@WATERNOMICS_EU www.waternomics.eu
Project co-funded by the European
Commission within the 7th Framework
Program (Grant Agreement No. 619660)
LINKED WATER DATA FOR WATER
INFORMATION MANAGEMENT
E. Curry, V. Degeler, E. Clifford, D. Coakley, A. Costa, T. Messervey, S.-J.
Van Andel, N. Van de Giesen, C. Kouroupetroglou, J. Mink, and S. Smit
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu2
WATER DECISION SUPPORT
• Present meaningful information
• Personalized Services
• User Awareness (usage)
• User Incentivisation (Price)
• Benchmarking
– Neighborhood
– Industry Sector
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu3
WATER FOOTPRINTS
•  Business transparency
driving assessments of
water impact
•  Water footprints
consider all sources of
water consumption (direct/
indirect)
•  No single data source
•  Requires integrated data
from many participants in
supply chain
– Weather data, geo-location
data, historical records,
product usage data, user
behaviour habits, etc
http://www.waterfootprint.org/
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu4
Technology and Data Interoperability
•  Data produced in different organizations
•  Data scattered among different
information systems Dynamic data, sensors,
ERP, BMS, assets databases, …
•  Multiple incompatible technologies make
it difficult to use
•  Significant cost to bring this data together
How do we breakdown these
Water Data Silos?
KEY DATA CHALLENGES
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu5
• Emerging data management techniques
recognize expense obtaining upfront
unifying schema across all data sources
Key Emerging Principles
– Co-existence of data without unifying schema
– Loosely integrated set of data sources
– Data integrated on “as needed” basis
– Tighter integration achieved in an incremental
"pay-as-you-go" fashion
Franklin, A. Halevy, and D. Maier From databases to dataspaces: a new
abstraction for information management,” Sigmod Record, 34(4) 2005.
A DIFFERENT APPROACH IS NEEDED
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu6
DBMS VS DATASPACE
DBMS Dataspace/
Linked Data
Model Relational All
Formats Homogenous Heterogeneous
Control Complete Partial
Query Precise Approximate
Integration Explicit Implicit/
Incremental
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu7
THE LINKED OPEN DATA CLOUD
7
20082007
2008
2008
2008
2009
20092010
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu8
LINKED OPEN DATA CLOUD - DOMAINS
Over 300 open data sets with more than 35 billion facts,
interlinked by 500 million typed links.
http://lod-cloud.net/
Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch.
Media
Government
Geo
Publications
User-generated
Life sciences
Cross-domain
US government
UK government
BBC

New York Times
LinkedGeoData
BestBuy
Overstock.com
Facebook
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu9
•  Linked Data is a method of exposing, sharing, and
connecting data (via de-referenceable URIs) on the Web.
–  Provides a Data (RDF) and Naming (URI) model for the Web
–  W3C Web-based Standards
–  Adaptive Ontologies
–  Incremental Approach
•  Resource Description Framework (RDF)
–  Graph based Data – nodes and arcs
–  Identifies objects (URIs)
–  Interlink information (Relationships)
•  Vocabularies (Ontologies)
–  Provides shared understanding of a domain
–  Organizes knowledge in a machine-comprehensible way
–  Gives an exploitable meaning to the data
LINKED DATA
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu10
LINKED DATA PRINCIPLES
1. Naming: Use URIs to identify the “things”
in your data
2. Access: Use HTTP URIs so people (and
machines) can look them up on the Web
3. Format: When a URI is looked up, return a
description of the thing in a structured
format (RDF)
4. Contextualization: Include links to related
things to provide context (data network)
http://www.w3.org/DesignIssues/LinkedData.html
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu11
rm:contains
foaf:name
water:consumptionfoaf:name
water:consumption
water:consumptionfoaf:name
rm:contains
“Main Kitchen” 83 L/d
40 L/d“Dishwasher” 16.5 L/d“Mr. Coffee”
http://lab.linkeddata.deri.ie/
2010/deri-rooms#r315
http://water.deri.ie#mr-coffeehttp://water.deri.ie#dishwasher23
energy:consumption
50 kWh
LINKED WATER DATA
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu12
•  To introduce demand response and accountability principles
(water footprint) in the water sector
•  To engage consumers in new interactive and personalized ways that
bring water efficiency to the forefront and leads to changes in water
behaviours
•  To empower corporate decision makers and municipal area managers
with a water information platform together with relevant tools and
methodologies to enact ICT-enabled water management programs
•  To promote ICT enabled water awareness using airports and water
utilities as pilot examples
•  To make possible new water pricing options and policy actions by
combining water availability and consumption data
WATERNOMICS will provide personalised and actionable
information on water consumption and water availability to
individual households, companies and cities in an intuitive &
effective manner at relevant time-scales for decision making
WATERNOMICS
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu13
KEY TECHNOLOGY
Open/Linked	
  Data	
   Internet	
  of	
  Things	
  
