Data inconsistency in sunspot detection

Ehsan Shahamatnia; Ivan Dorotovič; André Mora; José Fonseca; Rita Ribeiro

doi:10.1007/978-3-319-11310-4_49

Data inconsistency in sunspot detection

Ehsan Shahamatnia, Ivan Dorotovič, André Mora, José Fonseca, Rita Ribeiro

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

2 Citations (Scopus)

Abstract

Availability of integrated high quality information is a prerequisite for many intelligent knowledge based systems. Consistency of data plays an influential role in reassuring the quality of the integrated data. In this paper we discuss issues of data inconsistency in the domain of sunspot detection (i.e. a manifestation of solar activity). Sunspots data are collected from ground based observatories and also from instruments aboard satellites. Due to instrumentation limitations and inevitable subjectivity of human observers, the collected data bear some levels of inconsistency. This paper discusses issues regarding inconsistency in data used for performance validation of an automated sunspot tracking system. For evaluating the results, an integrated probability reference map is created, using knowledge integration, which reinforces data accuracy with higher certainty. Further, we use a weighted matching technique to reduce the impact of some data inconsistency.

Original language	English
Title of host publication	Intelligent Systems'2014
Subtitle of host publication	Tools, Architectures, Systems, Applications
Editors	D. Filev, J. Jabłkowski, J. Kacprzyk, M. Krawczak, I. Popchev, L. Rutkowski, V. Sgurev, E. Sotirova, P. Szynkarczyk, S. Zadrozny
Place of Publication	Cham
Publisher	Springer Verlag
Pages	567-577
Number of pages	11
Volume	2
ISBN (Electronic)	978-3-319-11310-4
ISBN (Print)	978-3-319-11309-8
DOIs	https://doi.org/10.1007/978-3-319-11310-4_49
Publication status	Published - 2015
Event	7th IEEE International Conference Intelligent Systems (IS’2014) - Warsaw, Poland Duration: 24 Sept 2014 → 26 Sept 2014 Conference number: 7th

Publication series

Name	Advances in Intelligent Systems and Computing
Publisher	Springer-Verlag
Volume	323
ISSN (Print)	2194-5357

Conference

Conference	7th IEEE International Conference Intelligent Systems (IS’2014)
Abbreviated title	IS’2014
Country/Territory	Poland
City	Warsaw
Period	24/09/14 → 26/09/14

Keywords

Data fusion
Knowledge integration
Solar image processing
Sunspot

Access to Document

10.1007/978-3-319-11310-4_49

Cite this

Shahamatnia, E., Dorotovič, I., Mora, A., Fonseca, J., & Ribeiro, R. (2015). Data inconsistency in sunspot detection. In D. Filev, J. Jabłkowski, J. Kacprzyk, M. Krawczak, I. Popchev, L. Rutkowski, V. Sgurev, E. Sotirova, P. Szynkarczyk, & S. Zadrozny (Eds.), Intelligent Systems'2014: Tools, Architectures, Systems, Applications (Vol. 2, pp. 567-577). (Advances in Intelligent Systems and Computing; Vol. 323). Springer Verlag. https://doi.org/10.1007/978-3-319-11310-4_49

Shahamatnia, Ehsan ; Dorotovič, Ivan ; Mora, André et al. / Data inconsistency in sunspot detection. Intelligent Systems'2014: Tools, Architectures, Systems, Applications. editor / D. Filev ; J. Jabłkowski ; J. Kacprzyk ; M. Krawczak ; I. Popchev ; L. Rutkowski ; V. Sgurev ; E. Sotirova ; P. Szynkarczyk ; S. Zadrozny. Vol. 2 Cham : Springer Verlag, 2015. pp. 567-577 (Advances in Intelligent Systems and Computing).

@inproceedings{da524ff758c845728ed82c09386a2c7c,

title = "Data inconsistency in sunspot detection",

abstract = "Availability of integrated high quality information is a prerequisite for many intelligent knowledge based systems. Consistency of data plays an influential role in reassuring the quality of the integrated data. In this paper we discuss issues of data inconsistency in the domain of sunspot detection (i.e. a manifestation of solar activity). Sunspots data are collected from ground based observatories and also from instruments aboard satellites. Due to instrumentation limitations and inevitable subjectivity of human observers, the collected data bear some levels of inconsistency. This paper discusses issues regarding inconsistency in data used for performance validation of an automated sunspot tracking system. For evaluating the results, an integrated probability reference map is created, using knowledge integration, which reinforces data accuracy with higher certainty. Further, we use a weighted matching technique to reduce the impact of some data inconsistency.",

keywords = "Data fusion, Knowledge integration, Solar image processing, Sunspot",

author = "Ehsan Shahamatnia and Ivan Dorotovi{\v c} and Andr{\'e} Mora and Jos{\'e} Fonseca and Rita Ribeiro",

year = "2015",

doi = "10.1007/978-3-319-11310-4_49",

language = "English",

isbn = "978-3-319-11309-8",

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series = "Advances in Intelligent Systems and Computing",

