Using Linked Data and the Internet of Things for Energy Management

Digital Enterprise Research Institute www.deri.ie

Using Linked Data and the Internet of
Things for Energy Management
Invited Talk to Galway-Mayo Institute of Technology
13th March 2013

Edward Curry, Green and Sustainable IT

© Copyright 2011 Digital Enterprise Research Institute. All rights
reserved.

Enabling Networked Knowledge

The
Environment
is
on
Everyone’s
Agenda

2

ICT’s
Mass
Produc:on
Carbon
Cost

ICT
Accounts
for

Approximately...

2%

…of
Global
CO2
Emissions.

3

Source
Gartner

McKinsey
2020
Report

ICTs
could
deliver
approximately
7.8
GtCO2
of
emissions
savings
in
2020,
represenFng
a

15%
of
emissions
cut
in
2020
and
600
billion
($946.5
billion)
of
cost
savings.
ICT
can

provide
business
soluFons
that
can
alleviate
at
least
ﬁve
Fmes
the
GHG
footprint
of
ICT

itself

Sustainable
IT

•  Align
all
IT
processes
and

pracFces
with
the
core
Reduce IT
principles
of
sustainability,
2%

which
are
to
reduce,
reuse,

and
recycle;
and

•  Find
innovaFve
ways
to
use

IT
in
business
processes
to
98%

deliver
sustainability

beneﬁts
across
the

enterprise
and
beyond.

5

Improve Efficiency

Analytics Opportunity

n  2010 MIT Sloan / IBM report on Analytics
¨  Embedding business insight into day-to-day operations is
critical to success
¨  Single greatest opportunity and challenge for the data-
driven enterprise

Enabling networked knowledge

Energy
InformaFcs

Energy
+
InformaFon
<
Energy

•  Analyzing,
designing,
and
implemenFng

informaFon
systems
to
increase
energy
eﬃciency

•  Adding
informaFon
to
the
energy
equaFon
to

reduce
energy
consumpFon

R.
T.
Watson,
M.-‐C.
Boudreau,
and
A.
J.
Chen,
InformaFon
Systems
and
Environmentally
Sustainable
Development:

Energy
InformaFcs
and
New
DirecFons
for
the
IS
Community,€
MIS
Quarterly,
vol.
34,
no.
1,
pp.
23-‐38,
2010.

7

Challenge

n  2010 survey of 600+ CIOs & IT Managers
¨  Paucity of sustainability information (i.e energy)
¨  Lost opportunity to leverage information to
improve sustainability
¨  Significant challenges ahead


The
Smart
City
Digital Enterprise Research Institute
www.deri.ie



A
Smart
City
driver
of
change
will
be
Data.



bstr acts
a
A Smart City removes silos moving
towards a connected digital layer.


Silos’ Value Untapped Value

http://www.mckinsey.com/mgi/publications/ig_data/pdfs/MGI_big_data_full_report.pdf

New Engineering Building at
NUI Galway

Cost
-‐
€
40,000,000

14

Research Motivation
A Real-World Example

Cost
-‐
€
40,000,000

AirCon
8:30-‐11:00
&
15:00-‐16:00
Mon
to
Fri

CO2
levels

Occupancy
Pagern

Time Monday Tuesday Wednesday Thursday Friday
ASHRAE

08:00-‐09:00
62.1-‐2010
09:00-‐10:00 237 237 200 237
10:00-‐11:00 237 237 237 200
11:00-‐12:00 237 180 180 145 237
12:00-‐13:00 237 200 237 200 149
13:00-‐14:00 145
14:00-‐15:00 221 237 145 140
15:00-‐16:00 221 120 160 140
16:00-‐17:00 149 250 160
17:00-‐18:00 200 160

15

Enterprise Energy Management

Energy Management Systems within an Enterprise will
need to support four key requirements


Holistic Energy Consumption

FaciliFes

Data
Centre
Business
Travel

Oﬃce
IT
Daily
Commute

Holis:c

Energy

Management


Business Context of
Energy Consumption

Energy

Finance Resource
Allocation

Human
Asset Mgmt Resources


Multi-Level Energy Analysis
CIO
Strategic Analysis CEO
Example KPI:
•  CIO needs high-level Energy used by
business function power global IT department
usage
•  CSO real-time carbon Helpdesk
emissions CSO Example KPI:
PUE of the
Tactical Analysis Data Center in Dublin

