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Map Gardening in Practice: Tracing Patterns of Growth and Maintenance in OpenStreetMap

Map Gardening in Practice: Tracing Patterns of Growth and Maintenance in OpenStreetMap

Alan McConchie

April 24, 2015
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  1. [email protected] // @mappingmashups // #AAG2015 // Session 4444 Map Gardening

    in Practice: Tracing Patterns of Growth and Maintenance in OpenStreetMap Alan McConchie PhD Candidate, University of British Columbia Design Technologist, Stamen Design [email protected] // @mappingmashups Association of American Geographers Annual Meeting April 24, 2015 1
  2. [email protected] // @mappingmashups // #AAG2015 // Session 4444 1. Editing

    existing features is as important as adding new ones 3
  3. [email protected] // @mappingmashups // #AAG2015 // Session 4444 2. OSM

    is a hybrid of volunteered data and imported datasets 4
  4. [email protected] // @mappingmashups // #AAG2015 // Session 4444 Hypotheses/questions: 1.

    do the “explorers” stick around? 2. do imports hinder growth of community? 3. does activity shift to “gardening”? 5
  5. [email protected] // @mappingmashups // #AAG2015 // Session 4444 OSM TIGER

    Import Stands for “Topologically Integrated Geographic Encoding and Referencing” TIGER is a product of the United States Census Bureau, therefore in the Public Domain OpenStreetMap imported TIGER’s 2005 data starting in late 2007: animation: wiki.osm.org/wiki/Tiger 6
  6. [email protected] // @mappingmashups // #AAG2015 // Session 4444 Just last

    Saturday, I discovered that the edits I made in Aylmer and Hull — suburbs of Gatineau, Quebec that I know very well, because I pass through them every time I go to Ottawa — had been replaced by a batch import from CanVec. It removed a lot of human intelligence that I had added to the existing streets, such as pedestrian crossings, traffic lights, and turning circles. It also obliterated service roads, and turned all streets into highway=unclassified instead of residential, tertiary, or secondary, and divided highways into two- way streets. And any areas that had shared a node with a street way were now bollixed up. In other words, a big mess to revert, or to fix: the CanVec data had some useful information to add to the map — but not at the cost of erasing hours upon hours of existing work. My work. I was pissed[…] My basic point was, and is, the following: that you’re not going to get local people to contribute to OSM if they believe that their edits are going to be wiped out by the next person to import a pile of data. Jonathan Crowe, 2011 (emphasis mine) http://www.maproomblog.com/2011/02/the_state_of_openstreetmap_in_canada.php 15
  7. [email protected] // @mappingmashups // #AAG2015 // Session 4444 OSM is

    part of a greater movement of collaborative productivity, where people all over the world can and do join forces to create something great, something of value. I believe that in 40 years, probably even in 15, hardly anything of the data we have collected will retain much value - but we will have been part of a great development, and mankind will be the better for it. Will OSM, instead of being the social endeavor of “a great map that people made themselves”, then be the technical challenge of “the geo database where a few clever guys managed to combine lots of existing data”? Frederik Ramm, 2012 (emphasis mine) https://lists.openstreetmap.org/pipermail/talk-us/2012-December/009966.html 16
  8. [email protected] // @mappingmashups // #AAG2015 // Session 4444 A popular

    (although not universally accepted) theory is that massive imports are to blame for slowing down the development of the US community. …instead of the fun task of going out, finding new streets, and filling in a blank map, new contributors in the US were now faced with the relative tedium of correcting repetitive errors in an existing dataset. Meanwhile, in countries like Germany, almost all data has been collected by volunteer mappers, with only a few small-scale imports conducted in places where there already was an active community. This was not by design - there simply wasn't a comparable dataset that could have been imported - but it was ultimately beneficial. At least if you accept the theory, of course. Tobias Knerr, 2015 (emphasis mine) http://forum.openstreetmap.org/viewtopic.php?id=30121 17
  9. [email protected] // @mappingmashups // #AAG2015 // Session 4444 Current best

    practice wiki.osm.org / wiki / Import / Guidelines 18
  10. [email protected] // @mappingmashups // #AAG2015 // Session 4444 Community Imports

