1. Digital Enterprise Research Institute www.deri.ie
Linking the Real World
Manfred Hauswirth
Copyright 2011 Digital Enterprise Research Institute. All rights reserved.
Enabling networked knowledge
3. DERI’s Mission
Digital Enterprise Research Institute www.deri.ie
Enabling & exploiting
Networked Knowledge
Enabling networked knowledge
4. About DERI
Digital Enterprise Research Institute www.deri.ie
Founded June 2003 as a CSET (Centre for Science,
Engineering and Technology).
Link scientists and engineers / academia and industry
Fundamental research
Development of Irish-based technology companies
Attract industry
Education & outreach
DERI Institute
CSET
Commercialization, DAI
EU, EI, direct industry, IRCSET
DERI strategic plan responds to priorities
Local: University focus on Informatics, Physical &
Computational Sciences
National: SMART Economy, Program for Government
International: EU Digital Agenda
Enabling networked knowledge
5. About DERI
Digital Enterprise Research Institute www.deri.ie
Number one in our core space
Research Publications > 1000
Participation in 17 standardisation groups (W3C, OASIS)
Approx. 140 members from 30 nations
57 PhDs /Masters
42 completed PhDs/Masters
Core Industrial Partners:
MNC’s: Cisco, Avaya, Bel-Labs, Ericsson…
SME’s: Storm, Celtrak, OpenLink……
Research: FBK
Total Research Grants: > €60 million
SFI, EU Framework, Enterprise Ireland, Industry
Currently 18 EU project running
Industry funded projects with Fujitsu Labs Japan, Cisco,
Google, Renault, EADS, Fidelity,…
Enabling networked knowledge
7. DERI Innovation Approach
Digital Enterprise Research Institute www.deri.ie
• Seevl
• Sindice.com
Spin Outs • Peracton
• Atom
• PEPPR
• IVEA Commerci-
alisation • Joint projects
• Patents and
Industry Licensing
• DERI Applied
Research Collaboration Innovation
Excellence
• W3C
• OASIS
• SIOC
• VOID, DCAT
• schema.org
• OData Standards • Drupal 7
Open • Semantic Desktop
• SIREn
Source
Prototypes
Enabling networked knowledge
8. The DERI House
Digital Enterprise Research Institute www.deri.ie
DERI Applied
Research Commercialisation
eBusiness Green &
eLearning
Financial Services Sustainable IT
Health Care Cyber
Data eGovernment
Life Sciences Security Linked
Cloud Analy
Data
tics
Information Security,
Cloud Data Sensor
Social Software Mining Privacy
Management Middleware
and Retrieval & Trust
Data Natural Service
Reasoning and Knowledge
Visualisation Language Oriented
Querying Discovery
and Interaction Processing Architecture
DERI is designed to provide an integrated solution
Enabling networked knowledge
10. A Network of Knowledge
Digital Enterprise Research Institute www.deri.ie
Interconnected
Universal
All encompassing
Assists humans,
organizations and systems in
problem solving
Enable global and local
collaboration
Enabling networked knowledge
11. A Network of Knowledge
Digital Enterprise Research Institute www.deri.ie
Interconnected
Universal
All encompassing
•Application
• Search Research Domains
• Collaboration • Commercialization
• Information Mining
• Middleware
Linked Data
assists humans,
organizations and systems
with problem solving
enabling innovation and
increased productivity
Enabling networked knowledge
12. Two Key Ingredients
Digital Enterprise Research Institute www.deri.ie
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
Enabling networked knowledge
12 of 46
13. Why Graphs and Ontologies?
Digital Enterprise Research Institute www.deri.ie
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
Enabling networked knowledge
14. Linked Open Data Cloud
Digital Enterprise Research Institute www.deri.ie
2008
2007 2008 2010
2009
2008 2009
2008
Enabling networked knowledge
14
14
15. Linked Data Domains
Digital Enterprise Research Institute www.deri.ie
BestBuy
http://lod-cloud.net/ Overstock.com
Facebook
Powered US government
UK government
by DERI! Media
User-generated
Government Publications
BBC
New York Times
Cross-domain
Geo
Life sciences
LinkedGeoData
Over 200 open data sets with more than 25 billion facts,
interlinked by 400 million typed links, doubling every 10 month!
Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch.
