Presentation given to H.Dip. in Data Analytics and Visualisation at National University of Ireland Galway on 19/11/2020

1. Mapping the accessibility of cities through
Crowdsourcing and Data Analytics
Bianca Pereira
H. Dip. Class - 19/11/2020

2. Bianca Pereira
Researcher in Data Semantics
(“Knowledge Graphs”)
Diversity and Inclusion Long Distance Walking

3. How it started?
SOURCE: Galway Politics Live https://www.youtube.com/watch?v=ZNjoDFDIDE4

4. SOURCE: Mapillary SOURCE: Open Street Maps

5. What are the accessible areas of the city?

6. @crowd4access
Current Initiatives
https://agefriendlyireland.ie/category/publications/guidelines-t
oolkits/
Study from Ability West
HackDublin
?

7. It is a
Data Problem!
SOURCE: https://overpass-turbo.eu/ with data from Open Street Maps.

8. @crowd4access
Crowd4Access
Experience Sharing
Workshops
Data Analytics for Mapping Mapping Workshops

9. HCI Challenges

10. Experience Sharing
Workshops
"
If you ask users of
manual wheelchairs
you will know pretty much
all accessibility issues.
"
Challenge 1. Listening to the right user

11. @crowd4access
Accessibility - A matter of diversity

12. @crowd4access
Accessibility - A matter of diversity

13. Accessibility - A matter of diversity

14. @crowd4access
Key Features

15. Data Analytics for Mapping
"
You can just give an
accessibility score
to each footpath.
There are already too many
elements in the map.
"
Challenge 2. Conflicting objectives

16. Semantic Description of Footpaths
highway = road
sidewalk = both
accessibility_score = 3

17. Semantic Description of Footpaths
kerb = flushed
tactile_paving = yes
footway = crossing
crossing = traffic_signals
kerb = flushed
tactile_paving = yes

18. Mapping Workshops
Challenge 3. Making mapping easier
"
You will need a
professional mapping team
"

19. Kerb
Lowered (3cm)
Flush (0cm)
Raised (~5cm)

20. Street crossing
unmarked

21. Street crossing
uncontrolled
SOURCE: Mapillary

22. Street crossing
traffic_signals

23. Mapping Workshops
"
I have no idea what to map
and how to map,
how can I volunteer then?
"
Challenge 4. Educating the user

24. Learning Materials

25. Mapping Workshops
"
What is the
commitment expected
for this initiative?
Where do you plan to map?
"
Challenge 5. Participants' concerns

26. Volunteer Group

27. Mapillary
https://mapillary.com/

28. Mapping Workshops
"
How do the results look like?
Will this data really be useful?
"
Challenge 6. Visualising the results

29. Maps for the Blind
https://touch-mapper.org/en/map?map=Bdcf81
adbb84565a

30. Pictures Taken
https://www.mapillary.com/app/org/crowd4acc
ess?lat=53.28241607477122&lng=-9.007200027
872386&z=12.079339755242982&tab=uploads

31. Data Collected
https://www.openstreetmap.org/#map=18/53.2
9033/-9.04153

32. Data Collected
https://overpass-turbo.eu/#

33. Data Collected
http://umap.openstreetmap.fr/en/map/footpath
-access-in-mount-merrion_523939#15/53.2959/-
6.2067

34. Possible Applications
https://openrouteservice.org/example-optimize-
pub-crawl-with-ors/

35. HCI Opportunities

36. @crowd4access
Data Available
Image dataset for detection of
Urban Elements
Geographical database that can
be queried
Open Data Commons Open Database
License (ODbL)
Creative Commons

37. @crowd4access
OpenSource Applications
https://wiki.openstreetmap.org/wiki/Downloading_dataOpenStreetMap
https://github.com/tyrasd/overpass-turboOverpass Turbo
https://github.com/umap-project/umapUMAP
https://github.com/GIScience/openrouteserviceOpenRouteService

38. @Crowd4Access
crowd4access@insight-centre.org
http://crowd4access.insight-centre.org
@bianca_oli_per
bianca.pereira@insight-centre.org
Bianca Pereira