eindpresentatie ba scriptie
TRANSCRIPT
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Open Data: a design for the provisioning of Dutch public and geo-spatial transport data.Bachelor Thesis: Stef van Grieken
dinsdag 25 januari 2011
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The problem
Government Businesses
dinsdag 25 januari 2011
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Wat we would like to see
dinsdag 25 januari 2011
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The value of government data
0 0,5 1,0 1,5 2,0
Scientific Instruments
Textiles
Printing and Publishing
Public Sector Information
% GDP
Source: Commercial Exploitation of Europe’s Public Sector Information - PIRA Study
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Problem and Causes
Problem: The business potential of government owned transport and geo-spatial data remains untapped in the Netherlands.Causes:Financial: the pricing strategies governments use prevent re-use of dataLegal: law gives governments intellectual property, copyright and database rights Technical: there is no technical infrastructure to deliver the data
dinsdag 25 januari 2011
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Problem and Causes
Problem: The business potential of government owned transport and geo-spatial data remains untapped in the Netherlands.Causes:Financial: the pricing strategies governments use prevent re-use of dataLegal: law gives governments intellectual property, copyright and database rights Technical: there is no technical infrastructure to deliver the data
We leave this one alone
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MethodsIs their an economic case for open data?How does government ICT architecture work?
Who is involved in open data?What is their stake?
How does open data infuence the business case of the stakeholders?
How should the data be delivered to businesses?
Literature Review
Stakeholder Indentification
Business case analysis
Requirements analysis
What solution should we design for the data delivery?What specifications should the data warehouse have?
Datawarehouse design
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Solution
A new business model for the provisioning of public sector information (Open Data)A technical architecture to deliver public transport and geospatial data to businesses (Data Warehouse)
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Design: Business Model
structured, free, machine
readable dataBusinesses Travellers
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Design: Business Model
structured, free, machine
readable dataBusinesses Travellers
Change pricing and legal
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Design: Business Model
structured, free, machine
readable dataBusinesses Travellers
Change pricing and legal
Create Data Warehouse
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Design: Data Warehouse
Railnetwork Operator (1..n)
Data Warehouse
and Interface
Service Operators
Businesses
Transport Authorities
Roadnetwork Operator (1..n)
Traveler
Rail and Road management
Source Data Raw Data Interpreted Data
Creation, Selection
Warehouse Design
Storage, Processing & Packaging Delivery
Data provider
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Service Operator
Route(.code)
Network Operator(.code)
Vehicle(.code)
Connection(.code)
Stop(.code)
maintains
Distance(.KM)
2 ... 1
Name
Name
Type
Name
Capacity(.INT)
maintains <<
Planning Item(.code)
is served by ... during ...
Departure Time(.timestamp)
Arrival Time(.timestamp)
Direction(.STOP)
Price(.EUR)
Location(.GPS)
Location(.GPS)
is Availible
is Available
is Available
has Disabled Acces
has Toilet
Price(.EUR)
Exception(.code)Description
Planning NoteAlternate
Departure Time(.timestamp)
Alternate Arrival Time
(.timestamp)
*Derived fact type from planning item
price
has << has <<
has <<
has << has
>> containshas has has
has
has
has <<
has << has <<has <<
has
contains <<
Platform(.code)
2 ... 1
has Cateringhas <<
uses <<
has <<
Alternate Platform(.code)
has <<*Derived fact type
from platform
bills for
Title
has <<
Design: Data model
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Service Operator
Route(.code)
Network Operator(.code)
Vehicle(.code)
Connection(.code)
Stop(.code)
maintains
Distance(.KM)
2 ... 1
Name
Name
Type
Name
Capacity(.INT)
maintains <<
Planning Item(.code)
is served by ... during ...
Departure Time(.timestamp)
Arrival Time(.timestamp)
Direction(.STOP)
Price(.EUR)
Location(.GPS)
Location(.GPS)
is Availible
is Available
is Available
has Disabled Acces
has Toilet
Price(.EUR)
Exception(.code)Description
Planning NoteAlternate
Departure Time(.timestamp)
Alternate Arrival Time
(.timestamp)
*Derived fact type from planning item
price
has << has <<
has <<
has << has
>> containshas has has
has
has
has <<
has << has <<has <<
has
contains <<
Platform(.code)
2 ... 1
has Cateringhas <<
uses <<
has <<
Alternate Platform(.code)
has <<*Derived fact type
from platform
bills for
Title
has <<
Design: Data model
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Service Operator
Route(.code)
Network Operator(.code)
Vehicle(.code)
Connection(.code)
Stop(.code)
maintains
Distance(.KM)
2 ... 1
Name
Name
Type
Name
Capacity(.INT)
maintains <<
Planning Item(.code)
is served by ... during ...
Departure Time(.timestamp)
Arrival Time(.timestamp)
Direction(.STOP)
Price(.EUR)
Location(.GPS)
Location(.GPS)
is Availible
is Available
is Available
has Disabled Acces
has Toilet
Price(.EUR)
Exception(.code)Description
Planning NoteAlternate
Departure Time(.timestamp)
Alternate Arrival Time
(.timestamp)
*Derived fact type from planning item
price
has << has <<
has <<
has << has
>> containshas has has
has
has
has <<
has << has <<has <<
has
contains <<
Platform(.code)
2 ... 1
has Cateringhas <<
uses <<
has <<
Alternate Platform(.code)
has <<*Derived fact type
from platform
bills for
Title
has <<
Design: Data model
dinsdag 25 januari 2011
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Service Operator
Route(.code)
Network Operator(.code)
Vehicle(.code)
Connection(.code)
Stop(.code)
maintains
Distance(.KM)
2 ... 1
Name
Name
Type
Name
Capacity(.INT)
maintains <<
Planning Item(.code)
is served by ... during ...
Departure Time(.timestamp)
Arrival Time(.timestamp)
Direction(.STOP)
Price(.EUR)
Location(.GPS)
Location(.GPS)
is Availible
is Available
is Available
has Disabled Acces
has Toilet
Price(.EUR)
Exception(.code)Description
Planning NoteAlternate
Departure Time(.timestamp)
Alternate Arrival Time
(.timestamp)
*Derived fact type from planning item
price
has << has <<
has <<
has << has
>> containshas has has
has
has
has <<
has << has <<has <<
has
contains <<
Platform(.code)
2 ... 1
has Cateringhas <<
uses <<
has <<
Alternate Platform(.code)
has <<*Derived fact type
from platform
bills for
Title
has <<
Design: Data model
dinsdag 25 januari 2011
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Discussion
Findings: interviews are consistent with makro economic literature -> businesses expect more competition and increase in innovationFindings: cost structures change at the ‘government’ stakeholder, data providing organizations need to be compensated for loss due to different pricing strategies, or they are forced to drop certain activitiesLegal: intellectual property of some businesses loses value (i.e. Kadaster vs. Tele Atlas)Legal: insuring coverage, quality, privacy and neutrality of data provided by the governmentPolicy: governments need to be aware that data and services are two different things, planning API’s compete with the market
dinsdag 25 januari 2011
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Questions
dinsdag 25 januari 2011