    • Divide data into chunks • Community members manually upload each chunk NOTE: The term "Import" is highly loaded in the OSM community. "A distributed and curated merge," is a more accurate description of what Seattle OSM planning to do. — wiki.osm.org/wiki/Seattle_Import 19
  11. [email protected] // @mappingmashups // #AAG2015 // Session 4444 Building community

    through imports Four training events and editathons Five events out walking around 20+ active participants slideshare.net/gwhathistory/osm-sotm-us-2013-imports4community-002 20
  12. [email protected] // @mappingmashups // #AAG2015 // Session 4444 NYC community

    building import • Estimated 1500 hours of work • Volunteers + Mapbox employees • Coordination with NYC GIS Dept animation: mapbox.com/blog/nyc-buildings-openstreetmap 21
  13. [email protected] // @mappingmashups // #AAG2015 // Session 4444 24 Zielstra,

    Dennis, Hartwig H. Hochmair, and Pascal Neis. 2013. Assessing the Effect of Data Imports on the Completeness of OpenStreetMap - A United States Case Study. Transactions in GIS 17, no. 3 (June): 315–334. The impact of the TIGER import on OSM completeness
  14. [email protected] // @mappingmashups // #AAG2015 // Session 4444 25 Neis,

    Pascal, Dennis Zielstra, and Alexander Zipf. 2013. Comparison of Volunteered Geographic Information Data Contributions and Community Development for Selected World Regions. Future Internet 5, no. 2 (June 3): 282–300. Comparison of OSM in various cities:
  15. [email protected] // @mappingmashups // #AAG2015 // Session 4444 “A  WikiGardener

     is  a  person  who  goes  around  the  wiki,  correcting   typos  here,  rearranging  things  to  be  more  readable  there.  In  general,   good  WikiGardeners  are  liked  and  respected,  since  they  have  the   magical  ability  to  take  a  jumble  of  pages  and  create  good,  readable   text  out  of  them.  Anyone  can  be  a  WikiGardener.  If  you  see  a  typo  or   a  spelling  mistake,  feel  free  to  correct  it!  If  you  feel  up  to  it,  rearrange   a  page,  or  split  a  long  page  to  smaller  pages,  or  if  you  think  some  page   belongs  to  some  WikiCategory,  add  a  link  to  it.  If  you  make  a  mistake,   don't  worry  about  it,  since  everything  you  do  can  be  restored.  Also,   remember  to  add  a  change  note  when  doing  your  wikigardening.”                     http://www.jspwiki.org/wiki/WikiGardener                                                                           26 Wiki  Gardening
  16. [email protected] // @mappingmashups // #AAG2015 // Session 4444 • Complete

     history  dump  of  OSM  up  to  December  31,  2014   • Extract  a  small  number  of  study  areas   • Only  look  at  nodes,  disregard  all  other  data  types   • Overlay  grid  (1  km)   • Find  earliest  node  in  each  grid  cell   • For  each  username,  count  following  values:   Number  of  total  node  edits     Number  of  version  1  edits  (node  creation)   Number  of  version  2+  edits  (move  node  or  change  attributes)   Number  of  edits  in  “blank  spots  on  the  map”   • Only  count  a  user's  activity  within  each  study  area.   27 The  analysis
  17. [email protected] // @mappingmashups // #AAG2015 // Session 4444 30 Central

    London with 1000m grid First OSM nodes in each cell
  18. [email protected] // @mappingmashups // #AAG2015 // Session 4444 31 Downtown

     Vancouver    1000m  grid   First  OSM  nodes  in  each  cell
  19. [email protected] // @mappingmashups // #AAG2015 // Session 4444 33 Greater

     London:   OSM  contributors  plotted  by   number  of  “blank  spot”  edits   and  number  of  total  edits.   Circles  are  individuals  editors   sized  according  to  number  of   days  active   London
  20. [email protected] // @mappingmashups // #AAG2015 // Session 4444 34 San

