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Real-time Visualisation of Cultural
Heritage and Environmental Archaeology
Data in Landscape Reconstructions
Marcus Smith, Riksantikvarieämbetet
Philip Buckland, Umeå University
marcus.smith@raa.se
phil.buckland@umu.se
ArkHack
• May 2013, hack day hosted at RAÄ in Visby; “ArkHack”
• RAÄ, Kb, SEAD, HUMLab
• Goal: develop information infrastructure for archaeology,
cultural heritage and environment by linking data
• Participants at different stages of linked data:
– Kb (Libris) highly structured, queryable, linked open
RDF from the ground up;
– SEAD also highly structured, but relational, not linked
RDF;
– RAÄ (K-samsök) queryable linked RDF, but coarse
and sometimes inconsistent
SEAD data to RDF
• Divided up into teams:
– Link Libris & K-samsök using SPARQL to find objects
in common
– Interface and UX
– Map a subset of SEAD data to RDF
– Vision and use-cases
• Surprisingly successful!
• Stay tuned for more ArkHacks in 2014!
How might this information be used…

…beyond simply being present as another
source in K-samsök?
Environmental Reconstruction
• Linked data about a
landscape during a
timeslice
• Drawn together from a
variety of sources
• Making complementary
inferences from
different data
• Animating timeslices to
illustrate changes over
time
Using paleoenvironmental data to reconstruct
the environment and climate
Using paleoenvironmental data to reconstruct
the environment and climate
Using paleoenvironmental data to reconstruct
the environment and climate

Buckland & co.

Sugita, Bunting etc.
Using paleoenvironmental data to reconstruct
the environment and climate – multiple sites...

Buckland & co.

Sugita, Bunting etc.
… at and around sites and monuments.
… at and around sites and monuments.
… at and around sites and monuments.
… at and around sites and monuments.

With lots of clever mathematics, programming and GIS!
And qualitative interpretation.
Potential Data Sources
• K-samsök
– Sites & monuments from FMIS
– Finds from 40+ national and regional museums
– Fieldwork documentation (not yet!)
• SEAD (not LOD – yet!)
• TORA (doesn’t exist yet, but will be LOD)
– Settlement patterns
• Lantmäteriet (not LOD)
– Historic maps
– National height model
• SGU (machine-readable, but neither linked nor open)
– Geology and bedrock surveys, soils, vegetation, climate
• GBIF – Biodiversity (limited)
• (Some of these data are accessible via INSPIRE Geodata portal)
Real-time Visualisation of Cultural Heritage and Environmental Archaeology Data in Landscape Reconstructions
Places a site in a broader context,
• …which is why we want to do it.
• You simply cannot understand a place completely from the modern
landscape. Digital Terrain Models (DTMs) are only part of the story.
• Help understand:
– A more complete and real landscape picture pre/during/post
construction/settlement
– Why they built it/settled there
– What they were thinking
– How they interacted with the environment
Further possibilities
• References from structured texts using contemporary
historical sources & literature:
– MENOTA http://menota.org/
– Skaldic Project http://abdn.ac.uk/skaldic/
– IEM http://www.nabohome.org/iem/
• A service that can accept all this data, and spit it out a
beautifully-rendered 3D model.
Further possibilities
• References from structured texts using contemporary
historical sources & literature:
– MENOTA http://menota.org/
– Skaldic Project http://abdn.ac.uk/skaldic/
– IEM http://www.nabohome.org/iem/
• A service that can accept all this data, and spit it out a
beautifully-rendered 3D model. (How hard can it be?!)
Further possibilities
• References from structured texts using contemporary
historical sources & literature:
– MENOTA http://menota.org/
– Skaldic Project http://abdn.ac.uk/skaldic/
– IEM http://www.nabohome.org/iem/
• A service that can accept all this data, and spit it out a
beautifully-rendered 3D model. (How hard can it be?!)
• Educational systems and games.
(How hard can it be?!)
•
•
•
•

A “non-trivial” task…
Different approaches for different proxies and goals
Integrating these into single landscape output…
What is scientifically useful is not often pretty...

Sugita etc.

Bunting, Middleton & Twiddle
How far have we come?

