Data Verification for Collective Adaptive Systems: Spatial Model-Checking of Vehicle Location Data

Vincenzo Ciancia; Stephen Gilmore; Diego Latella; Michele Loreti; Mieke Massink

doi:10.1109/SASOW.2014.16

Data Verification for Collective Adaptive Systems: Spatial Model-Checking of Vehicle Location Data

Vincenzo Ciancia, Stephen Gilmore, Diego Latella, Michele Loreti, Mieke Massink

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper we present the use of a novel spatial model-checker to detect problems in the data which an adaptive system gathers in order to inform future action. We categorise received data as being plausible, implausible, possible or problematic. Data correctness is essential to ensure correct functionality in systems which adapt in response to data and our categorisation influences the degree of caution which should be used in acting in response to this received data. We illustrate the theory with a concrete example of detecting errors in vehicle location data for buses in the city of Edinburgh. Vehicle location data is visualised symbolically on a street map, and categories of problems identified by the spatial model-checker are rendered by repainting the symbols for vehicles in different colours.

Original language	English
Title of host publication	Eighth IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW 2014, London, United Kingdom, September 8-12, 2014
Publisher	Institute of Electrical and Electronics Engineers
Pages	32-37
Number of pages	6
ISBN (Print)	978-1-4799-6378-2
DOIs	https://doi.org/10.1109/SASOW.2014.16
Publication status	Published - 2014

Access to Document

10.1109/SASOW.2014.16

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7056349

QUANTICOL - A Quantitative Approach to Management and Design of Collective and Adaptive Behaviours (RTD)
Hillston, J. (Principal Investigator) & Gilmore, S. (Co-investigator)
EU government bodies
1/04/13 → 31/03/17
Project: Research

Cite this

Ciancia, V., Gilmore, S., Latella, D., Loreti, M., & Massink, M. (2014). Data Verification for Collective Adaptive Systems: Spatial Model-Checking of Vehicle Location Data. In Eighth IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW 2014, London, United Kingdom, September 8-12, 2014 (pp. 32-37). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/SASOW.2014.16

Ciancia, Vincenzo ; Gilmore, Stephen ; Latella, Diego et al. / Data Verification for Collective Adaptive Systems: Spatial Model-Checking of Vehicle Location Data. Eighth IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW 2014, London, United Kingdom, September 8-12, 2014. Institute of Electrical and Electronics Engineers, 2014. pp. 32-37

@inproceedings{a7db611a2c6047ea830c7fac54e356cd,

title = "Data Verification for Collective Adaptive Systems: Spatial Model-Checking of Vehicle Location Data",

abstract = "In this paper we present the use of a novel spatial model-checker to detect problems in the data which an adaptive system gathers in order to inform future action. We categorise received data as being plausible, implausible, possible or problematic. Data correctness is essential to ensure correct functionality in systems which adapt in response to data and our categorisation influences the degree of caution which should be used in acting in response to this received data. We illustrate the theory with a concrete example of detecting errors in vehicle location data for buses in the city of Edinburgh. Vehicle location data is visualised symbolically on a street map, and categories of problems identified by the spatial model-checker are rendered by repainting the symbols for vehicles in different colours.",

author = "Vincenzo Ciancia and Stephen Gilmore and Diego Latella and Michele Loreti and Mieke Massink",

year = "2014",

doi = "10.1109/SASOW.2014.16",

language = "English",

isbn = "978-1-4799-6378-2",

pages = "32--37",

booktitle = "Eighth IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW 2014, London, United Kingdom, September 8-12, 2014",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

}

Ciancia, V, Gilmore, S, Latella, D, Loreti, M & Massink, M 2014, Data Verification for Collective Adaptive Systems: Spatial Model-Checking of Vehicle Location Data. in Eighth IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW 2014, London, United Kingdom, September 8-12, 2014. Institute of Electrical and Electronics Engineers, pp. 32-37. https://doi.org/10.1109/SASOW.2014.16

Data Verification for Collective Adaptive Systems: Spatial Model-Checking of Vehicle Location Data. / Ciancia, Vincenzo; Gilmore, Stephen; Latella, Diego et al.
Eighth IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW 2014, London, United Kingdom, September 8-12, 2014. Institute of Electrical and Electronics Engineers, 2014. p. 32-37.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Data Verification for Collective Adaptive Systems: Spatial Model-Checking of Vehicle Location Data

AU - Ciancia, Vincenzo

AU - Gilmore, Stephen

AU - Latella, Diego

AU - Loreti, Michele

AU - Massink, Mieke

PY - 2014

Y1 - 2014

N2 - In this paper we present the use of a novel spatial model-checker to detect problems in the data which an adaptive system gathers in order to inform future action. We categorise received data as being plausible, implausible, possible or problematic. Data correctness is essential to ensure correct functionality in systems which adapt in response to data and our categorisation influences the degree of caution which should be used in acting in response to this received data. We illustrate the theory with a concrete example of detecting errors in vehicle location data for buses in the city of Edinburgh. Vehicle location data is visualised symbolically on a street map, and categories of problems identified by the spatial model-checker are rendered by repainting the symbols for vehicles in different colours.

AB - In this paper we present the use of a novel spatial model-checker to detect problems in the data which an adaptive system gathers in order to inform future action. We categorise received data as being plausible, implausible, possible or problematic. Data correctness is essential to ensure correct functionality in systems which adapt in response to data and our categorisation influences the degree of caution which should be used in acting in response to this received data. We illustrate the theory with a concrete example of detecting errors in vehicle location data for buses in the city of Edinburgh. Vehicle location data is visualised symbolically on a street map, and categories of problems identified by the spatial model-checker are rendered by repainting the symbols for vehicles in different colours.

U2 - 10.1109/SASOW.2014.16

DO - 10.1109/SASOW.2014.16

M3 - Conference contribution

SN - 978-1-4799-6378-2

SP - 32

EP - 37

BT - Eighth IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW 2014, London, United Kingdom, September 8-12, 2014

PB - Institute of Electrical and Electronics Engineers

ER -

Ciancia V, Gilmore S, Latella D, Loreti M, Massink M. Data Verification for Collective Adaptive Systems: Spatial Model-Checking of Vehicle Location Data. In Eighth IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW 2014, London, United Kingdom, September 8-12, 2014. Institute of Electrical and Electronics Engineers. 2014. p. 32-37 doi: 10.1109/SASOW.2014.16

Data Verification for Collective Adaptive Systems: Spatial Model-Checking of Vehicle Location Data

Abstract

Access to Document

Fingerprint

Projects

QUANTICOL - A Quantitative Approach to Management and Design of Collective and Adaptive Behaviours (RTD)

Cite this