The document discusses using 3D and semantic data to discover relationships between artefacts. It describes artefacts as puzzle pieces that are missing, worn, and scattered across different museums. The presentation explores how 3D modeling, semantic descriptions of materials and styles, and natural language processing can be used to reunify fragmented artefacts, both digitally and through 3D printing. This involves combining geometric data from scans with semantic data from catalog descriptions to identify similar objects and learn more about their relationships.

1. Discovering relationships
between artefacts using 3D and
semantic data
Stephen C. Phillips
IT Innovation Centre
RICHES Networking Session 2015
19th October 2015

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https://www.flickr.com/photos/lunamodule/

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Front Back
Faded
Cracked
Eroded

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British Museum Cyprus Museum
Ashmolean Museum Fitzwilliam Museum

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Jigsaw
in 3D
most pieces missing
all the edges worn off
many puzzles jumbled together
pieces spread across many countries

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Re-Assembly
Re-Unification
Re-Association

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Re-Assembly
you have some (eroded) pieces
the computer fits them together
Hard!
Re-Unification
Re-Association

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Re-Unification
Head in the British
Museum
Statue in the Cyprus
Museum

12.  Re-unify 3D models of the statue
 3D print copies for re-unification
 Re-unify statue in virtual tour
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Re-Unification

13. Re-Association
Semantic Description
Material, decoration, size, shape, period, style, glaze, …
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Data in another museum catalogue

14. Re-Association
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How?

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Geometric data, material data
 Point cloud, mesh
 Photos
 Shape, geometry
 reassembly
 Curvature
 Colour(s)
 UV light, pigments
 Pattern
 Texture
 markings front & back
 manufacturing methods
 Chemical composition
 x-ray fluorescence
 Microscopic composition
 clay matrix, porosity

17. “
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Semantic data, natural language data
 CIDOC-CRM (“conceptual reference model”)
 ISO 21127:2006
 Object type, place, date, material, style, people, institution,
bibliography, dimensions, school, production technique, …
 Object  hasNote  “…lots of free-form text added by the curator”
 Natural Language Processing (NLP) required to extract further information
 The CRM harmonises knowledge to support discovery and enables
knowledge collaboration
 The British Museum has 2.5M objects described in CRM
provides definitions and a formal structure for describing the
implicit and explicit concepts and relationships used in cultural
heritage documentation.

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And…
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19. Further work?
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20. GRAVITATE-PROJECT.EU
Stephen C Phillips
scp@it-innovation.soton.ac.uk
© Copyright University of Southampton IT Innovation Centre and other GRAVITATE partners, 2015