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pages = "567--577",

editor = "Filev, {D. } and J. Jab{\l}kowski and Kacprzyk, {J. } and Krawczak, {M. } and Popchev, {I. } and Rutkowski, {L. } and Sgurev, {V. } and Sotirova, {E. } and Szynkarczyk, {P. } and Zadrozny, {S. }",

booktitle = "Intelligent Systems'2014",

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Shahamatnia, E, Dorotovič, I, Mora, A , Fonseca, J & Ribeiro, R 2015, Data inconsistency in sunspot detection. in D Filev, J Jabłkowski, J Kacprzyk, M Krawczak, I Popchev, L Rutkowski, V Sgurev, E Sotirova, P Szynkarczyk & S Zadrozny (eds), Intelligent Systems'2014: Tools, Architectures, Systems, Applications. vol. 2, Advances in Intelligent Systems and Computing, vol. 323, Springer Verlag, Cham, pp. 567-577, 7th IEEE International Conference Intelligent Systems (IS’2014), Warsaw, Poland, 24/09/14. https://doi.org/10.1007/978-3-319-11310-4_49

Data inconsistency in sunspot detection. / Shahamatnia, Ehsan; Dorotovič, Ivan; Mora, André et al.
Intelligent Systems'2014: Tools, Architectures, Systems, Applications. ed. / D. Filev; J. Jabłkowski; J. Kacprzyk; M. Krawczak; I. Popchev; L. Rutkowski; V. Sgurev; E. Sotirova; P. Szynkarczyk; S. Zadrozny. Vol. 2 Cham: Springer Verlag, 2015. p. 567-577 (Advances in Intelligent Systems and Computing; Vol. 323).

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

TY - GEN

T1 - Data inconsistency in sunspot detection

AU - Shahamatnia, Ehsan

AU - Dorotovič, Ivan

AU - Mora, André

AU - Fonseca, José

AU - Ribeiro, Rita

N1 - Conference code: 7th

PY - 2015

Y1 - 2015

N2 - Availability of integrated high quality information is a prerequisite for many intelligent knowledge based systems. Consistency of data plays an influential role in reassuring the quality of the integrated data. In this paper we discuss issues of data inconsistency in the domain of sunspot detection (i.e. a manifestation of solar activity). Sunspots data are collected from ground based observatories and also from instruments aboard satellites. Due to instrumentation limitations and inevitable subjectivity of human observers, the collected data bear some levels of inconsistency. This paper discusses issues regarding inconsistency in data used for performance validation of an automated sunspot tracking system. For evaluating the results, an integrated probability reference map is created, using knowledge integration, which reinforces data accuracy with higher certainty. Further, we use a weighted matching technique to reduce the impact of some data inconsistency.

AB - Availability of integrated high quality information is a prerequisite for many intelligent knowledge based systems. Consistency of data plays an influential role in reassuring the quality of the integrated data. In this paper we discuss issues of data inconsistency in the domain of sunspot detection (i.e. a manifestation of solar activity). Sunspots data are collected from ground based observatories and also from instruments aboard satellites. Due to instrumentation limitations and inevitable subjectivity of human observers, the collected data bear some levels of inconsistency. This paper discusses issues regarding inconsistency in data used for performance validation of an automated sunspot tracking system. For evaluating the results, an integrated probability reference map is created, using knowledge integration, which reinforces data accuracy with higher certainty. Further, we use a weighted matching technique to reduce the impact of some data inconsistency.

KW - Data fusion

KW - Knowledge integration

KW - Solar image processing

KW - Sunspot

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DO - 10.1007/978-3-319-11310-4_49

M3 - Conference contribution

AN - SCOPUS:84921490048

SN - 978-3-319-11309-8

VL - 2

T3 - Advances in Intelligent Systems and Computing

SP - 567

EP - 577

BT - Intelligent Systems'2014

A2 - Filev, D.

A2 - Jabłkowski, J.

A2 - Kacprzyk, J.

A2 - Krawczak, M.

A2 - Popchev, I.

A2 - Rutkowski, L.

A2 - Sgurev, V.

A2 - Sotirova, E.

A2 - Szynkarczyk, P.

A2 - Zadrozny, S.

PB - Springer Verlag

CY - Cham

T2 - 7th IEEE International Conference Intelligent Systems (IS’2014)

Y2 - 24 September 2014 through 26 September 2014

ER -

Shahamatnia E, Dorotovič I, Mora A , Fonseca J, Ribeiro R. Data inconsistency in sunspot detection. In Filev D, Jabłkowski J, Kacprzyk J, Krawczak M, Popchev I, Rutkowski L, Sgurev V, Sotirova E, Szynkarczyk P, Zadrozny S, editors, Intelligent Systems'2014: Tools, Architectures, Systems, Applications. Vol. 2. Cham: Springer Verlag. 2015. p. 567-577. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-319-11310-4_49

Data inconsistency in sunspot detection

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