•  Manager needs energy
usage of business Maintenance Personnel
processes, business line or
Example KPI:
group kWhs used by
server 172.16.0.8

Operational Analysis
•  Technician needs
equipment power usage Building
•  Low-level monitoring
Sensors, events Data Center

19 of XYZ

Energy Situational
Awareness

n  Help users to:
¨  Understand energy data
¨  Make appropriate energy saving decisions
¨  Support energy performance objectives and
other business performance objectives
–  human resources (i.e. occupancy comfort)
–  enterprise resource planning (i.e. room utilization).


Key Challenges

n  Technology and Data Interoperability
¨  Data scattered among different information systems
¨  Multiple incompatible technologies make it difficult to use

n  Interpreting Dynamic and Static Data
¨  Sensors, ERP, BMS, assets databases, …
¨  Need to proactively identify efficiency opportunities

n  Empowering Actions
¨  Understanding of direct and indirect impacts of activities
¨  Embedding impacts within business processes

21

Interoperability

!
D. Chen, et al. “Architectures for enterprise integration and
interoperability: Past, present and future,” Computers in Industry 59(7)


Barriers

n  Conceptual barriers
¨  Syntactic differences (format)
¨  Semantic (interpretation of meaning)
n  Technological barriers
¨  Incompatibility of protocols, encoding,
platforms, infrastructures, etc.
n  Organizational barriers
¨  Incompatibility of definitions of
responsibility, authority, and
organizational structures


Integration Approaches

n  Integrated approaches
¨  Common format for all models
exists
n  Unified approaches
¨  Uppermodel exists to facilitate
mapping between models
n  Federated approaches
¨  No common format exists but rather
is done on the fly


Emerging Trends

Everything is Connected
and..

…Data is Shared on the
Web with Linked Data

Enabling networked knowledge

Proposed Approach

n  Leverage key trends in
information management
¨  Dataspace approach to
information management
¨  Linked data approach to sharing
information on the web
¨  Internet of Things to
interconnect devices
n  Information Interoperability
¨  Overcome technical and
conceptual barriers
¨  Supports overcoming
organizational barriers !

What is a Dataspace?

n  Emerging data management architecture
n  Recognizes expense obtaining upfront
unifying schema across all sources
¨  Co-existence of data without unifying schema
¨  Loosely integrated set of data sources
n  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.


DBMS vs Dataspace

DBMS Dataspace

Model Relational All

Formats Homogenous Heterogeneous

Control Complete Partial

Query Precise Approximate

Integration Explicit Implicit/
Incremental


The Web of Data


The Linked Open Data cloud

2008
2007 2008 2010
2009
2008 2009
2008

30
30

Linked Open Data cloud
- domains
BestBuy
http://lod-cloud.net/ Overstock.com
Facebook
US government
UK government
Media

User-generated

Government Publications
BBC
New York Times

Cross-domain
Geo
Life sciences

LinkedGeoData
Over 300 open data sets with more than 35 billion facts,
interlinked by 500 million typed links.
Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch.

31

What is Linked Data?

32

Two Key Ingredients

1.  RDF – Resource Description Framework
Graph based Data – nodes and arcs
¨  Identifies objects (URIs)
¨  Interlink information (Relationships)

2.  Vocabularies (Ontologies)
¨  provide shared understanding of a domain
¨  organise knowledge in a machine-comprehensible way
¨  give an exploitable meaning to the data

33 of 46

Why Graphs and Ontologies?