Gamifica:on	
  
Simple	
  UI	
  
Seman:cs	
   Leak	
  Detec:on	
  
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu14
WATERNOMICS
APPROACH
Internet of Things
• Sensors connected to the Internet
• Real-time water awareness
• Semanitc Event Processing
Linked Water Data
• Linkage of contextual information
• Inclusion of W3C Standards
• Water data as Open Data on Web
Water Information Services
• Visual Dashboards
• Decision support systems
• Games & interactive learning apps
Water Analysis Services
• Water Usage Prediction Models
• Meteorological Drought Forecasting
• Leak & Fault Detection
IoT
Water Management Systems
• Auditing procedures
• Sensor network design rules
• Organizational procedures
WATERNOMICS will be demonstrated in three high
impact pilots that target three different end users/
stakeholders.
PILOTS
Domestic Usage
Municipality of Thermi, Greece
Corporate Usage
Linate Airport, Milan, Italy
Mixed Use
Galway City, Ireland
Homes (single residence,
apartments and complexes) in
a water stressed region
Installing a water management
system in the main terminal of
a signature EU airport
Decision making tools and
support to public buildings and
public assets
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu1515	
  	
  
Water
Analysis
Model
Usage
Model
Water
Dashboards
Decision
Support
Services
Corporate
Municipality Public
Waternomics	
  
Informa/on	
  Pla2orms	
  
GENERIC WATER INFORMATION SERVICES
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu16
Water Management Apps
•  Water dashboards
•  Decision support
•  Availability forecast
Support Services
•  Simplify linked data
consumption via services
Linked Water Data Cloud
•  Rich with knowledge and
semantics about water
usage performance
Data/Meter Sources
•  Existing operational
legacy systems
•  Adapters perform the
“RDFization” lift to the
dataspace
WATERNOMICS INFORMATION PLATFORM
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu17
ssn:Sensor
rm:Room
En:Sink
En:Dishwasher
ssn:observes
En:Water
Consumption
foaf:Person
foar:Group
foaf:memberOf
rm:Roomrm:Desk foaf:Person
rm:occupantrm:contains
rm:Building
rm:Floor
rm:contains
rm:contains
owl:sameAs
owl:sameAs
Human Resource
Building
Management
System
Sensor Network
CROSS-DOMAIN WATER DATA
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu18
TOWARDS LINKED WATER SERVICES
Water Analysis
Models
Water Consumption
Forecasting
Water Awareness
Dashboards
Water
Footprint
s
Dynamic Pricing
Decision
Support
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York
@WATERNOMICS_EU www.waternomics.eu19
SUMMARY AND FUTURE WORK
• Emerging data management
approaches recognize expense
obtaining upfront unifying
schema across all sources
• Linked Data is a method of
publishing, sharing, and
connecting data on the Web
• Waternomics will explore
Linked Water Data
– Project kicked-off in February 2014
– Linked Water Dataspace
development is underway
E. Curry, et. al “Linked Water Data For Water
Information Management,” in HIC 2014, New York

