Presented at The 6th Workshop on Semantics for Smarter Cities (S4SC 2015) co-located with The 14th International Semantic Web Conference (ISWC 2015). Full paper at: http://tw.rpi.edu/web/doc/santos-s4sc-2015

1. Contextual Data Collection for Smart
Cities
The 6th
Workshop on Semantics for Smarter Cities (S4SC 2015)
at The 14th
International Semantic Web Conference (ISWC 2015)
Bethlehem, Pennsylvania, U.S.A.
Henrique O. Santos, LEC-UNIFOR and TW-RPI
Vasco Furtado, LEC-UNIFOR and CITINOVA
Paulo Pinheiro, TW-RPI
Deborah L. McGuinness, TW-RPI

2. 2
Smart Cities
• Smart City is a city that is aimed to the
future, i.e., with public policies to foster
its safeness, sustainability,
creativeness, innovativeness and so
forth
• Two keys points are identified: access
to and understanding of city data

3. 3
Smart Cities are cities that produce relevant data that
can be understood, derive knowledge from this data
and use that knowledge to empower the city aspects.

4. 4
Open Government Data (OGD)
• City data encompasses not only datasets containing regular data from city
agencies, but also datasets and streams containing monitored data from
sensors deployed throughout the city
• This monitored data is normally published as regular datasets (many times in
CSV format) without further information about the sensor network that is
behind the collection of the data
• Monitored data is about data that is collected empirically by sensors
deployed in the city. It talks about a measured value that is obtained while
sensing a characteristic of an entity of interest

5. 5
Aspects of OGD today
Aspect How it is addressed
Data presentation to the
stakeholders
- Datasets
Metadata information - Description text files
- Annotations
- Derived from the above
Provenance - Dataset level:
Description text files
- Data level: (mostly not
addressed)
Context (Not addressed)

6. 6
Context timeline
t
Feb 12, 2015,
11:45PM
Feb 11, 2015,
10:00AM
Configuration
Deployment
Dec 28, 2015,
11:32AM
Dec 16, 2015,
9:55AM
Calibration
Acquire
Nov 4, 2014,
12:55PM
t
February 12, 2015,
9:30AM
February 12, 2015,
11:45PM
Auto calibration
Oct , 2015,
10:33AM
Feb 12, 2015,
9:30AM

7. 7
City sensor network
Sensors
• What is being monitored on the city?
• Where are the sensors deployed?
• What are the sensors capable of monitoring?
Monitored data
• Is this data coming from which sensor?
• Can one compare two monitored values for
scientific purposes?

8. 8
HASNetO
●
The Human-Aware Sensor Network Ontology [1]
VSTO-I OBOE
Deployment Data Collection Dataset Measurement
Entity Characteristic Unit Platform
Instrument Detector
1. Pinheiro, P., McGuinness, D.L., Santos, H.: Human-Aware Sensor Network Ontology: Semantic Support for Empirical Data
Collection. In: Proceedings of the 5th Workshop on Linked Science. Bethlehem, PA, USA (2015)
2. Fox, P., McGuinness, D.L., Cinquini, L., West, P., Garcia, J., Benedict, J.L., Middleton, D.: Ontology-supported scientific data
frameworks: The Virtual Solar-Terrestrial Observatory experience. Computers & Geosciences 35(4), 724–738 (Apr 2009)
3. http://www.w3.org/TR/prov-o
4. Madin, J., Bowers, S., Schildhauer, M., Krivov, S., Pennington, D., Villa, F.: An ontology for describing and synthesizing ecological
observation data. Ecological Informatics 2(3), 279–296 (Oct 2007)
[2
]
[3
]
[4
]

9. 9
HASNetO-SC
• The Human-Aware Sensor Network Ontology for Smart Cities

10. 10
Contextualized CSV - CCSV
TimeStamp,AirTemp_C_Avg,RH_Pct_Avg
2015-02-12T09:30:00Z,-4.5,66.58
2015-02-12T09:45:00Z,-4.372,66.45
2015-02-12T10:00:00Z,-4.146,65.98
2015-02-12T10:15:00Z,-4.084,66.22
2015-02-12T10:30:00Z,-4.251,67.48
2015-02-12T10:45:00Z,-4.185,69.85
2015-02-12T11:00:00Z,-4.133,72
2015-02-12T11:15:00Z,-3.959,70.84
…
2015-02-12T23:00:00Z,-9.63,77.88
2015-02-12T23:15:00Z,-10.48,80.8
2015-02-12T23:30:00Z,-10.96,82
2015-02-12T23:45:00Z,-10.1,80.7
t
February 12, 2015,
9:30AM
February 12, 2015,
11:45PM

11. 11

12. 12
senses senses
SOLR
CCSV-loader
Ontologies
(HASNetO, OBOE,
PROV, VSTO)Data Metadata
data (CCSV)
data (CCSV)
expanded CSV
Sensor network
description
Data browser
SPARQL / SOLR queries
Data users
Architecture

13. 13
Fortaleza is the 5th
biggest capital in Brazil
With more than 2.5 million residents

14. 14
Use case: Fortaleza bus
transportation system
• http://dados.fortaleza.ce.gov.br
• Used datasets
– Bus checkpoints
– Bus companies
– Bus fleet
– GPS measurements for February 2015

15. 15
Domain ontology

16. 16
Fortaleza bus sensor network description

17. 17

18. 18

19. 19
Aspects of OGD with HASNetO-SC
Aspect How it is addressed How we are addressing
Data presentation to
the stakeholders
- Datasets - Data collections
Metadata information - Description text files
- Annotations
- Derived from the above
- HASNetO-SC sensor
network
- OBOE concepts
Provenance - Dataset level: Description
text files
- Data level: (mostly not
addressed)
- PROV-O
Context (Not addressed) - HASNetO activities

20. 20
Conclusion and next steps
• A challenge exists in representing context in city sensor
networks in a meaningful way, i.e., that can leverage the full
potential the data it collects
• Our work addresses that challenge by linking the monitored
data to metadata (sensor network and activities) using CCSV
and HASNetO-SC
• We are approaching monitored data, but non-monitored data
also plays a main role on smart cities. We are currently
researching how to cope PROV with “told” data

21. 21
Thank you!
Questions?
Henrique O. Santos – oliveh@rpi.edu
Vasco Furtado – vasco@unifor.br
Paulo Pinheiro – pinhep@rpi.edu
Deborah L. McGuinness – dlm@cs.rpi.edu