Towards a graph of ancient world geographical knowledge


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Presentation on three collaborative projects: Hestia (, GAP (, and Pelagios (

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Towards a graph of ancient world geographical knowledge

  1. 1. Towards a graph of ancient world geographical knowledge   Elton Barker (The Open University)Elton Barker (The Open University) 11 March, 2014 | Classics and Ancient History seminar, Exeter
  2. 2. Geographical Applications | AMWC: mapping antiquity topographically
  3. 3. Geographical Applications | Orbis: mapping historical networks
  4. 4. Harley (1989)  The object of mapping is to produce a 'correct' relational model of the terrain. Its assumptions are that the objects in the world to be mapped are real and objective, and that they enjoy an existence independent of the cartographer; that their reality can be expressed in mathematical terms; that systematic observation and measurement offer the only route to cartographic truth; and that this truth can be independently verified. The research context | Counter-cartography, spatial humanities, narrative geographie Harris, T. M., Bergeron, S. and Rouse, L. J. (2011)  Much of the interest in GIS has largely revolved around a (re)discovery of the power of the map. The humanities have long been at risk of treating space, the backdrop to all human behavior and events, as being neutral—a spatial vacuum—an isotropic backdrop to human affairs. Indeed, a perusal of many maps incorporated in humanities texts would imply that events take place in landscapes seemingly devoid of any terrain, hydrology, infrastructure, human culture, or other geography. Purves (2010)  Plot's spatial legacy is pervasive in ancient Greek thought, where songs might be conceived as pathways, logoi as routes, writing as the movement of oxen turning back and forth across a field with a plough..., narratives as pictures or landscapes, and plots even as living creatures that take up set areas of space.
  5. 5. How is space mapped discursively in Herodotus’s Histories?  Hestia (2008-2010, 2013-2014), funded by the AHRC  Stefan Bouzarovski, Dept. of Geography, University of Birmingham  Chris Pelling, Christ Church, Oxford  Leif Isaksen, Dept. of Archaeology, University of Southampton Presentation summary | The projects How can we extract and visualize spatial data from texts?  GAP (2010-2011, 2012-2014), funded by Google  Leif Isaksen, Dept. of Archaeology, University of Southampton  Kate Byrne, Institute of Informatics, Edinburgh  Eric Kansa, Open Context, UC at Berkeley  Nick Rabinowitz  Enrico Daga, KMi, The Open University How can we link together the graph of ancient world data?  Pelagios (2011, 2011-2012, 2013-2015), funded by JISC, Mellon  Leif Isaksen, Dept. of Archaeology, University of Southampton  Rainer Simon, Austrian Institute of Technology
  6. 6. But after this (the Persians say), the Greeks were very much to blame; for they invaded Asia before the Persians attacked Europe… “We of Asia did not deign to notice the seizure of our women; but the Greeks, for the sake of a Lacedaemonian woman, recruited a great armada, came to Asia, and destroyed the power of Priam. Ever since then we have regarded Greeks as our enemies.” For the Persians claim Asia for their own, and the foreign peoples that inhabit it; Europe and the Greek people they consider to be separate from them. Herodotus, Histories 1.4 I laugh to see how many have before now drawn maps of the world, not one of them reasonably; for they draw the world as round as if fashioned by compasses, encircled by the Ocean river, and Asia and Europe of a like extent. For myself, I will in a few words indicate the extent of the two, and how each should be drawn. Herodotus, Histories 4.36.2 It was in the reign of Cleomenes that Aristagoras the tyrant of Miletus came to Sparta. When he had an audience with the king, as the Lacedaemonians report, he brought with him a bronze tablet on which the map of all the earth was engraved, and all the sea and all the rivers ( χων χάλκεον πίνακα ν τ γ ς πάσης περίοδοςἔ ἐ ῷ ῆ ἁ νετέτμητο κα θάλασσά τε π σα κα ποταμο πάντεςἐ ὶ ᾶ ὶ ὶ ). Herodotus, Histories 5.49.1. Why is Herodotus ‘good to think with’? | Three passages