Enabling networked knowledge
15
16. Challenges of Big Data
Digital Enterprise Research Institute www.deri.ie
“90% of the data in the world today
has been created in the last two
years alone” – IBM
The bringing together of a vast
amount of data from public and
private sources […] is what Big Data is
all about,” – IDC
Enabling networked knowledge
17. How to exploit Big Data?
Digital Enterprise Research Institute www.deri.ie
Solutions required for
Management and Integration
Abstraction and Reasoning
Analytics and Visualization
Interaction and Collaboration
Domain Knowledge
and
Integration into a coherent
Framework!
Enabling networked knowledge
18. Knowledge Dashboard
Digital Enterprise Research Institute www.deri.ie
Analytics
Visualisation
Abstraction
Reasoning
Networked
Data
Enabling networked knowledge
19. What is a Smart City?
Digital Enterprise Research Institute www.deri.ie
Invests in
human and social capital
traditional/modern infrastructure
that
fuels sustainable economic development
and high quality of life
while
managing natural resources
through
participatory governance
Enabling networked knowledge
http://ideas.repec.org/p/dgr/vuarem/2009-48.html
20. Digital Enterprise Research Institute www.deri.ie
A Smart City removes silos moving
towards a connected digital layer.
Enabling networked knowledge
21. Silos’ Value Untapped Value
Digital Enterprise Research Institute www.deri.ie
Enabling networked knowledge
http://www.mckinsey.com/mgi/publications/ig_data/pdfs/MGI_big_data_full_report.pdf
22. Digital Enterprise Research Institute www.deri.ie
A Smart City driver of change will be Data.
Enabling networked knowledge
25. Goal
Digital Enterprise Research Institute www.deri.ie
Streams are just yet another
form/source of linked data
Semantic description of sensors, streams,
events, observations, etc.
“Senso ergo sum” – semantic descriptions
down to the sensor level
Web protocols down to the sensor level
SPARQL-like access to streams and sensors
Infrastructure framework
Enabling networked knowledge
26. Keep it simple, Stupid!
Digital Enterprise Research Institute www.deri.ie
Application := Data + Services
Application
LOD REST
Enabling networked knowledge
27. KISS revisited
Digital Enterprise Research Institute www.deri.ie
Application
CQELS REST SPARQL
Linked Streams Linked Data
Virtual COAP
Sensors Sensors
Enabling networked knowledge
29. Digital Enterprise Research Institute www.deri.ie
Sensors, streams,
events, observations
Enabling networked knowledge
30. W3C SSN XG
Digital Enterprise Research Institute www.deri.ie
Semantic Sensor Networks ontology to describe sensors
and sensor data
Semantic annotations for OGC’s SWE Sensor Model
Language
Motivations
No existing sensor ontology included all the basic concepts
Ease integration of (some) semantics in more spread languages
and standards (specifically SensorML)
Enabling networked knowledge
31. Relation to existing
standards
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Enabling networked knowledge
40. CoAP = HTTP for sensors
Digital Enterprise Research Institute www.deri.ie
Enabling networked knowledge
41. CoAP Example
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Accessing sensors from we browser using HTTP-CoAP
proxying – SPITFIRE Smart Service Proxy (SSP)
Enabling networked knowledge
42. Digital Enterprise Research Institute www.deri.ie
OK, we can access
sensors via RESTful
interfaces now
Enabling networked knowledge
43. KISS revisited
Digital Enterprise Research Institute www.deri.ie
Application
CQELS REST SPARQL
Linked Streams Linked Data
Virtual COAP
Sensors Sensors
Enabling networked knowledge
44. CQELS
Digital Enterprise Research Institute www.deri.ie
Continuous Query Evaluation over
Linked Streams
Scalable processing model for unified
Linked Stream Data and Linked Open
Data
Combines data pre-processing and an
adaptive cost-based query
optimization algorithm
Experimental evaluation shows great
performance (w.r.t. response time
and scalability)
Enabling networked knowledge
45. Black Box Approach
Digital Enterprise Research Institute www.deri.ie
Query
Query rewriter
Optimizer
SPARQL-like
Operator implementations Orchestrator
Overhead
Executor
Data transformation
Execution
Access methods
Enabling networked knowledge
46. EP-SPARQL and C-SPARQL
Digital Enterprise Research Institute www.deri.ie
CSPARQL to SPARQL
EP-SPARQL to Prolog Query Rewriter
SPARQL
Query Rewriter Engine