Cities:Dublin
Geo:hasLargestCity
84421km2
Wikipedia.org Geo:IslandOfIreland
Geo:hasCapital
Geo:area
Geo:locatedOn

EU:RepublicOfIreland

EU:RepublicOfIreland
Gov:hasDepartment
Gov:hasTaoiseach
Gov.ie Person:EndaKenny
IE:DepartmentOfFinance


Linked Data Principles

1.  Use URIs to identify the “things” in your data
2.  Use HTTP URIs so people (and machines) can
look them up on the Web
3.  When a URI is looked up, return a
description of the thing in a structured
format (RDF)
4.  Include links to related things to provide
context
http://www.w3.org/DesignIssues/LinkedData.html


Linked Data Example

Resource Description Framework (RDF)
subject - predicate – object
Edward Curry is the Occupant of Room 202e
Edward Curry is the Occupant of Room 202e

http://www.deri.ie/about/team/member/edward_curry/

http://vocab.deri.ie/rooms#occupant

http://lab.linkeddata.deri.ie/2010/deri-rooms#r202e

36

Linked Dataspace

Dataspace + Linked Data = Linked Dataspace

37

Linked Dataspaces

n  Complimentary technology for data sharing
¨  Minimal disruption to existing infrastructure
¨  Maintains loose coupling between systems

n  Pay-as-you-go data integration
¨  Incremental enrichment of entity profiles (i.e. SameAs)
¨  Links relevant knowledge and contextual information from
across all systems


Merging Entity Graphs
the Cloud

Linked Dataspace Corporate System

“Edward Curry” “DGSIT” Corporate
foaf:name
en:memberOf
Building
hJp://www.deri.ie/about/team/
member/edward_curry#me
Office IT

owl:sameAs owl:sameAs

hJp://www.deri.ie/about/team/ hJp://www.deri.ie/about/team/

rm:occupant

en:has_a

hJp://lab.linkeddata.deri.ie/
hJp://energy.deri.ie#macbook15698
2010/deri-‐rooms#r202e

foaf:name
en:consumption
foaf:name
en:consumption

“MacBook Pro” 10kWh “202e” 50kWh

Office IT System Building Management System


Dereferenceable URI
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix owl: <http://www.w3.org/2002/07/owl#> .
@prefix rooms: <http://vocab.deri.ie/rooms#> .
@prefix foaf: <http://xmlns.com/foaf/0.1#> .
@prefix deri-energy-ont: <http://energy.deri.ie/ontology#> .
@prefix deri-energy: <http://energy.deri.ie#> .
@prefix ssn: <http://purl.oclc.org/NET/ssnx/ssn> .
@prefix deri-rooms: <http://lab.linkeddata.deri.ie/2010/deri-rooms#> .

deri-rooms:building rdf:type rooms:Building;
rooms:contains deri-rooms:1st-floor.
deri-rooms:1st-floor rdf:type rooms:Floor;
rooms:contains deri-rooms:1st-floor-south-wing.
deri-rooms:1st-floor-south-wing rdf:type rooms:Wing;
rooms:contains deri-rooms:r202e.
deri-rooms:r202e rdf:type rooms:Desk;
rooms:occupant <http://www.deri.ie/about/team/member/edward_curry#me>.
<http://www.deri.ie/about/team/member/edward_curry#me> rdf:type foaf:Person;
deri-energy-ont:has_a deri-energy:macbook15698;
deri-energy:macbook15698 rdf:type deri-energy-ont:Laptop;
ssn:observedBy deri-energy:sensor123.
deri-energy:sensor123 rdf:type ssn:Sensor;
ssn:observes deri-energy-ont:PowerConsumption.
deri-energy:observation1236 rdf:type ssn:Observation;
ssn:observationResult deri-energy:observationResult1236;
ssn:featureOfInterest deri-energy:macbook15698;
ssn:observedBy deri-energy:sensor123.
deri-energy:observationResult1236 rdf:type ssn:SensorOutput;
ssn:hasValue deri-energy:vale1236.
deri-energy:vale1236 deri-energy-ont:hasQuantityValue 31.5;
deri-energy-ont:hasQuantityUnitOfMeasurement deri-energy-ont:kWh.

40

CoAP = HTTP for sensors


CoAP Applications

42

CoAP Example

n  Accessing sensors from we browser using HTTP-CoAP
proxying – SPITFIRE Smart Service Proxy (SSP)


Energy Intelligence

n  Linked Dataspace for Energy Intelligence
¨  Uses Linked Data and CoAP to manage energy
¨  Transforms raw data into meaningful energy
information
¨  Enables effective strategic, tactical, and operational
decision-making for energy mgmt
¨  Provides energy consumption of business activities
so they can be understood and optimized


