Springer Nature Video Discovery in Motion

Springer Nature Video is a collection of highly educational, peer-reviewed videos created by leading academics, practitioners, and thinkers. Titles take viewers through various demonstrations, case studies, and lectures that spark discourse and give a unique chance to see experts at work. 

Over 150 videos and 1,300 video clips are currently housed on SpringerLink. They incorporate interactive tools and links to related texts that make our content accessible, discoverable, and capable of supporting a diverse range of needs and interests.

Today’s researchers and students are ever-increasingly accustomed to learning from videos. The Springer Nature Video catalog answers this demand with well-presented, exclusive content in line with our renowned eBook program. With our first two packages, Clinical Medicine and Professional and Applied Computing, users can add value to scholarly work in numerous ways, including with:

  • Training (i.e. surgical training; protocols) 
  • Teaching materials     
  • Lectures, interviews, and roundtable discussions

Video examples

Cameron C. Wick: Otosclerosis and Stapes Surgery

Liz Clark: Controlling LEDs with Arduino

Michael Killen: How to Scale Your Small Business

Why use Springer Nature Video?


Curated and peer reviewed videos

Trusted content in areas researchers are interested in. Presented in learning courses and education videos developed by leading institutions and authors.


Full transcript and rich metadata

For better discovery and indexing


Connected to eBooks and journals content

Trust high quality eBook and journals content 

Where Springer Nature Video provides added value to users

Medical users

  • Watch surgical procedures in real-time with concurrent narration from the surgeon.
  • Experience conference-like presentations as researchers present new finding with data, slides, and other visuals.
  • Hear from thought leaders in various disciplines via one-on-one interviews with their mentees.

IT users

  • Learn a programming language, such as Python, R or MATLAB to support handling of large data-sets.
  • Learn how to manage a database and handle large data migrations.
  • Watch video primers to catch up on key tech topics and prerequisite terms (i.e. learn how the blockchain works).
  • Start learning new skills with introductory courses and titles, like Building Intelligent Systems: ​​​​​​​An Introduction to Machine Learning Engineering from Geoff Hulten.

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