xWEB DATA evolved over time
2
Static Document and files
Real-Time Sensor, Social, Multi-media
data
Dynamic User Generated Content
1990’s
2000’s
2010’s
xProperties of Streaming Data
3
Continuous
RapidHuge Volume
Heterogeneous
Information Overload!!
xSome Statistics
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“Sensors Networks will produce 10-20 times the amount of generated by social media in the next few years” - GigaOmni Media
Solution - “Meaningfully summarize this data”“More data has been created in the last three years than in all the past 40,000 years”- Teradata
“A cross-country flight from New York to Los Angeles on a Boeing 737 plane generates a massive 240 terabytes of data”- GigaOmni Media
Real-Time Analysisof Streaming Sensor Data
Harshal Patni, Cory Henson, Michael Cooney,Amit Sheth, Thirunarayan Krishnaprasad
Ohio Center of Excellence in Knowledge enabled Computing (Kno.e.sis) Wright State University, Dayton, OH
Semantic Sensor Web @ Kno.e.sis
48th ACM Southeast Conference. ACMSE 2010. Oxford, Mississippi. April 15-17, 2010.
xRT feature stream
7
Huge amount of Raw Sensor Data
Background Knowledge
Features representing Real-World events
ABSTRACTION
BlizzardRain Storm
xTypes of Abstractions
8
Sum
mar
izat
ion
over
the
Tem
pora
l Dim
ensi
on
Summarization across Thematic Dimension
xTypes of Abstractions
9
Summarization across Thematic Dimension
AnalyzeBackground Knowledge
Select
Join
Features representing Real-World Events
xSystem Architecture
10
xAn example problem?
11
“Find the sequence of weather events observed near Dayton James Cox Airport between Jan 13th and Jan 18th?”
Thematic Spatial Temporal
Technologies required - 1. Linked Sensor Data2. Feature Streams
Sensor Discovery Application
12
Weather Station ID
Weather Station Coordinates
Weather Station Phenomena
Current Observations from MesoWest
MesoWest – Project under Department of Meteorology, University of UTAH
GeoNames – Geographic dataset
Sensors near Dayton James Cox Airport
Linked Sensor Data
13
O&M2RDFCONVERTER
Summarizing Linked Sensor Data
ObservationKB Sensor KB Location KB
(Geonames)
procedure locationlocation
procedure location720F Thermometer Dayton Airport
• ~2 billion triples• MesoWest• Static +
Dynamic
• 20,000+ systems• MesoWest• ~Static
• 230,000+ locations
• Geonames• ~Static
Find the sensor around Dayton James Cox Airport?
Extract Data for the sensor?
xFeature Composition
15
xSystem Capability
16
xSystem Feature Integration
17
SELECT
JOIN
xFeature Definition
18
• Rain Storm NOAA definitionRainStorm = HighWindSpeed(above 35mph) AND
Rain Precipitation AND Temperature(greater than 32F)
SPARQL query for RainStorm
Temperature
Rain Precipitation
WindSpeed
xFeature Analysis
19
RDF Feature Stream
Summarizing Feature Streams
ObservationKB Sensor KB Location KB
(Geonames)
procedurelocation
procedure location720F Thermometer Dayton Airport
• ~2 billion triples• MesoWest• Static +
Dynamic
• 20,000+ systems• MesoWest• ~Static
• 230,000+ locations
• Geonames• ~Static
Feature StreamsKB
Find sequence of events near Dayton Airport?
xAnswering the query
21
“Find the sequence of weather events observed near Dayton James Cox Airport between Jan 13th and Jan 18th?”
Linked Sensor Data Feature Streams
xDemo
22
on-line video: http://www.youtube.com/watch?v=_ews4w_eCpg
WORKSHOP PAPERS• Harshal Patni, Satya S. Sahoo, Cory Henson, Amit Sheth,
Provenance Aware Linked Sensor Data, 2nd Workshop on Trust and Privacy on Social and Semantic Web,Co-Located with ESWC, Heraklion Greece, May 30th - June 3rd 2010
• Harshal Patni, Cory Henson, Amit Sheth, Linked Sensor Data, In: Proceedings of 2010 International Symposium on Collaborative Technologies and Systems (CTS 2010), Chicago, IL, May 17-21, 2010
TECHNICAL REPORT• Harshal Patni, Cory Henson, Amit Sheth, and Pramod Ananthram.
From Real Time Sensor Streams to Real Time Feature Streams, Kno.e.sis Center Technical Report, December 2009
• Joshua Pschorr, Cory Henson, Harshal Patni, and Amit Sheth. Sensor Discovery on Linked Data, Kno.e.sis Center Technical Report, December 2009
JOURNAL PAPER (In Progress)• Semantic Sensor Web: Design and Application towards weaving a meaningful sensor web
Related Publications
23
Semantic Sensor Web
24
Demos, Papers and more at: http://semantic-sensor-web.com
Semantic Sensor Web @ Kno.e.sis
QUESTIONS
25