Data
transformation
EP-SPARQL
C-SPARQL
Orchestrator
Orchestrator
RDF to Java objects
Prolog Engine Data
transformation
RDF to prolog facts
ESPER
Data
transformation
Query Rewriter
EP-SPARQL
CSPARQL to EPSER EPL
C-SPARQL
Enabling networked knowledge
47. White Box Approach
Digital Enterprise Research Institute www.deri.ie
Query
Adaptive Optimizer
Operator implementations
Adaptive Executor
Adaptive Execution
Native Access methods
RDF Linked
dataset datastream
Enabling networked knowledge
48. Enabling adaptivity
Digital Enterprise Research Institute www.deri.ie
Incoming data will continuously change the costs of query plans
➥ Data elements are adaptively routed to processing operators on
equivalent data flows (routing policies)
Enabling networked knowledge
50. Processing Model:
Operators
Digital Enterprise Research Institute www.deri.ie
Triple-based window operators extracts triples
from RDF stream or dataset that
match a given triple pattern
are valid within in a time window
Relational operators enable employing relational
algebras in the processing model
Streaming operators generate new streams from
output of other operators based on graph
templates
Enabling networked knowledge
51. Continuous Query Evaluation over
Linked Streams (CQELS)
Digital Enterprise Research Institute www.deri.ie
Query CQELS language (an extension of SPARQL 1.1)
Caching and Indexing
Adaptive Optimizer
Operator implementations
Adaptive Executor
Adaptive Execution
SPO index scheme
Dictionary
Ring Triple-based
Dynamic Routing Policy Native Access methods indices for
windows
RDF Linked
dataset datastream
Enabling networked knowledge
52. Techniques
Digital Enterprise Research Institute www.deri.ie
Dictionary encoding
Smaller memory for representing triples
Avoid lookup & decoding overhead for numeric RDF nodes
Caching and Indexing
Caching: avoid re-computing of intermediate results of sub-
queries over non-stream data.
Indexing: facilitate faster access on caches and window data.
Dynamic Routing Policy
Incoming data can be evaluated in multiple equivalent data
flows adaptive to changes
Easy & flexible support to implement routing policies
Enabling networked knowledge
53. CQELS query language
Digital Enterprise Research Institute www.deri.ie
CQELS Language – an extension to SPARQL 1.1
Construct new RDF stream Stream pattern
Enabling networked knowledge
54. Experimental setup
Digital Enterprise Research Institute www.deri.ie
Conference scenario: combine linked stream from RFID tags
(physical relationships) with DBLP data (social relationships)
Setup
Systems: CQELS vs ETALIS and C-SPARQL
Datasets
– Replayed RFID data from Open Beacon deployments
– Simulated DBLP by SP2Bench
Queries: 5 query templates with different complexities
– Q1: selection,
– Q2: stream joins, Q3,Q4: Stream and non-stream joins
– Q5: aggregation
Experiments
– Single query: generate 10 query instances of each template by varying the constants
– Vary size of DBLP dataset (104-107triples)
– Multiple queries: register 2M parallel instances (0≤M≤10)
Enabling networked knowledge
55. Experiment results - Query
execution time
Digital Enterprise Research Institute www.deri.ie
CQELS performs faster by orders of magnitude
Query 1 Query 2 Query 3 Query 4 Query5
CQELS 0.47 3.90 0.51 0.53 21.83
C-SPARQL 332.46 99.84 331.68 395.18 322.64
ETALIS 0.06 27.47 79.95 469.23 160.83
Aggregation:
Simple selection: ETALIS performs best 15 times faster than C-SPARQL
Stream join: Stream and non-stream joins:
8 times faster than ETALIS
25 times faster than C-SPARQL
>600 times faster than C-SPARQL
8 times faster than ETALIS 150-850 times faster than ETALIS
Enabling networked knowledge
56. Scalability: Static data size
Digital Enterprise Research Institute www.deri.ie
Enabling networked knowledge
57. Scalability: # of queries
Digital Enterprise Research Institute www.deri.ie
Enabling networked knowledge
58. Next steps
Digital Enterprise Research Institute www.deri.ie
Optimization
Adaptive cost-based query optimization
Inter-query optimization
Smart and dynamic caching
Adaptive caching
Materialized view maintenance for dynamic data
Scalability: clusters and cloud
Enabling networked knowledge
59. Digital Enterprise Research Institute www.deri.ie
OK, now we can also
process Linked
Streams and integrate
Linked Data efficiently
Enabling networked knowledge
60. KISS revisited
Digital Enterprise Research Institute www.deri.ie
Application