  7. 7. ‘going through in detail towns of men both small and great alike: for of the places that were once great, most have now become small, while those that were great in my time were small before’ ( μο ως σμικρ κα μεγ λα στεα νθρ πων πεξι ν· τὁ ί ὰ ὶ ά ἄ ἀ ώ ἐ ώ ὰ γ ρ τ π λαι μεγ λα ν, τ πολλ σμικρ α τ ν γ γονε·ὰ ὸ ά ά ἦ ὰ ὰ ὰ ὐ ῶ έ τ δ π με ν μεγ λα, πρ τερον ν σμικρ , Herodotusὰ ὲ ἐ ᾿ ἐ ῦ ἦ ά ό ἦ ά 1.5) The problem? | Mapping the Histories
  8. 8. The Source | The Perseus digital text
  9. 9. Immediate outcomes | The Database
  10. 10. Immediate outcomes | Top physical places
  11. 11. GIS | all places
  12. 12. Web technologies | Google Earth
  13. 13. Web technologies | The NarrativeMap
  14. 14. Network Analysis | A Qualitative Typology  Definition: place and proxy  Unit: clause analysis (SVO) of Histories 5  Quality: movement and/or transformation  Variables: focalisation, tense/mood Telling a story and following a path are cognate activities, telling a story is ordering events and actions in space and time – it is a form of knowledge making. Diagrams and maps are likewise stories. In science, just as in all knowledge producing traditions, the processes are inherently narratological; they involve the creation of knowledge spaces in which people, practices and places are discursively linked… We make our world in the process of moving through and knowing it. Turnbull (2007)
  15. 15. Network Analysis | The Spaghetti monster
  16. 16. Network Analysis | Total book 5 Sci2 Team (2009) Science of Science (Sci2) Tool. Indiana University & SciTech Strategies
  17. 17. Network Analysis | Category 1: Positioning
  18. 18. Network Analysis | Category 4: Mobile Intervention
  19. 19. Automated Networks | “Territories” in GIS
  20. 20. Automated Networks | Web-browsing Book 5
  21. 21. GAP | The challenge of a million texts…
  22. 22. The concept | There and back again
  23. 23. .txt .html .xml Format conversion Token- isation POS tagging Lemma- tisation Named Entity Recognition .geotagged .xml Geotagging Gazetteer lookup Resolution .geotagged .xml .gaz.xml Georesolution The methodology | Geoparsing
  24. 24. The interface | A Snapshot of the Histories
  25. 25. The interface | The Reading View
  26. 26. The interface | The Place View
  27. 27. 27 …or any other online resource that bears a relation to a particular ancient place! Connecting Ancient World Research Resources through the Places they refer to InscriptionsInscriptions TextsTexts Archaeological Finds Archaeological Finds Museum Objects Museum Objects Archaeological Sites Archaeological Sites Pelagios | linking together the places of our past through the documents that refer to them
  28. 28. 28  Data aggregation  Federated search  Standard data representation  Schema alignment Connectivity through common references rather than a common schemaConnectivity through common references rather than a common schema What Pelagios isn’t | One ring to rule them all
  29. 29. The concept | Don’t Unify the Model – Annotate! 29 pleiades:579885 (Athenae) pleiades:570685 (Sparta)
  30. 30. The outcome | The Pelagios API 30  Context – obtain links to online data that may be relevant to your own  Discovery – users can find your data by following links on other partners’ sites  Reuse – the Pelagios API provides machine-readable representations (JSON, RDF) to enable mashups and other forms of 3rd party re-use
  31. 31. Pelagios API in the Wild | awld.js 31 A JavaScript library for Ancient World Linked Data, developed by Nick Rabinowitz and Sebastian Heath, awld.js adds functionality and visual elements based on links to stable URIs. Pop-ups for Pleiades places link to Pelagios references
  32. 32. Visualization Interface | Heat Mapping Annotations
  33. 33. 33  New periods and areas: incl. Mediaeval, Islamic and Chinese traditions  New challenges: aligning gazetteers; producing annotations; geoparsing texts and maps; developing user interfaces Pelagios phase 3 | Early Geospatial documents (up to 1492) Early Geospatial Documents
  34. 34. Text Annotation Interface | Places in a document (the ‘target’)
  35. 35. Map Interface | Places in the gazetteer (the ‘body’)
  36. 36. 36