Linked Water Data For Water Information Management

  • 1.
    @WATERNOMICS_EU www.waternomics.eu Project co-fundedby the European Commission within the 7th Framework Program (Grant Agreement No. 619660) LINKED WATER DATA FOR WATER INFORMATION MANAGEMENT E. Curry, V. Degeler, E. Clifford, D. Coakley, A. Costa, T. Messervey, S.-J. Van Andel, N. Van de Giesen, C. Kouroupetroglou, J. Mink, and S. Smit E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 2.
    @WATERNOMICS_EU www.waternomics.eu2 WATER DECISIONSUPPORT • Present meaningful information • Personalized Services • User Awareness (usage) • User Incentivisation (Price) • Benchmarking – Neighborhood – Industry Sector E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 3.
    @WATERNOMICS_EU www.waternomics.eu3 WATER FOOTPRINTS • Business transparency driving assessments of water impact •  Water footprints consider all sources of water consumption (direct/ indirect) •  No single data source •  Requires integrated data from many participants in supply chain – Weather data, geo-location data, historical records, product usage data, user behaviour habits, etc http://www.waterfootprint.org/ E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 4.
    @WATERNOMICS_EU www.waternomics.eu4 Technology andData Interoperability •  Data produced in different organizations •  Data scattered among different information systems Dynamic data, sensors, ERP, BMS, assets databases, … •  Multiple incompatible technologies make it difficult to use •  Significant cost to bring this data together How do we breakdown these Water Data Silos? KEY DATA CHALLENGES E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 5.
    @WATERNOMICS_EU www.waternomics.eu5 • Emerging datamanagement techniques recognize expense obtaining upfront unifying schema across all data sources Key Emerging Principles – Co-existence of data without unifying schema – Loosely integrated set of data sources – Data integrated on “as needed” basis – Tighter integration achieved in an incremental "pay-as-you-go" fashion Franklin, A. Halevy, and D. Maier From databases to dataspaces: a new abstraction for information management,” Sigmod Record, 34(4) 2005. A DIFFERENT APPROACH IS NEEDED E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 6.
    @WATERNOMICS_EU www.waternomics.eu6 DBMS VSDATASPACE DBMS Dataspace/ Linked Data Model Relational All Formats Homogenous Heterogeneous Control Complete Partial Query Precise Approximate Integration Explicit Implicit/ Incremental E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 7.
    @WATERNOMICS_EU www.waternomics.eu7 THE LINKEDOPEN DATA CLOUD 7 20082007 2008 2008 2008 2009 20092010 E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 8.
    @WATERNOMICS_EU www.waternomics.eu8 LINKED OPENDATA CLOUD - DOMAINS Over 300 open data sets with more than 35 billion facts, interlinked by 500 million typed links. http://lod-cloud.net/ Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. Media Government Geo Publications User-generated Life sciences Cross-domain US government UK government BBC
 New York Times LinkedGeoData BestBuy Overstock.com Facebook E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 9.
    @WATERNOMICS_EU www.waternomics.eu9 •  LinkedData is a method of exposing, sharing, and connecting data (via de-referenceable URIs) on the Web. –  Provides a Data (RDF) and Naming (URI) model for the Web –  W3C Web-based Standards –  Adaptive Ontologies –  Incremental Approach •  Resource Description Framework (RDF) –  Graph based Data – nodes and arcs –  Identifies objects (URIs) –  Interlink information (Relationships) •  Vocabularies (Ontologies) –  Provides shared understanding of a domain –  Organizes knowledge in a machine-comprehensible way –  Gives an exploitable meaning to the data LINKED DATA E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 10.
    @WATERNOMICS_EU www.waternomics.eu10 LINKED DATAPRINCIPLES 1. Naming: Use URIs to identify the “things” in your data 2. Access: Use HTTP URIs so people (and machines) can look them up on the Web 3. Format: When a URI is looked up, return a description of the thing in a structured format (RDF) 4. Contextualization: Include links to related things to provide context (data network) http://www.w3.org/DesignIssues/LinkedData.html E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 11.