CQELS REST SPARQL
Linked Streams Linked Data
Virtual COAP
Sensors Sensors
Enabling networked knowledge
61. RDF-on-the-go
http://rdfonthego.googlecode.com/
Digital Enterprise Research Institute www.deri.ie
A single, integrated mobile phone data store for all
applications
Intrinsically integrated with the Web (Linked Data)
Enabling networked knowledge
62. RDF-on-the-go
http://rdfonthego.googlecode.com/
Digital Enterprise Research Institute www.deri.ie
Enabling networked knowledge
63. Business Card Demo
Digital Enterprise Research Institute www.deri.ie
URI to FOAF file
Enabling networked knowledge
64. Digital Enterprise Research Institute www.deri.ie
OK, we can do all
that on mobile
phones too
Enabling networked knowledge
65. KISS revisited
Digital Enterprise Research Institute www.deri.ie
Application
CQELS REST SPARQL
Linked Streams Linked Data
Virtual COAP
Sensors Sensors
Enabling networked knowledge
66. Global Sensor Networks
Digital Enterprise Research Institute www.deri.ie
Decrease the cost and complexity of sensor
network deployment
Abstraction level
Heterogeneous platforms Abstract from data
producers
Heterogeneous data Data level
Semantic description of
sensors and sensor data
No common abstractions Data integration
Large scale
Very large scale Distributed query
processing and reasoning
Enabling networked knowledge
67. Where are we now?
Digital Enterprise Research Institute www.deri.ie
Global Sensor Networks
http://gsn.sourceforge.net/
WS
• Uniform, declarative abstractions
• Simple semantic descriptions
SOA • Supports all major platforms
• Fast and simple deployment
• Plug & play
GSN
• Zero-programming
• Efficient query processing
Enabling networked knowledge
68. GSN’s view of the world
Digital Enterprise Research Institute www.deri.ie
Sensor network +
base computer =
sensor node
Many sensor nodes
produce a lot of data on
the Internet
Questions:
Deployment
Description
Discovery
Integration
Distributed processing
Enabling networked knowledge
69. Central abstraction:
Virtual sensors
Digital Enterprise Research Institute www.deri.ie
A virtual sensor can be any kind of data producer
a real sensor, a wireless camera, a mobile phone, etc.
N input streams 1 (structured) output stream
processing
a combination of other local or
remote virtual sensors
Specification
simple semantic descriptions of sensors and data streams
declarative SQL-based specification of the data stream processing
functional properties related to stream quality management, etc.
Enabling networked knowledge
70. Virtual sensor definition:
XML + SQL Structure / data type
Digital Enterprise Research Institute
Meta-data of output stream www.deri.ie
<virtual-sensor name="room-monitor" priority="11"> <query>
<addressing> select AVG(temp1) as T1 from WRAPPER
<predicate key="geographical">BC143</predicate> </query>
<predicate key="usage">room monitoring</predicate> </stream-source>
</addressing> <stream-source alias="temperature2“
<life-cycle pool-size="10" /> storage-size="1m"
<storage permanent="true" history-size="10h" /> disconnect-buffer-size="10">
<output-structure> <address wrapper="remote">
<field name="image" type="binary:jpeg" /> Input stream 2:
<predicate key="type">
<field name="temp" type="int" /> System resources temperature
Temperature
</output-structure> </predicate>
<input-streams> to assign <predicate key="geographical">
<input-stream name="cam"> BC143-S Query over input
<stream-source alias="cam" storage-size="1"
disconnect-buffer-size="10">
</predicate>
</address>
streams to produce
<address wrapper="remote"> <query> output stream of
<predicate key="geographical">BC143</predicate> select AVG(temp2) as T2
<predicate key="type">Camera</predicate> from WRAPPER the Virtual Sensor
</address> </query>
<query>select * from WRAPPER</query> </stream-source>
</stream-source> <query>
<stream-source alias="temperature1“ select cam.picture as image, temperature.T1
storage-size="1m" as temp
disconnect-buffer-size="10"> from cam, temperature1
<address wrapper="remote"> where temperature1.T1 > 30 AND
<predicate key="type">temperature</predicate> temperature1.T1 = temperature2.T2
<predicate key="geographical">
BC143-N Input stream 1:
</query>
</input-stream>
Input stream 3:
</predicate>
</address> Camera images
</input-streams>
</virtual-sensor>
Temperature
70 of 58
Enabling networked knowledge
71. Accessing sensors:
Wrappers
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HTTP Generic Wrapper Generic UDP Wrapper