     Francisco  Bay  Area:   OSM  contributors  plotted  by   number  of  “blank  spot”  edits   and  number  of  total  edits.   Circles  are  individuals  editors   sized  according  to  number  of   days  active   Bay Area
  21. [email protected] // @mappingmashups // #AAG2015 // Session 4444 35 Selected

    bounding boxes around approximate extent of urban areas Bounding box population estimated using Gridded Population of the World dataset for year 2000 (GPWv3) London Population 8,500,000 Land area 3300 sq km Berlin Population 1,900,000 Land area 2100 sq km Seattle Population 3,200,000 Land area 6300 sq km
  22. [email protected] // @mappingmashups // #AAG2015 // Session 4444 36 Area

    (sq km) Population (thousands) 100,000 10,000 1,000 100 1,000 10,000
  23. [email protected] // @mappingmashups // #AAG2015 // Session 4444 37 Total

    edited nodes by month (new nodes + modified nodes) TIGER imports Boston building import Haiti earthquake Paris building import second Boston import NYC building imports seattle building import
  24. [email protected] // @mappingmashups // #AAG2015 // Session 4444 38 Total

    modified nodes by month Modification history lost before OSM API v0.5 Berlin Haiti Berlin Bay Area Montevideo London New York Bay Area Los Angeles Paris Los Angeles
  25. [email protected] // @mappingmashups // #AAG2015 // Session 4444 39 Total

    “blankspot” nodes by month Haiti TIGER imports
  26. [email protected] // @mappingmashups // #AAG2015 // Session 4444 40 Total

    edited nodes by month normalized by area Boston Boston Amsterdam Amsterdam Paris
  27. [email protected] // @mappingmashups // #AAG2015 // Session 4444 41 Total

    edited nodes by month normalized by population Boston Boston Amsterdam Montevideo
  28. [email protected] // @mappingmashups // #AAG2015 // Session 4444 42 Total

    edited nodes by month: London (new nodes + modified nodes)
  29. [email protected] // @mappingmashups // #AAG2015 // Session 4444 43 Total

    created nodes by month: London (new nodes only)
  30. [email protected] // @mappingmashups // #AAG2015 // Session 4444 44 Total

    created nodes by month: London (modified nodes only)
  31. [email protected] // @mappingmashups // #AAG2015 // Session 4444 46 Total

    edited nodes by month: London red: blankspot contributors light blue: non-blankspot contributors
  32. [email protected] // @mappingmashups // #AAG2015 // Session 4444 47 Created

    nodes by month: London red: blankspot contributors light blue: non-blankspot contributors
  33. [email protected] // @mappingmashups // #AAG2015 // Session 4444 48 Modified

    nodes by month: London red: blankspot contributors light blue: non-blankspot contributors
  34. [email protected] // @mappingmashups // #AAG2015 // Session 4444 49 Total

    edited nodes by month: London solid line: aggregated blankspot contributors (n = 130) dotted line: aggregated non-blankspot contributors (n = 5488)
  35. [email protected] // @mappingmashups // #AAG2015 // Session 4444 50 Total

    created nodes by month: London solid line: aggregated blankspot contributors (n = 130) dotted line: aggregated non-blankspot contributors (n = 5488)
  36. [email protected] // @mappingmashups // #AAG2015 // Session 4444 51 Total

    modified nodes by month: London solid line: aggregated blankspot contributors (n = 130) dotted line: aggregated non-blankspot contributors (n = 5488)
  37. [email protected] // @mappingmashups // #AAG2015 // Session 4444 52 Total

    edited nodes by month: Berlin solid line: aggregated blankspot contributors (n = 109) dotted line: aggregated non-blankspot contributors (n = 6893)
  38. [email protected] // @mappingmashups // #AAG2015 // Session 4444 53 Total

    created nodes by month: Berlin solid line: aggregated blankspot contributors (n = 109) dotted blue: aggregated non-blankspot contributors (n = 6893)
  39. [email protected] // @mappingmashups // #AAG2015 // Session 4444 54 Total

