1. Open Data Evolution in
Amsterdam
EUROCITIES WG Innovation,27 th Febr 2014, Utrecht
Katalin Gallyas
Open Innovation Policy
Advisor
@KatalinG
2. Open Data. Why?
Public sector staff recognize the importance of open
data, but many are unsure how to use it. (Guardian Research,
June 2013)
3. Open Data Controversial for Local Governments
Open Data chances are unrevealed
for governments.
Open Data Interpretation Illiteracy
but curiosity (something big,
exciting with Open Data is coming)
Who to choose? What to choose?
-Linked Data
-Data Visualization
-Data Mining are unexploited
Loc Gov need a helping hand and
collaboration on Open Data
5. Vocabularies Policy Makers
“What is the evidence that
we should release
datasets?”
“How many start ups have
been created since we
launched the first datasets”
“Can Open Data repair a
market failure, inefficiency?”
9. Precarious Open Data Policies
• Opening, exchanging data between departments of
the city hall
• External: hackathons
still missing in Open Data scenario’s
-Big Data Strategy
-Meaning behind data (visualization, mining)
Connected
-Interoperability of open data based apps
24 hours
-Civic App Store
19. Open Data Evolution in Amsterdam
• In 2010 hackers, innovation labs and SME’s, web
entrepreneurs requested the first datasets
• 28 datasets open in 2011
• Nearly 400 datasets open in 2014 (most popular geo and
transport data)
• 2010 – 0 euro budget
• 2013 – 1,5 M euro budget
• In 2013 Open Data Program – by Amsterdam Economic Board
• 3 EU projects that promote the value of Open Data
20. Best Practices Open Data
• 30 apps have been launched
(face recognition by portrays)
• High educational impact
• Positive PR for the museum
• Reach of new younger
target group
https://www.rijksmuseum.nl/api -110.000 high resolution
photo’s of the collection
23. Open Data Observations
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Linked data & API , commitment from city halls
User feed-back on Open Data.
City Challenges with Open Calls, awards.
Reused codes between cities for better civic apps.
Value of data-mining, visualization
Beyond Opening Up -> Interpretation
24. Open Data Observations
1. Open Data Catalysts are strongly dependent on
external financing and networking - Liberate open data
agents!
2. Vocabularies match between policy makers and open
data catalyst
3. Produce user cases to discover the enormous
underexploited value of data
4. Watch out with corporate Big Data providers
5. Encourage cities to move toward Commons, peer
reviewed open data vendors
28. Smart Data Management
Procure services built on data smartly
Analyze, enrich and interpret data
Generate demand for datasets with high
market potential
Feed-back loop