HTTP GET or POST requests UDP connections
Serial Forwarder Wrapper Generic Serial Wrapper
Local RS-232 connections
TinyOS compatible motes
TI-RFID Wrapper
USB Camera Wrapper
Texas Instruments Series
Local USB connection 6000 S6700 multi-protocol
RFID readers
Bluetooth Wrapper
MAC and RFCOMM Bluetooth Generic RSS/XML Wrapper
GPSD Wrapper
COAP Wrapper
More than 60 NMEA-compliant GPS devices
RESTful interface to sensors
Contiki, Coalesenses
Enabling networked knowledge
72. Coding efforts
Digital Enterprise Research Institute www.deri.ie
Wrapper type Lines of code
TinyOS 120
WiseNode 75
Generic UDP 45
Generic serial 180
Wired camera 300
Wireless camera (HTTP) 60
RFID reader (TI) 50
Enabling networked knowledge
73. Selected Features
Digital Enterprise Research Institute www.deri.ie
Workflow Editor
- Web-based design of
Virtual Sensors
SafeStorage
- Safe data backups
Enabling networked knowledge
74. Plug and Play: Zero
Programming
Digital Enterprise Research Institute www.deri.ie
An IEEE 1451-compliant sensor provides a Transducer
Electronic Data Sheet (TEDS) which is stored inside the sensor
TEDS provides a simple semantic description of the sensor
the sensor's properties and measurement characteristic
GSN uses the TEDS self-description feature for dynamic
generation and deployment of virtual sensor descriptions
Next step: store queries not only data in TEDS or RFID tags
New level of data processing in terms of flexibility
Enabling networked knowledge
76. Experimental setup
Digital Enterprise Research Institute www.deri.ie
5 desktop PCs
Pentium 4, 3.2GHz with 1MB
cache, 1GB memory, 100Mbit
Ethernet, Debian 3.1
Linux kernel 2.4.27, MySQL
5.18
SN-1: 10 Mica2 motes with light and
temperature sensors, packet size 15
Bytes, TinyOS
SN-2: 8 Mica2 motes with light,
temperature, acceleration, and
sound sensors, packet size 100
Bytes, TinyOS
SN-3: 4 Shockfish Tiny-Nodes with a
light and two temperature sensors
packet size 29 Bytes, TinyOS
SN-4: 15 wireless 8002.11b cameras
(AXIS 206W), 640x480 JPEG, 5 with
16kB average image size, 5 with
32kB, 5 with 75kB
SN-5: TI Series 6000 S6700 multi-
protocol RFID reader with three
different kind of tags (up to 8KB of
data)
Enabling networked knowledge
77. Experimental setup
Digital Enterprise Research Institute www.deri.ie
2 1.8 GHz Centrino laptops with
1GB memory as observers
Each ran up to 250 lightweight
GSN instances.
Each instance produced random
queries with varying table names,
varying filtering condition
complexity, and varying
configuration parameters
3 filtering predicates in the
WHERE clause on average, using
random history sizes from 1
second up to 30 minutes and
uniformly distributed random
sampling rates (seconds) [0.01, 1]
Motes produce random bursts (1-
100 data items) with 25%
probability
Enabling networked knowledge
78. Processing time per
client
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Enabling networked knowledge
79. Scalability in the number of
clients
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79 of 58
Enabling networked knowledge
80. Digital Enterprise Research Institute www.deri.ie
OK, now we also have a
nice middleware /
database abstraction
for any sensor type
Enabling networked knowledge
81. KISS revisited
Digital Enterprise Research Institute www.deri.ie
Application
CQELS REST SPARQL
Linked Streams Linked Data
Virtual COAP
Sensors Sensors
Enabling networked knowledge
82. Digital Enterprise Research Institute www.deri.ie
Putting it all together
Semantics / Linked Data / Real-Time / Streams / GIS
Enabling networked knowledge
83. Linking the Real World
Digital Enterprise Research Institute www.deri.ie
People in DERI scan QR code
with mobile to check into room
Position of people in DERI
RFID tag of person is identified
FOAF info is displayed
Availability based on haptic
phone interface
QR code points to FOAF profile
Associated RFID tag
Associated mobile
Available Not Available
Position of other people
In the demo room
Enabling networked knowledge
84. Behind the Scenes
Digital Enterprise Research Institute www.deri.ie
www.deri.ie REST
(FOAF) where.deri.ie
REST
gsn.deri.ie (FOAF) REST
(availability)
REST
REST
(position)
(position)
REST
Screen
(position, availability)
Demo room
RFID base station
Enabling networked knowledge
85. Digital Enterprise Research Institute www.deri.ie
OK, now let’s make
it bigger and
general-purpose!