Biodiversity, Literature,
Palaeoenvironment,
Cultural Heritage &
Museisök

API

Google

Tidsresan/
Time Mash

Kringla.nu

Fornfynd IOS

K-SAMSÖK
(RAÄ)

Libris

Wikipedia, Wikimedia
Wikipedia

(KB, RAÄ litt)

SEAD

(civilsamhället)
(society)

Historic
environment
RAÄ

LänsLänsLänsmuseum
Länsmuseum
museum
Museum
museum

LänsLänsmuseum
LänsLocal
museum
museum
societies
http://www.kringla.nu/

http://www.kringla.nu/kringla/objekt?refe
rens=raa/fmi/10149301140001
Query results

Google maps

Wikimedia

FMIS/Fornsök

Wikipedia (UGC)

Wikimedia (UGC)

Linkad data
via
K-samsök
x

Occupation
x

Occupation
Challenges
• The data are not linked, services not in place… yet!
• Coverage of paleoenvironmental data is geographically and
chronologically patchy.
• Coverage of proxies is patchy.
• Extrapolation from the “closest” surrounding data points (in time and
space) reduces reliability(?)
• Interpretation is not neutral/objective - depends on models used.
• Visualizing (variability in) accuracy, precision & equifinality.
• Different users prefer different types of visualization.
• Uniting forces of existing computer models for palaeoenvironmental
reconstruction? Multidisciplinary science is difficult and hard to fund.
Prerequisites
But much of the rest of the infrastructure for the data itself already
exists:
• FMIS
• SEAD
• K-samsök for managing/aggregating linked data sources
• Lantmäteriet
• SGU
• GEORG (older) and KARL (younger) geometric maps from RA
• Structured historical texts
And others are on the horizon:
• DAP
• TORA
• Excavation database(s)?
phil.buckland@umu.se
marcus.smith@raa.se

If one nerd can
solve anything,
many nerds can
solve everything.

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Real-time Visualisation of Cultural Heritage and Environmental Archaeology Data in Landscape Reconstructions

