Mapping the Maps

Finding the maps; georeferencing them; and categorising them;building from a title index to the 1,000,000 image collection

James Heald (@heald_j),Wikimedia volunteer

With thanks to• Kimberly Kowal, formerly of BL Maps department• Ben O’Steen, Mahendra Mahey, BL Labs

1,000,000 imagesFantastic, but …

Very limited metadata

Very limited metadataWikimedia said no bulk upload

Response…

Create a subject index by book title…

Response…

… initially started by hand, then using class-marks …

… encouraging images to be uploaded by the book(20,000 so far – mostly by one man)

… however, manual categorisation of images isvery very time-consuming.

Could anything be done more automatically…

?

Maps: natural classification, given co-ordinates

Could anything be done more automatically…

?

First step: find the maps on Flickr, and tag them…

… using the index to drive the process

31 Oct

… using the index to drive the process

31 Oct

… using the index to drive the process

31 Oct

… using the index to drive the process

03 Nov

… using the index to drive the process

17 Dec

… using the index to drive the process

19 Dec

But how many maps were there ?

Oct 31

But how many maps were there ?

Oct 31

But how many maps were there ?

Nov 2

But how many maps were there ?

Nov 7

But how many maps were there ?

Nov 14

But how many maps were there ?

Dec 1

But how many maps were there ?

Dec 10

But how many maps were there ?

Dec 17

But how many maps were there ?

Dec 28

-- including 20,000 found independently by @Quasimondo, machine-assisted using his own pattern recognition methods

50,000 maps in all:

classmark detailed totals index index ------ ---------- ----------- misc 16074 14091 1983

Europe 13136 6254 6882British Isles 7191 269 6922North America 6758 1524 5234 USA 5782 1209 4573Asia 2736 1280 1456Africa 2300 1075 1225South America 895 659 236

Where do the maps depict, in detail ?

Next step: Geo-referencing

classmark detailed totals index index ------ ---------- ----------- misc 16074 14091 1983

Europe 13136 6254 6882British Isles 7191 269 6922North America 6758 1524 5234 USA 5782 1209 4573Asia 2736 1280 1456Africa 2300 1075 1225South America 895 659 236

Again, use the index to drive the process…

… with Flickr tags to keep track

A link on the Flickr page…

Geo-location, using the Klokan/BL Georeferencer

(Free alternatives are also available)

… leads to the Georeferencer

Identify corresponding points by adding pins to the old map and the new map

… leads to the Georeferencer

Success allows the old map to be laid over the top of a modern one

which can then be zoomed in and out and faded up and down

Maps can then be characterised by location

... and by zoom-level

04

... or both together

05

... or both together

06

... or both together

07

... or both together

08

... or both together

09

... or both together

10

... or both together

11

... or both together

12

... or both together

13

... or both together

14

... or both together

15

... or both together

16

... or both together

17

... or both together

18

... or both together

19

... or both together

20

... or both together

21

... or both together

For classification, we would like toidentify geographical entities…

With coordinates, we can do this, using place-name lookup services to identify named regions…

eg: OSM Nominatim, 4 votes out of 5Continent=Europe, Country=France, then no consensus

Tagging these regions, we can now extract maps at a given zoom for individual continents …

… countries …

… nation …

… nations …

… cities …

… and beyond

… and beyond.

All easily retrievable using Flickr tags…

All easily retrievable using Flickr tags…… ready to be uploaded to Wikimedia.

All easily retrievable using Flickr tags…… ready to be uploaded to Wikimedia.

Live-updated data also downloadable -

All easily retrievable using Flickr tags…… ready to be uploaded to Wikimedia.

links http://commons.wikimedia.org/wiki/COM:BL_MAPS