    @WATERNOMICS_EU www.waternomics.eu11 rm:contains foaf:name water:consumptionfoaf:name water:consumption water:consumptionfoaf:name rm:contains “Main Kitchen”83 L/d 40 L/d“Dishwasher” 16.5 L/d“Mr. Coffee” http://lab.linkeddata.deri.ie/ 2010/deri-rooms#r315 http://water.deri.ie#mr-coffeehttp://water.deri.ie#dishwasher23 energy:consumption 50 kWh LINKED WATER DATA E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 12.
    @WATERNOMICS_EU www.waternomics.eu12 •  Tointroduce demand response and accountability principles (water footprint) in the water sector •  To engage consumers in new interactive and personalized ways that bring water efficiency to the forefront and leads to changes in water behaviours •  To empower corporate decision makers and municipal area managers with a water information platform together with relevant tools and methodologies to enact ICT-enabled water management programs •  To promote ICT enabled water awareness using airports and water utilities as pilot examples •  To make possible new water pricing options and policy actions by combining water availability and consumption data WATERNOMICS will provide personalised and actionable information on water consumption and water availability to individual households, companies and cities in an intuitive & effective manner at relevant time-scales for decision making WATERNOMICS E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 13.
    @WATERNOMICS_EU www.waternomics.eu13 KEY TECHNOLOGY Open/Linked  Data   Internet  of  Things   Gamifica:on   Simple  UI   Seman:cs   Leak  Detec:on   E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 14.
    @WATERNOMICS_EU www.waternomics.eu14 WATERNOMICS APPROACH Internet ofThings • Sensors connected to the Internet • Real-time water awareness • Semanitc Event Processing Linked Water Data • Linkage of contextual information • Inclusion of W3C Standards • Water data as Open Data on Web Water Information Services • Visual Dashboards • Decision support systems • Games & interactive learning apps Water Analysis Services • Water Usage Prediction Models • Meteorological Drought Forecasting • Leak & Fault Detection IoT Water Management Systems • Auditing procedures • Sensor network design rules • Organizational procedures WATERNOMICS will be demonstrated in three high impact pilots that target three different end users/ stakeholders. PILOTS Domestic Usage Municipality of Thermi, Greece Corporate Usage Linate Airport, Milan, Italy Mixed Use Galway City, Ireland Homes (single residence, apartments and complexes) in a water stressed region Installing a water management system in the main terminal of a signature EU airport Decision making tools and support to public buildings and public assets E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 15.
    @WATERNOMICS_EU www.waternomics.eu1515     Water Analysis Model Usage Model Water Dashboards Decision Support Services Corporate Municipality Public Waternomics   Informa/on  Pla2orms   GENERIC WATER INFORMATION SERVICES E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 16.
    @WATERNOMICS_EU www.waternomics.eu16 Water ManagementApps •  Water dashboards •  Decision support •  Availability forecast Support Services •  Simplify linked data consumption via services Linked Water Data Cloud •  Rich with knowledge and semantics about water usage performance Data/Meter Sources •  Existing operational legacy systems •  Adapters perform the “RDFization” lift to the dataspace WATERNOMICS INFORMATION PLATFORM E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 17.
  • 18.
    @WATERNOMICS_EU www.waternomics.eu18 TOWARDS LINKEDWATER SERVICES Water Analysis Models Water Consumption Forecasting Water Awareness Dashboards Water Footprint s Dynamic Pricing Decision Support E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York
  • 19.
    @WATERNOMICS_EU www.waternomics.eu19 SUMMARY ANDFUTURE WORK • Emerging data management approaches recognize expense obtaining upfront unifying schema across all sources • Linked Data is a method of publishing, sharing, and connecting data on the Web • Waternomics will explore Linked Water Data – Project kicked-off in February 2014 – Linked Water Dataspace development is underway E. Curry, et. al “Linked Water Data For Water Information Management,” in HIC 2014, New York