Linked dataspace for
Energy Intelligence

Organisation-level
Business Process Personal-level

Linked
dataspace
for

Energy
Intelligence

Office IT Corporate
Building Logistics
Data Center

45

Linked dataspace for
Digital Enterprise Research Institute
Energy Intelligence www.deri.ie

Energy Saving Applications
Applications

n 
Decision Support Energy Analysis
Systems Model
Energy and
Sustainability Dashboards
Situation Awareness
Apps
n  Energy Awareness

Semantic Event Processing
Complex Events
n 
Natural Language Interface
Services
Support

Entity Complex Event
Management
Data
Catalog
Provenance Search &
Query
Processing n 
Service Engine

n  Collaborative Data Mgmt.

n  Interlinked Cloud of Energy
Linked Data

Data

n  Resource Description
Adapter Adapter Adapter Adapter Adapter
Framework (RDF)
Sources

n  Semantic Sensor Network
Ontology (SSN)
n  CoAP = Constrained Application
Protocol


Data Sources

Information System Type Information
Building Information Model ArchiCAD BIM Physical Dimensions of Building

Building Resource Allocation Spreadsheet Assignment of building resources to people
and groups within DERI
Office IT Assets Database SharePoint Office IT equipment assignment

Human Resource Employee SharePoint Person detail, group affiliations and current
Database work assignments
DC Resource Allocation Spreadsheet Assignment of DC resources to services

DC Resource Monitoring Ganglia Real-time monitoring of hardware resources
Monitoring within the data center such as CPU load
System averages or network utilization)
DC Assets Database SharePoint Repository of equipment within Data Centre

Service Management Software Zabbix Real-time monitoring of network services
and hardware
Energy Sensor Network Enistic Sensor Real-time sensor reading from power meters
Platform within building
… … …

CoAP Sensors

48 of 26

Energy Saving Applications

Enterprise Energy Smart Buildings Green Cloud
Observatory Computing

Office IT Energy Mgmt. Personal Energy Mgmt.

Building Energy

1.  Data from
Enterprise
Linked Data
Cloud
2.  Sensor Data
3.  Building
Energy
Situation
Awareness

50 of 26

Linking Building Data

W3C SSN XG Ontology + DERI Rooms + CoAP


iEnergy – Personal


Example of Savings
Achieved


Credits

Team Members The Partners


Selected References

Sustainability Use Cases
n  Curry, E., et al . (2011). An Entity-Centric Approach To Green Information
Systems. 19th European Conference on Information Systems (ECIS 2011).
n  Curry, E., & Donnellan, B. (2012). Green and Sustainable Informatics. In,
Harnessing Green IT: Principles and Practices. John Wiley & Sons
n  Curry, E. et al. An Environmental Chargeback for Data Center and Cloud
Computing Consumers, in First International Workshop on Energy-Efficient
Data Centers, 2012.
n  Curry, E. et al, Building Optimisation using Scenario Modeling and Linked
Data, in 1st Workshop Linked Data in Architecture and Construction 2012
n  Curry E. et al, Enterprise Energy Management using a Linked dataspace for
Energy Intelligence. In: The Second IFIP Conference on Sustainable Internet
and ICT for Sustainability (SustainIT) 2012.


Selected References

Information Management
n  Hasan, S. et al. (2011). Toward Situation Awareness for the Semantic
Sensor Web: Complex Event Processing with Dynamic Linked Data
Enrichment. 4th International Workshop on Semantic Sensor Networks
n  Hasan, S. et al, Approximate Semantic Matching of Heterogeneous Events,
in 6th ACM International Conference on Distributed Event-Based Systems
n  Curry E. (2012) System of Systems Information Interoperability using a
Linked Dataspace In: IEEE 7th International Conference on System of
Systems Engineering (SOSE 2012).
IT Management
n  Curry, E. et al. Developing an Sustainable IT Capability: Lessons From
Intel’s Journey, MIS Quarterly Executive, vol. 11, no. 2, pp. 61-74, 2012.
n  Donnellan B. et al, (2011) A Capability Maturity Framework for Sustainable
Information and Communication Technology. IEEE IT Professional 13(1).
n  Curry E, et al, (2012) Sustainable IT: Challenges, Postures, and Outcomes,
IEEE Computer 15(11)


Using Linked Data and the Internet of Things for Energy Management

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