Enabling networked knowledge
86. KISS re-re-visited
Digital Enterprise Research Institute www.deri.ie
Application
Middleware
CQELS REST SPARQL
Linked Streams Linked Data
Virtual COAP
Sensors Sensors
Enabling networked knowledge
87. Linked Sensor
Middleware
Digital Enterprise Research Institute www.deri.ie
Middleware for the semantic integration of live
real-world data
SPARQL endpoint for querying unified Linked Stream Data
and Linked Data
Sensor mashup composer
Wrappers for collecting and enriching
real-time / stream (sensor) data
Live data
Web interface for data
exploration, annotation and
visualisation
Mobile phone applications
Enabling networked knowledge
89. Linked Stream Model
Digital Enterprise Research Institute www.deri.ie
Sensor metadata
:weatherStation
ssn:observes
ssn:observes
:aTemperature ssn:observedBy
:aHumidity
ssn:isPropertyOf ssn:isPropertyOf
:dublinAirport
ssm:observedPropery ssm:observedPropery
ssn:featureOfInterest
:latestWeather
:tempValue ssn:observationResult :humidValue
ssn:hasValue ssn:hasValue
ssm:value ssm:value ssm:unit
ssm:unit :readings
“18”^xsd:fl “60”^xsd:fl
“Celcius” “%”
oat oat
Stream data snapshot at 2011-07-08T21:32:52
Enabling networked knowledge
90. Over 110,000 live data
sources
Digital Enterprise Research Institute www.deri.ie
Webcams:24570 Weather: 82365
Traffic:469 (London, Snowfall: 2639
Ohio) Snow depth: 377
Roadactivity:575 (Ohio) Sea level: 45
Flights: >1000 Radar:1
Railway stations:251 Satellite: 12
(London)
Bike hire:421(London)
… and growing!!!
Enabling networked knowledge
91. Deployment
Digital Enterprise Research Institute www.deri.ie
CQELS
Web
Virtuoso (Stream
server
Proc.)
Data Bus
Stream Sources
Enabling networked knowledge
92. Mobile Applications
Digital Enterprise Research Institute www.deri.ie
SPARQL,CQELS
SPARQL-XML/RDF
LSM
100-200 lines of code
Enabling networked knowledge
93. LSM: Live flights info
Digital Enterprise Research Institute www.deri.ie
Enabling networked knowledge
94. LSM: Live train info
Digital Enterprise Research Institute www.deri.ie
Enabling networked knowledge
95. LSM: Live traffic info
Digital Enterprise Research Institute www.deri.ie
Enabling networked knowledge
101. Across Research Areas
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Semantic Web
Linked Data
Mobile Cloud
Internet of Things
Enabling networked knowledge
102. Strategic Application
Domains
Digital Enterprise Research Institute www.deri.ie
Smart Cities
Enterprise Environments
Telehealth
Enabling networked knowledge
103. Upcoming Research
Areas
Digital Enterprise Research Institute www.deri.ie
Sensor data management in the Cloud
Sensor data annotation and sharing (portals,
community-based)
Social network analysis (online, mobile, real-world)
Social and opportunistic sensing (mobile phone)
Distributed query processing
Integrating business processes and sensors
Enabling networked knowledge
10
3
104. Conclusions
Digital Enterprise Research Institute www.deri.ie
“Linking the Real World”
requires cross-domain /
cross-layer research
Non-trivial, open research
questions knowledge
management, Semantic
Web, databases, Cloud,
sensor networks, etc.
Running systems and
experiments!
Enabling networked knowledge
105. Acknowledgements
Digital Enterprise Research Institute www.deri.ie
Danh Le-Phuoc
Anh Le Tuan
Myriam Leggieri
Hoan Nguyen Mau Quoc
Josiane Xavier Parreira
Martin Serrano
Christian von der Weth
Enabling networked knowledge