The document discusses the benefits of using 3D technologies in education and research, highlighting how it can enhance audience engagement, preserve fragile collections, and facilitate data sharing. It details various methods of creating 3D models, including digital scanning and photogrammetry, and emphasizes the role of 3D printing and gamification in immersive learning experiences. Overall, the use of 3D technologies is presented as a way to democratize access to information and improve collaboration across disciplines.

2. 3D technologies for teaching and learning
How using 3D technologies can benefit education
and research

3. Image by UCL. Used with permission
An Introduction to 3D Digitisation
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4. Who is this 3D for?
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schools colleges universities
museums archives archaeology
engineeringhumanities
design arts computer sciences

5. Image by Andre Hilton. CC BY-SA 3.0
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Why use digital 3D?

6. » We can widen our audience by‘dematerialising’our real-world collection
» We can preserve fragile collections by making 3D copies
» We can harvest data from real world objects to increase our
understanding
» Researchers can gain new knowledge by 3D modeling & simulation
» We can share 3D data of real world objects
» 3D printing can make surrogate objects available to all
» 3D printing creates infinite opportunities for prototyping
» Learners engage with immersive worlds and‘gamification’
Why?
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7. 09/03/15 Jisc Digital Festival, 9-10 March 2015, ICC Birmingham 7
Dematerialising material
» A digital 3D model is essentially a
set of instructions
» The digital 3D model is a virtual
object
» 3D digital models can also be
‘printed out’ as real, tangible
objects
» Part of the 'open' movement
» Falling costs and simplified
workflows means using 3D
content is now a realistic option
Image by Andre Hilton. CC BY-SA 3.0

8. » Museum collections are
protected from excessive
handling
» Data can be used for analysis
and sharing
» Surrogate objects can be
generated
» Web delivery of collections
generates greater footfall
Preserving collections
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Image by UCL. Used with permission

9. » 3D data provides greater insights
and understanding
» Data can be made available to all
» Value added research
» Data can be used across
disciplines
Harvesting data
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Image by CyArk. CC BY-SA 3.0

10. » 3D data provides insights into
real world objects that are
otherwise not attainable
» Increased knowledge can be used
for conservation and
preservation
» Dissemination of knowledge
fulfils research remit
Gaining knowledge
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Image by Justin Barton. CC BY-SA 3.0

11. » 3D data can be archived and
accessed at any time
» 3D data can be delivered via
many means including web
» 3D data can be shared openly
between institutions around the
world
» Research can be collaborative
» 3D data can be accessed globally
for 3D printing
Sharing 3D data
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Image by Eggalois. CC BY-SA 3.0

12. » 3D printing is a proactive,
immersive learning activity
» Learners achieve immediate,
tangible results
» Imagination is not limited by
material
» Applicable learning to a wide
variety of subjects and disciplines
3D printing for all
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Photo by nyxchaotica. CC BY-SA 3.0

13. » Democratisation of manufacture
» Infinite flexibility without cost
» Intricate shaping without waste
» Imagination without limits
3D prototyping
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Photo by Shapeways. CC BY-SA 3.0

14. » 3D augments gamification
» Learning can be gamified
» 3D creates immersive interaction
» 3D interaction develops
cognitive skills
» 3D gamification increases
engagement
» 3D gamification takes learning
out of the classroom
3DVR AR
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Photo by Hagustin. CC BY-SA 3.0

15. » Dimension judged by eye or
measured by hand
» Can be accurate and simple
» Or detailed and less accurate
» Any 3D modelling software can
be used
» No point cloud > polygon
transformations involved
Approximation
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Image by David Van Brink. CC BY-SA 3.0

16. » Laser focused on object
» Time of bound-back to scanner
used to judge distance of a single
point
» Built-in camera may also collect
colour information for each point
» Point cloud is built then
transformed into polygon
» Reflective objects are
problematic
Laser scanning
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Image by CyArk. CC BY-SA 3.0

17. » Regular pattern of light projected
onto object
» Object digitally photographed
» Computer calculates degree and
nature of pattern distortion
» Computer calculates 3D shape of
object
» Point cloud is built then
transformed into polygon for
viewing, sharing and using
» 2D images can be taken to create
colour ‘texture maps’
Structured light
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Image by David Van Brink. CC BY-SA 3.0

18. » Using maths to ‘pull’ 3D geometry
from 2D images
» Any camera can be used but
‘neutral’ lenses work best
» Done manually inWWI but now
computerised
» Point cloud is built then
transformed into polygon for
viewing, sharing and using
» 2D images can be used to create
colour ‘texture map’
Photogrammetry
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Image by Michael Ashley. CC BY-SA 3.0

19. 09/03/15 Jisc Digital Festival, 9-10 March 2015, ICC Birmingham 19
https://sketchfab.com/models/d60d7945d378414d8387444fce61ba1c
https://sketchfab.com/models/56a3210a2d8f4a55a5b9ae69f12f05c0
https://sketchfab.com/models/ca6ca4a2e3b043f78e1eb3479b158897
https://sketchfab.com/models/b1e0c0a586b241b5996b1f2bcbfc664a

20. Find out more…
Contact…
Except where otherwise noted, this
work is licensed under CC-BY-NC-ND
Matt Faber
Imaging advisor
matt.faber@jisc.ac.uk
www.jiscdigitalmedia.ac.uk