My presentation at SW4CH 2018: Third International Workshop on Semantic Web for Cultural Heritage In Conjunction with 15th Extended Semantic Web Conference (ESWC 2018).
Abstarct: Cultural heritage (CH) resources are very diverse, heterogeneous, discontinuous and subject to possible updates and revisions in nature. The use of semantic web technologies associated with 3D graphical tools is proposed to improve the access, the exploration, the mining and the enrichment of this CH data in a standardized and more structured form. This paper presents a new ontology-based tool that allows to visualize spatial clustering over 3D distribution of CH artifacts. The data
that we are processing consists of the archaeological shipwreck ”Xlendi, Malta”, which was collected by photogrammtry and modeled by the Arpenteur ontology. Following semantic web best practices, the produced CH dataset was published as linked open data (LOD).
FAIRSpectra - Enabling the FAIRification of Analytical Science
Clustering over the cultural heritage linked open dataset xlendi shipwreck
1. Clustering Over the Cultural Heritage
Linked Open Dataset: Xlendi Shipwreck
Ben Ellefi Mohamed - Nawaf Mohamad Motasem - Sourisseau
Jean Christophe – Gambin Timmy - Castro Filipe - Drap Pierre
SW4CH 2018
2. The Context: Xlendi Shipwreck
The Arpenteur Ontology
The Xlendi LOD dataset
GUI Tool for Clustering
Data Linking Discussion
Conclusion
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3. • This work started on July 2014
• The support of the Superintendence of Cultural Heritage of Malta
• Financed by the National Research Agency
• The framework of the GROPLAN project (http://www.lsis.org/groplan).
• This shipwreck is datable to approximately 7th century BC at a depth of 110 m.
• As one of the best-preserved archaeological sites in Malta datable to the early
Phoenician period.
Archaeology: Timmy Gambin (University of Malta), Jean-Christophe Sourisseau, (CCJ, CNRS)
Marine operation: Bertrand Chemisky, (COMEX)
Photogrammetry: Pierre Drap, (LIS, CNRS)
1 The Context: Xlendi Shipwreck
The bulk of the cargo still remains buried in the sediments.
8. It is not just about 3D …
Analysing the distribution of amphorae can help for understanding this shipwreck.
➢ The nature of the ship ?
➢ The ship destination ?
➢ The origin ?
➢ The content of the cargo ?
(…)
Clustering artifacts by typologies, by orientations, etc.
GROPLAN project (http://www.lsis.org/groplan)
10. In our model we identify three dimensions:
• Typological (height, maximum diameter, volume, ...)
• Photogrammetrical process (bundle model, camera, photographs, ...)
• Spatial (position, convex envelope, ...)
Mohamed BEN ELLEFI, et al. Cultural Heritage Resources Profiling: Ontology-based Approach.
In The 2018 Web Conference Companion, 2018, Lyon, France
2 The Arpenteur Ontology
11. In our model we identify three dimensions:
• Typological (height, maximum diameter,
volume, ...)
• Photogrammetrical process (bundle model, camera, photographs, ...)
• Spatial (position, convex envelope, ...)
2 The Arpenteur Ontology
12. Typological Description
The set of morphological features that characterizes a given CH typology.
➢ Based on this set of features, we are able to identify the typology of a given CH resource.
Xlendi Amphorae Typology Modeling
GROPLAN project (http://www.lsis.org/groplan)
13. Morphological model
(dimension, volume, etc..) Measures are associated to annotations on specific zones
Xlendi Amphorae Typology Modeling
GROPLAN project (http://www.lsis.org/groplan)
14.
15.
16. In our model we identify three dimensions:
• Typological (height, maximum diameter, volume, ...)
• Photogrammetrical process (bundle
model, camera, photographs, ...)
• Spatial (position, convex envelope, ...)
The Arpenteur Ontology2
17. Dives Survey Reports:
• Dives 1: The survey begun at 11:00, 8 passes E-W and 6 passes N-S and the record
finished at 12:20.
➢ The camera has been disposed at the vertical of the site.
• Dives 2: The second survey has been done the 18/07/2014, the survey begun at
11:29 and finished at 12:25. 10 transects E-W and 8 transects N-S
➢ The camera has been disposed at +22.5°
(…)
Photogrammetrical Process Modeling
Photogrammetry Description
The model that describes all the involved components in the photogrammetrical process.
➢ Modeling the relation between CH resources and the corresponding cameras settings, i.e.
resolution, position, orientation, etc.
19. In our model we identify three dimensions:
• Typological (height, maximum diameter, volume, ...)
• Photogrammetrical process (bundle model, camera, photographs, ...)
• Spatial (position, convex envelope, ...)
The Arpenteur Ontology2
20. Spatial Description
The set of features that provide information about the orientation and the location of a given CH
resource in a specific geographical area.
Spatial Distribution Modeling
➢ The shape➢ The localization
33. cluster num 0 nb item4
Data analysis on 4.0 elements
Average 0.5110184066310204
Median 0.5109524164523762
MAD 0.00148657127091667
RMS 0.5900761571720867
Max 0.5130573506564815
Min 0.5091114429628476
Index of Max elem 1.0
Index of Min elem 3.0
Data analysis on 7.0 elements
Average 0.39443207822179266
Median 0.39451410787725383
MAD 0.0012772255320951942
RMS 0.4260424415650642
Max 0.39701713467045296
Min 0.390012183094278
Index of Max elem 0.0
Index of Min elem 6.0
nb Amphorae cluster 11
cluster 0 4
cluster 1 7
cluster 2 4
cluster 3 4
cluster 4 3
cluster 5 4
cluster 6 3
cluster 7 5
cluster 8 3
cluster 9 3
cluster 10 4
GUI Tool for Clustering4
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35.
36.
37. Each setting is so unique that when you dismount the camera and plug it back,
it is no longer the same !
<owl:NamedIndividual
rdf:about="DigitalCamera1962398162">
<rdf:type rdf:resource="DigitalCamera"/>
<hasDistortion
rdf:resource="Distortion1263391254"/>
<hasFocalLength>14.4146</>
<hasFrameHeigthInPixel>2000</l>
<hasFrameWidthInPixel>3008</l>
<hasName>D100_LIS_14mm_H2O</>
…
</owl:NamedIndividual>
SameAs ?
SeeAlso ?
(..)
Data Linking Discussion5
38. ADS triplestore does not contain amphorae data, but rather a SKOS thesaurus of amphorae data types.
http://archaeologydataservice.ac.uk http://data.archaeologydataservice.ac.uk/
Data Linking Discussion5
45. Future Directions and Open Issues
▪ Easy query GUI for archaeologists
▪ Xlendi Dataset need to be linked:
➢ Data source selection …
➢ Automatic linking tools …
➢ Type of links ? (seeAlso, exact, broad, narrow, … )
Conclusion5
46. Thank you for your attention !
➢ Pierre Drap, et al. Underwater
photogrammetry and object modeling: a
case study of Xlendi Wreck in Malta.
In Sensors (2015).
➢ Pierre Drap, et al. Ontology-Based
Photogrammetric Survey in Underwater
Archaeology. In ESWC 2017
➢ Mohamed BEN ELLEFI, et al. Cultural
Heritage Resources Profiling: Ontology-
based Approach. In WWW ’18 Companion
➢ Jérôme Pasquet, et al. Amphora
Detection Based on a Gradient
Weighted Error in a Convolution
Neuronal Network. In IMEKO (2017).
• The ontology: http://www.arpenteur.org/
• The Imareculture project: http://imareculture.weebly.com/
