3. Objectives
•
Develop tools to enable collection and visualization
of events within OpenStreetMap (OSM) platform.
•
Install infrastructure to run OpenStreetMap (OSM)
locally.
•
•
•
Identify strategy for event data entry into OSM.
Develop tools to facilitate data entry.
Create web application for visualization of
collected data.
5. Introduction
•
“Free” : without much legal or technical limitations.
“be creative” [1].
•
Collaborative Ownership (wiki model).
“go online, create an account and start editing”.
•
•
Open database (downloadable) and modifiable.
Open technology.
“all software can be downloaded and run locally free
of cost”.
[1] http://wiki.openstreetmap.org/wiki/List_of_OSM_based_Services
7. OSM data
•
Key = Value pairs (tags) represent
properties.
•
Tags have meaning, affects how they are
rendered in the map.
•
•
Arbitrary tags can be entered.
•
So we decided to setup the database in
our own server.
Maintainers use tools to check if
unwanted tags are present. Fix them and
even ban users.
8. OSM data
OSM data is all about tags.
highway=residential
name=Helene-Mayer-Ring 7
maxspeed=180
maxspeed:winter=80
The community agrees on certain key and value combinations for
tags that are informal standards, documented extensively at [1]
No tags for events “yet”.
[1] http://wiki.openstreetmap.org/wiki/Map_Features
9. What we did
Collect Event
Data
Create Tag
Syntax
Enter into
local
OSM database
Setup local
database
JOSM Editor
plugin
10. What is an event?
An activity associated with a physical location that happened at
certain point or period of time.
Attributes that we capture for an event are:
name
description
category
sub_category
classification.
organization
start_date
end_date
a longer event.
url
numparticipants
howoften
related_items
11. OSM tags for events
Syntax
event:<event_index>:<event_attribute> = value
event_index belongs to [0,1,2,3,..,N]
event_attribute is one of the values like name,
category, subcategory, ...
12. OSM tags for events
name = kaufingerstraße
highway = pedestrian
bicycle = no
cycleway = no
...
event = yes
event:0:name = Christkindlemarkt
event:0:category = social
event:0:sub_category = Fairs / Festivals
...
event:1:name = Munich Carnival
event:1:category = social
event:1:sub_category = Fairs / Festivals
event:1:start_date = 07/01/2013
event:1:end_date = 12/02/2013
event:1:howoften = Yearly
...
Contains two events:
Christkindlemarkt,
Munich Carnival.
25. Event Visualization
Figure 3: Comparison between OpenStreetMap and OpenEventMap table
In OSM current_node_tags table, a single event data is stored across mult
belows:
node_id
event
yes
12345
event:0:name
Oktoberfest
12345
event:0:category
social
12345
event:1:name
Frühlingsfest
12345
Event
database
v
12345
OSM
database
k
event:1:category
social
into
11
The two events are converted into two single rows in search_event table as following:
id
event_type
type_id
number
name
category
subcategory
...
1
node
12345
0
Oktoberfest
social
...
2
node
12345
1
Frühlingsfest
social
...
The search_event table format makes it easier to do complex queries searching more than
26. Event Visualization
Figure 3: Comparison between OpenStreetMap and OpenEventMap table
In OSM current_node_tags table, a single event data is stored across mult
belows:
node_id
event
yes
12345
event:0:name
Oktoberfest
12345
event:0:category
social
12345
event:1:name
Frühlingsfest
12345
Event
database
v
12345
OSM
database
k
event:1:category
social
into
checks for two events are converted into two single rows in search_event table as following:
changes every
11
The
minute
id
event_type
type_id
number
name
category
subcategory
...
1
node
12345
0
Oktoberfest
social
...
2
node
12345
1
Frühlingsfest
social
...
The search_event table format makes it easier to do complex queries searching more than
32. Conclusion
•
•
Objectives accomplished:
•
•
•
•
Infrastructure of OSM installed locally.
Strategy to enter events data developed.
Data entry tool for events developed.
Web application for visualization of collected data created.
Learning Experience:
•
•
•
Working with OSM, Map Server and Map Rendering.
Basics of Cartography and Map making.
Data visualization and its importance.
