ODI Futures - Milton Keynes and the future of open data and being a smart city by Gerd Kortuem
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Transcript of ODI Futures - Milton Keynes and the future of open data and being a smart city by Gerd Kortuem
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Prof Gerd Kortuem @kortuem
www.kortuem.com [email protected]
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28000 New Homes
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CHALLENGES
Transport Energy Water Citizen services Jobs and skills Environment and Sustainability ================================= A Successful City of the Future
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Milton Keynes Near Future
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Digital technologies and data-driven approaches to tackle key challenges for the future of Milton Keynes
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MK Data Platform (Acquisition, Management, Analysis)
Energy Transport Water Education
Data Data Data Data Data
Open Data APIs
Data Data Data Data Data
Data Flow
Open dataPublic Data
Commercial Data
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Open Data Challenges
1. Lack of exper/se in exploi/ng open data; lack of interest in exploi/ng MK-specic local open data
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Open Data Challenges
1. Lack of exper/se in exploi/ng open data; lack of interest in exploi/ng MK-specic local open data
Milton Keynes has > 1000 grass-root community groups with roughly of MK ci/zens being involved in at least one of them.
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Open Data Challenges
1. Lack of exper/se in exploi/ng open data; lack of interest in exploi/ng MK-specic local open data
2. Value lies in mashing up data sets and deep analysis of data, not just raw data
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GeneraAng Value from MulA-Owner Data Mash-ups
Data
Data
Data
Data
Novel service EV Charging Infrastructure
Provider
Residen/al Energy Provider
Electric Vehicle Owner
Energy Distribu/on Company
e.g. Urban Energy Demand Model, Driver Recommenda/on System, Domes/c Energy Management
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Open Data Challenges
1. Lack of exper/se in exploi/ng open data; lack of interest in exploi/ng MK-specic local open data
2. Value lies in mashing up data sets and deep analysis of data, not just raw data
3. Many high-value data sets are proprietary, commercially- sensi/ve or personal.
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Complex Services requires Deep Analysis of Complex Data Types
Building Energy Efficiency/1
WP4 - Energy
Solar Capacity & Potential
WP4 - Energy
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Open Data Challenges
1. Lack of exper/se in exploi/ng open data; lack of interest in exploi/ng MK-specic local open data
2. Value lies in mashing up data sets and deep analysis of data, not just raw data
3. Many high-value data sets are proprietary, commercially sensi/ve or raise privacy issues
4. Growing number of data sets requires automa/on for data cura/on and rights management
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AutomaAc VericaAon of Usage Policies, Sharing Policies, Data Licensing
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Gerd Kortuem | www.kortuem.com | @kortuem | [email protected]
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Prof Gerd Kortuem www.kortuem.com
@kortuem [email protected]