Hierarchical clustering of metamodels for comparative analysis and visualization

Ö. Babur; L.G.W.A. Cleophas; M.G.J. van den Brand

doi:10.1007/978-3-319-42061-5_1

Hierarchical clustering of metamodels for comparative analysis and visualization

Ö. Babur, L.G.W.A. Cleophas, M.G.J. van den Brand

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

31 Citaten (Scopus)

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Many applications in Model-Driven Engineering involve processing multiple models or metamodels. A good example is the comparison and merging of metamodel variants into a common metamodel in domain model recovery. Although there are many sophisticated techniques to process the input dataset, little attention has been given to the initial data analysis, visualization and filtering activities. These are hard to ignore especially in the case of a large dataset, possibly with outliers and sub-groupings. In this paper we present a generic approach for metamodel comparison, analysis and visualization as an exploratory first step for domain model recovery. We propose representing metamodels in a vector space model, and applying hierarchical clustering techniques to compare and visualize them as a tree structure. We demonstrate our approach on two Ecore datasets: a collection of 50 state machine metamodels extracted from GitHub as top search results; and ∼
∼
100 metamodels from 16 different domains, obtained from AtlanMod Metamodel Zoo.

Originele taal-2	Engels
Titel	Modelling Foundations and Applications
Subtitel	12th European Conference, ECMFA 2016, Held as Part of STAF 2016, Vienna, Austria, July 6-7, 2016, Proceedings
Redacteuren	A. Wąsowski, H. Loenn
Plaats van productie	Dordrecht
Uitgeverij	Springer
Pagina's	3-18
ISBN van elektronische versie	978-3-319-42061-5
ISBN van geprinte versie	978-3-319-42060-8
DOI's	https://doi.org/10.1007/978-3-319-42061-5_1
Status	Gepubliceerd - 2016

Publicatie series

Naam	Lecture Notes in Computer Science
Uitgeverij	Springer
Volume	9764

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10.1007/978-3-319-42061-5_1

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Babur, Ö., Cleophas, L. G. W. A., & van den Brand, M. G. J. (2016). Hierarchical clustering of metamodels for comparative analysis and visualization. In A. Wąsowski, & H. Loenn (editors), Modelling Foundations and Applications : 12th European Conference, ECMFA 2016, Held as Part of STAF 2016, Vienna, Austria, July 6-7, 2016, Proceedings (blz. 3-18). (Lecture Notes in Computer Science; Vol. 9764). Springer. https://doi.org/10.1007/978-3-319-42061-5_1

Babur, Ö. ; Cleophas, L.G.W.A. ; van den Brand, M.G.J. / Hierarchical clustering of metamodels for comparative analysis and visualization. Modelling Foundations and Applications : 12th European Conference, ECMFA 2016, Held as Part of STAF 2016, Vienna, Austria, July 6-7, 2016, Proceedings. redacteur / A. Wąsowski ; H. Loenn. Dordrecht : Springer, 2016. blz. 3-18 (Lecture Notes in Computer Science).

@inproceedings{7007684b07544206a5feddef5d749dc4,

title = "Hierarchical clustering of metamodels for comparative analysis and visualization",

abstract = "Many applications in Model-Driven Engineering involve processing multiple models or metamodels. A good example is the comparison and merging of metamodel variants into a common metamodel in domain model recovery. Although there are many sophisticated techniques to process the input dataset, little attention has been given to the initial data analysis, visualization and filtering activities. These are hard to ignore especially in the case of a large dataset, possibly with outliers and sub-groupings. In this paper we present a generic approach for metamodel comparison, analysis and visualization as an exploratory first step for domain model recovery. We propose representing metamodels in a vector space model, and applying hierarchical clustering techniques to compare and visualize them as a tree structure. We demonstrate our approach on two Ecore datasets: a collection of 50 state machine metamodels extracted from GitHub as top search results; and ∼ ∼100 metamodels from 16 different domains, obtained from AtlanMod Metamodel Zoo.",

author = "{\"O}. Babur and L.G.W.A. Cleophas and {van den Brand}, M.G.J.",

year = "2016",

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Babur, Ö , Cleophas, LGWA & van den Brand, MGJ 2016, Hierarchical clustering of metamodels for comparative analysis and visualization. in A Wąsowski & H Loenn (uitgave), Modelling Foundations and Applications : 12th European Conference, ECMFA 2016, Held as Part of STAF 2016, Vienna, Austria, July 6-7, 2016, Proceedings. Lecture Notes in Computer Science, vol. 9764, Springer, Dordrecht, blz. 3-18. https://doi.org/10.1007/978-3-319-42061-5_1

Hierarchical clustering of metamodels for comparative analysis and visualization. / Babur, Ö.; Cleophas, L.G.W.A.; van den Brand, M.G.J.
Modelling Foundations and Applications : 12th European Conference, ECMFA 2016, Held as Part of STAF 2016, Vienna, Austria, July 6-7, 2016, Proceedings. uitgave / A. Wąsowski; H. Loenn. Dordrecht: Springer, 2016. blz. 3-18 (Lecture Notes in Computer Science; Vol. 9764).

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

TY - GEN

T1 - Hierarchical clustering of metamodels for comparative analysis and visualization

AU - Babur, Ö.

AU - Cleophas, L.G.W.A.

AU - van den Brand, M.G.J.

PY - 2016

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N2 - Many applications in Model-Driven Engineering involve processing multiple models or metamodels. A good example is the comparison and merging of metamodel variants into a common metamodel in domain model recovery. Although there are many sophisticated techniques to process the input dataset, little attention has been given to the initial data analysis, visualization and filtering activities. These are hard to ignore especially in the case of a large dataset, possibly with outliers and sub-groupings. In this paper we present a generic approach for metamodel comparison, analysis and visualization as an exploratory first step for domain model recovery. We propose representing metamodels in a vector space model, and applying hierarchical clustering techniques to compare and visualize them as a tree structure. We demonstrate our approach on two Ecore datasets: a collection of 50 state machine metamodels extracted from GitHub as top search results; and ∼ ∼100 metamodels from 16 different domains, obtained from AtlanMod Metamodel Zoo.

AB - Many applications in Model-Driven Engineering involve processing multiple models or metamodels. A good example is the comparison and merging of metamodel variants into a common metamodel in domain model recovery. Although there are many sophisticated techniques to process the input dataset, little attention has been given to the initial data analysis, visualization and filtering activities. These are hard to ignore especially in the case of a large dataset, possibly with outliers and sub-groupings. In this paper we present a generic approach for metamodel comparison, analysis and visualization as an exploratory first step for domain model recovery. We propose representing metamodels in a vector space model, and applying hierarchical clustering techniques to compare and visualize them as a tree structure. We demonstrate our approach on two Ecore datasets: a collection of 50 state machine metamodels extracted from GitHub as top search results; and ∼ ∼100 metamodels from 16 different domains, obtained from AtlanMod Metamodel Zoo.

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Babur Ö , Cleophas LGWA , van den Brand MGJ. Hierarchical clustering of metamodels for comparative analysis and visualization. In Wąsowski A, Loenn H, redacteurs, Modelling Foundations and Applications : 12th European Conference, ECMFA 2016, Held as Part of STAF 2016, Vienna, Austria, July 6-7, 2016, Proceedings. Dordrecht: Springer. 2016. blz. 3-18. (Lecture Notes in Computer Science). doi: 10.1007/978-3-319-42061-5_1

Hierarchical clustering of metamodels for comparative analysis and visualization

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