  • 1. Real-time Visualisation of Cultural Heritage and Environmental Archaeology Data in Landscape Reconstructions Marcus Smith, Riksantikvarieämbetet Philip Buckland, Umeå University marcus.smith@raa.se phil.buckland@umu.se
  • 2. ArkHack • May 2013, hack day hosted at RAÄ in Visby; “ArkHack” • RAÄ, Kb, SEAD, HUMLab • Goal: develop information infrastructure for archaeology, cultural heritage and environment by linking data • Participants at different stages of linked data: – Kb (Libris) highly structured, queryable, linked open RDF from the ground up; – SEAD also highly structured, but relational, not linked RDF; – RAÄ (K-samsök) queryable linked RDF, but coarse and sometimes inconsistent
  • 3. SEAD data to RDF • Divided up into teams: – Link Libris & K-samsök using SPARQL to find objects in common – Interface and UX – Map a subset of SEAD data to RDF – Vision and use-cases • Surprisingly successful! • Stay tuned for more ArkHacks in 2014!
  • 4. How might this information be used… …beyond simply being present as another source in K-samsök?
  • 5. Environmental Reconstruction • Linked data about a landscape during a timeslice • Drawn together from a variety of sources • Making complementary inferences from different data • Animating timeslices to illustrate changes over time
  • 6. Using paleoenvironmental data to reconstruct the environment and climate
  • 7. Using paleoenvironmental data to reconstruct the environment and climate
  • 8. Using paleoenvironmental data to reconstruct the environment and climate Buckland & co. Sugita, Bunting etc.
  • 9. Using paleoenvironmental data to reconstruct the environment and climate – multiple sites... Buckland & co. Sugita, Bunting etc.
  • 10. … at and around sites and monuments.
  • 11. … at and around sites and monuments.
  • 12. … at and around sites and monuments.
  • 13. … at and around sites and monuments. With lots of clever mathematics, programming and GIS! And qualitative interpretation.
  • 14. Potential Data Sources • K-samsök – Sites & monuments from FMIS – Finds from 40+ national and regional museums – Fieldwork documentation (not yet!) • SEAD (not LOD – yet!) • TORA (doesn’t exist yet, but will be LOD) – Settlement patterns • Lantmäteriet (not LOD) – Historic maps – National height model • SGU (machine-readable, but neither linked nor open) – Geology and bedrock surveys, soils, vegetation, climate • GBIF – Biodiversity (limited) • (Some of these data are accessible via INSPIRE Geodata portal)
  • 16. Places a site in a broader context, • …which is why we want to do it. • You simply cannot understand a place completely from the modern landscape. Digital Terrain Models (DTMs) are only part of the story. • Help understand: – A more complete and real landscape picture pre/during/post construction/settlement – Why they built it/settled there – What they were thinking – How they interacted with the environment
  • 17. Further possibilities • References from structured texts using contemporary historical sources & literature: – MENOTA http://menota.org/ – Skaldic Project http://abdn.ac.uk/skaldic/ – IEM http://www.nabohome.org/iem/ • A service that can accept all this data, and spit it out a beautifully-rendered 3D model.
  • 18. Further possibilities • References from structured texts using contemporary historical sources & literature: – MENOTA http://menota.org/ – Skaldic Project http://abdn.ac.uk/skaldic/ – IEM http://www.nabohome.org/iem/ • A service that can accept all this data, and spit it out a beautifully-rendered 3D model. (How hard can it be?!)
  • 19. Further possibilities • References from structured texts using contemporary historical sources & literature: – MENOTA http://menota.org/ – Skaldic Project http://abdn.ac.uk/skaldic/ – IEM http://www.nabohome.org/iem/ • A service that can accept all this data, and spit it out a beautifully-rendered 3D model. (How hard can it be?!) • Educational systems and games.
  • 20. (How hard can it be?!) • • • • A “non-trivial” task… Different approaches for different proxies and goals Integrating these into single landscape output… What is scientifically useful is not often pretty... Sugita etc. Bunting, Middleton & Twiddle
  • 21. How far have we come? Biodiversity, Literature, Palaeoenvironment, Cultural Heritage &
  • 22. Museisök API Google Tidsresan/ Time Mash Kringla.nu Fornfynd IOS K-SAMSÖK (RAÄ) Libris Wikipedia, Wikimedia Wikipedia (KB, RAÄ litt) SEAD (civilsamhället) (society) Historic environment RAÄ LänsLänsLänsmuseum Länsmuseum museum Museum museum LänsLänsmuseum LänsLocal museum museum societies
  • 24. Query results Google maps Wikimedia FMIS/Fornsök Wikipedia (UGC) Wikimedia (UGC) Linkad data via K-samsök
  • 27. Challenges • The data are not linked, services not in place… yet! • Coverage of paleoenvironmental data is geographically and chronologically patchy. • Coverage of proxies is patchy. • Extrapolation from the “closest” surrounding data points (in time and space) reduces reliability(?) • Interpretation is not neutral/objective - depends on models used. • Visualizing (variability in) accuracy, precision & equifinality. • Different users prefer different types of visualization. • Uniting forces of existing computer models for palaeoenvironmental reconstruction? Multidisciplinary science is difficult and hard to fund.
  • 28. Prerequisites But much of the rest of the infrastructure for the data itself already exists: • FMIS • SEAD • K-samsök for managing/aggregating linked data sources • Lantmäteriet • SGU • GEORG (older) and KARL (younger) geometric maps from RA • Structured historical texts And others are on the horizon: • DAP • TORA • Excavation database(s)?
  • 29. phil.buckland@umu.se marcus.smith@raa.se If one nerd can solve anything, many nerds can solve everything.

Editor's Notes

  1. ArkHack, goal to develop information infrastructure for archaeology, cultural heritage and environment by linking data.
  2. Some success in translating SEAD data to RDF.
  3. But how might this information be used, beyond simply being present as another source in K-samsök?
  4. But how might this information be used, beyond simply being present as another source in K-samsök?
  5. Archaeology important in complete landscape reconstruction – cannot separate people & nature when reconstructing (or predicting)
  6. Different reconstruction methods vary in complexity, transparency, transferability, flexibility (cf. data quality), comparability (between sites)
  7. Lot of work to do on the archaeological database front...
  8. Despite the fact that the SEAD data isn’t yet linked, and we don’t have a service that can automatically extrapolate ancient climate/environment from an arbitrarily selected dataset, much