisper-ai.serve.scilifelab.se
Upload your video file
Select the desired output format(s):
.txt for a plain transcript
.srt for caption files
Submit the file for processing
When transcription is complete, your output files will automatically download to your computer

Using an on-device GUI such as Whisper Transcription (intermediate)

Download the Whisper Transcription app (developed by Good Snooze) from the Mac App Store
In the app, download the Small Whisper model for faster performance
Open your video or audio file in the app to start transcription
Once completed, export the results as:
.srt for captions, or
.txt for transcript text

Installing your own local instance of Whisper (advanced)

Install Whisper directly from GitHub: pip install -U openai-whisper, or from the repository at https://github.com/openai/whisper
Install ffmpeg if not already available:
- macOS: brew install ffmpeg
- Windows: choco install ffmpeg
Save your transcription script as thecode.py in a text editor

Transcription script

import whisper  

model = whisper.load_model("base")    
result = model.transcribe("audio.mp3")    

with open("transcript.txt", "a") as f:
    print(result["text"], file=f)

Variables:
- base — model size (small, medium, etc.)
- audio.mp3 — your audio file (.m4a, .wav, .flac)
- transcript.txt — name of your output transcript

Place your audio file (e.g. audio1234.mp3) in the same directory
Open a terminal and navigate to that folder: cd path/to/your/files
Run the script: python3 thecode.py
Wait for transcription to complete — your output will appear in the same directory

Reflection

When you are finished transcription, inspect the transcript and answer the following:

Is it accurate?
Is it usable?
How does this help me achieve FAIR learning aims?

6.5 Adding FAIR video & transcript to your sample course

In this final exercise, you will practice publishing your own FAIR-by-design training video. Following the basic guidelines below, add your video and its transcript or captions to your sample course page. This step helps make your learning material more FAIR by ensuring that your video content is well-described, openly shared, and accessible to all learners.

Using OpenEdx

Upload your video to a FAIR-friendly, openly accessible platform such as YouTube, Zenodo, or Figshare. Make sure the video has a descriptive title, license, and metadata.
If your video includes captions or a transcript file (.srt or .txt), upload that as well and link it in your course content.
Go to your sample course on https://sandbox.openedx.org/
Click on ‘view course in: Studio’ in the top right corner. You will be taken to course outline.
Create a new section or unit, rename it to something like Training Video
Add a subsection and a unit where the video will appear
Under ‘Add a new component’ click ‘Video’
Copy paste the URL for you video
If you have a transcript, click ‘Transcripts’ and upload your .srt file
Under ‘License’ select the Creative Commons license of your choice
Click ‘Save’ and check that your video plays correctly and that the transcript link works
Click Publish to make your course unit visible

You’ve embedded your FAIR video and provided a transcript and license to improve findability, accessibility, and reusability.

Using GitHub and LiaScript

Upload your video to a FAIR-friendly, openly accessible platform such as YouTube, Zenodo, or Figshare.
Make sure the video has a descriptive title, license, and metadata.
Upload your transcript file (.txt or .md) to your GitHub repository or another accessible public location.
Go to your course repository created from the training material template.
Open the file README.md in your browser or local editor.

Embed your video in Markdown. LiaScript supports simple Markdown video embedding. Add something like:

## Training Video

![Video](https://img.youtube.com/vi/yourvideoid/0.jpg)  
[Watch on YouTube](https://www.youtube.com/watch?v=yourvideoid)

Alternatively, embed directly using HTML:

<iframe width="800" height="450" src="https://www.youtube.com/embed/yourvideoid" frameborder="0" allowfullscreen></iframe>

Add your transcript below the video:

**Transcript:**  
[Download transcript (.txt)](transcript.txt)

Or include a short excerpt for learners to preview:

> “Welcome to this FAIR video tutorial…”

Commit and save your changes.
Open your course through https://liascript.github.io/ using the raw URL of your updated README.md.
Refresh your browser to see your embedded video and transcript displayed in the LiaScript course page.

You’ve now embedded a FAIR video and transcript in your LiaScript course — ensuring your content is accessible, shareable, and reusable.

Citations

Paivio A (2009) Mental Representations: A dual coding approach, Oxford Psychology Series. https://doi.org/10.1093/acprof:oso/9780195066661.001.0001
Mayer RE (2009) Multimedia Learning. 2nd ed. Cambridge University Press. https://doi.org/10.1017/CBO9780511811678
Guo P, Kim J, Rubin R. (2014) How video production affects student engagement: An empirical study of MOOC videos. L@S ‘14: Proceedings of the first ACM conference on Learning @ scale conference 41-50. https://doi.org/10.1145/2556325.2566239
Zhang D, Zhou L, Briggs RO, Nunamaker JF (2006) Instructional video in e-learning: Assessing the impact of interactive video on learning effectiveness. Information & Management 43(1): 15-27, https://doi.org/10.1016/j.im.2005.01.004