    modified nodes by month: Berlin solid line: aggregated blankspot contributors (n = 109) dotted blue: aggregated non-blankspot contributors (n = 6893)
  40. [email protected] // @mappingmashups // #AAG2015 // Session 4444 55 Total

    edited nodes by month: Moscow solid line: aggregated blankspot contributors (n = 79) dotted line: aggregated non-blankspot contributors (n = 3268)
  41. [email protected] // @mappingmashups // #AAG2015 // Session 4444 56 Total

    created nodes by month: Moscow solid line: aggregated blankspot contributors (n = 79) dotted line: aggregated non-blankspot contributors (n = 3268)
  42. [email protected] // @mappingmashups // #AAG2015 // Session 4444 57 Total

    modified nodes by month: Moscow solid line: aggregated blankspot contributors (n = 79) dotted line: aggregated non-blankspot contributors (n = 3268)
  43. [email protected] // @mappingmashups // #AAG2015 // Session 4444 58 Total

    created nodes by month: Toronto solid line: aggregated blankspot contributors (n = 58) dotted line: aggregated non-blankspot contributors (n = 1395)
  44. [email protected] // @mappingmashups // #AAG2015 // Session 4444 59 Total

    modified nodes by month: Toronto solid line: aggregated blankspot contributors (n = 58) dotted line: aggregated non-blankspot contributors (n = 1395)
  45. [email protected] // @mappingmashups // #AAG2015 // Session 4444 60 Total

    modified nodes by month: Vancouver solid line: aggregated blankspot contributors (n = 72) dotted line: aggregated non-blankspot contributors (n = 1004)
  46. [email protected] // @mappingmashups // #AAG2015 // Session 4444 61 Total

    modified nodes by month: Vancouver solid line: aggregated blankspot contributors (n = 72) dotted line: aggregated non-blankspot contributors (n = 1004)
  47. [email protected] // @mappingmashups // #AAG2015 // Session 4444 62 Total

    modified nodes by month: Haiti solid line: aggregated blankspot contributors (n = 317) dotted line: aggregated non-blankspot contributors (n = 1120)
  48. [email protected] // @mappingmashups // #AAG2015 // Session 4444 63 Total

    modified nodes by month: Haiti solid line: aggregated blankspot contributors (n = 317) dotted line: aggregated non-blankspot contributors (n = 1120)
  49. [email protected] // @mappingmashups // #AAG2015 // Session 4444 64 Total

    created nodes by month: Four U.S. cities solid lines: aggregated blankspot contributors (Bay Area n = 119, Seattle = 54, New York = 61, Boston = 27) dotted lines: aggregated non-blankspot contributors (Bay Area n = 3485, Seattle = 2067, New York = 3116, Boston = 1406)
  50. [email protected] // @mappingmashups // #AAG2015 // Session 4444 65 Total

    modified nodes by month: Four U.S. cities solid lines: aggregated blankspot contributors (Bay Area n = 119, Seattle = 54, New York = 61, Boston = 27) dotted lines: aggregated non-blankspot contributors (Bay Area n = 3485, Seattle = 2067, New York = 3116, Boston = 1406)
  51. [email protected] // @mappingmashups // #AAG2015 // Session 4444 Discussion: •

    Power law effects trump everything else. • Gradual shift to new contributors (less so in Canada!) • Subtle shift to maintenance tasks… • …but there are always new things to add. • Maintenance is “bursty”, like additions are. • Do imports hinder the growth of community? 66
  52. [email protected] // @mappingmashups // #AAG2015 // Session 4444 Discussion: •

    Power law effects trump everything else. • Gradual shift to new contributors (less so in Canada!) • Subtle shift to maintenance tasks… • …but there are always new things to add. • Maintenance is “bursty”, like additions are. • Do imports hinder the growth of community? 67 …not very clear cut at all
  53. [email protected] // @mappingmashups // #AAG2015 // Session 4444 @mappingmashups [email protected]

    68 http://almccon.github.io/mapgardening/timeseries.html (work in progress: use at own risk!) Thanks!