Workflow Discovery Through Semantic Constraints:  A Geovisualization Case Study

Vedran Kasalica; Anna-Lena Lamprecht

doi:10.1007/978-3-030-24302-9_34

Workflow Discovery Through Semantic Constraints: A Geovisualization Case Study

Vedran Kasalica, Anna-Lena Lamprecht

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

Abstract

The construction of computational pipelines, for example automated cartographic workflows for the construction of thematic maps, typically requires detailed knowledge about the available tools for the individual steps and the technicalities of their composition. It is a time-consuming process and comes with the risk of missing meaningful workflows because many possible pipelines are never taken into account. Automated workflow composition techniques can facilitate comprehensive workflow discovery based on semantic constraints: The users express their intention about the workflows by means of high-level constraints, and receive possible workflows that meet their request. The successful application of such methods essentially depends on the availability and quality of semantic domain models that describe the tools and data types in the domain. In this paper, we present an exemplary domain model for a geovisualization use case, and show how it enables the abstract specification and automated composition of a complex cartographic workflow.

Original language	English
Title of host publication	Computational Science and Its Applications -- ICCSA 2019
Subtitle of host publication	19th International Conference, Saint Petersburg, Russia, July 1-4, 2019, Proceedings
Editors	Sanjay Misra, Osvaldo Gervasi, Beniamino Murgante, Elena Stankova, Vladimir Korkhov, Carmelo Torre, Ana Maria A.C. Rocha, David Taniar, Bernady O. Apduhan, Eufemia Tarantino
Place of Publication	Cham
Publisher	Springer
Pages	473-488
Number of pages	16
ISBN (Electronic)	9783030243029
ISBN (Print)	9783030243012
DOIs	https://doi.org/10.1007/978-3-030-24302-9_34
Publication status	Published - 2019
Event	International Conference on Computational Science and its Applications - St. Petersburg, Russian Federation Duration: 1 Jul 2019 → 4 Jul 2019 Conference number: 19 http://www.iccsa.org/

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	11621
ISSN (Print)	0302-9743
ISSN (Electronic)	0302-9743

Conference

Conference	International Conference on Computational Science and its Applications
Abbreviated title	ICCSA
Country/Territory	Russian Federation
City	St. Petersburg
Period	1/07/19 → 4/07/19
Internet address	http://www.iccsa.org/

Keywords

scientific workflows
automated workflow composition
workflow discovery
workflow synthesis
semantic domain modeling
geoscience
geovisualization

Access to Document

10.1007/978-3-030-24302-9_34

978-3-030-24302-9_34Final published version, 3.78 MBLicence: Taverne

Cite this

Kasalica, V., & Lamprecht, A.-L. (2019). Workflow Discovery Through Semantic Constraints: A Geovisualization Case Study. In S. Misra, O. Gervasi, B. Murgante, E. Stankova, V. Korkhov, C. Torre, A. M. A. C. Rocha, D. Taniar, B. O. Apduhan, & E. Tarantino (Eds.), Computational Science and Its Applications -- ICCSA 2019: 19th International Conference, Saint Petersburg, Russia, July 1-4, 2019, Proceedings (pp. 473-488). (Lecture Notes in Computer Science; Vol. 11621). Springer. https://doi.org/10.1007/978-3-030-24302-9_34

Kasalica, Vedran ; Lamprecht, Anna-Lena. / Workflow Discovery Through Semantic Constraints : A Geovisualization Case Study. Computational Science and Its Applications -- ICCSA 2019: 19th International Conference, Saint Petersburg, Russia, July 1-4, 2019, Proceedings. editor / Sanjay Misra ; Osvaldo Gervasi ; Beniamino Murgante ; Elena Stankova ; Vladimir Korkhov ; Carmelo Torre ; Ana Maria A.C. Rocha ; David Taniar ; Bernady O. Apduhan ; Eufemia Tarantino. Cham : Springer, 2019. pp. 473-488 (Lecture Notes in Computer Science).

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abstract = "The construction of computational pipelines, for example automated cartographic workflows for the construction of thematic maps, typically requires detailed knowledge about the available tools for the individual steps and the technicalities of their composition. It is a time-consuming process and comes with the risk of missing meaningful workflows because many possible pipelines are never taken into account. Automated workflow composition techniques can facilitate comprehensive workflow discovery based on semantic constraints: The users express their intention about the workflows by means of high-level constraints, and receive possible workflows that meet their request. The successful application of such methods essentially depends on the availability and quality of semantic domain models that describe the tools and data types in the domain. In this paper, we present an exemplary domain model for a geovisualization use case, and show how it enables the abstract specification and automated composition of a complex cartographic workflow.",

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booktitle = "Computational Science and Its Applications -- ICCSA 2019",

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Kasalica, V & Lamprecht, A-L 2019, Workflow Discovery Through Semantic Constraints: A Geovisualization Case Study. in S Misra, O Gervasi, B Murgante, E Stankova, V Korkhov, C Torre, AMAC Rocha, D Taniar, BO Apduhan & E Tarantino (eds), Computational Science and Its Applications -- ICCSA 2019: 19th International Conference, Saint Petersburg, Russia, July 1-4, 2019, Proceedings. Lecture Notes in Computer Science, vol. 11621, Springer, Cham, pp. 473-488, International Conference on Computational Science and its Applications, St. Petersburg, Russian Federation, 1/07/19. https://doi.org/10.1007/978-3-030-24302-9_34

Workflow Discovery Through Semantic Constraints: A Geovisualization Case Study. / Kasalica, Vedran; Lamprecht, Anna-Lena.
Computational Science and Its Applications -- ICCSA 2019: 19th International Conference, Saint Petersburg, Russia, July 1-4, 2019, Proceedings. ed. / Sanjay Misra; Osvaldo Gervasi; Beniamino Murgante; Elena Stankova; Vladimir Korkhov; Carmelo Torre; Ana Maria A.C. Rocha; David Taniar; Bernady O. Apduhan; Eufemia Tarantino. Cham: Springer, 2019. p. 473-488 (Lecture Notes in Computer Science; Vol. 11621).

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

TY - GEN

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AU - Kasalica, Vedran

AU - Lamprecht, Anna-Lena

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PY - 2019

Y1 - 2019

N2 - The construction of computational pipelines, for example automated cartographic workflows for the construction of thematic maps, typically requires detailed knowledge about the available tools for the individual steps and the technicalities of their composition. It is a time-consuming process and comes with the risk of missing meaningful workflows because many possible pipelines are never taken into account. Automated workflow composition techniques can facilitate comprehensive workflow discovery based on semantic constraints: The users express their intention about the workflows by means of high-level constraints, and receive possible workflows that meet their request. The successful application of such methods essentially depends on the availability and quality of semantic domain models that describe the tools and data types in the domain. In this paper, we present an exemplary domain model for a geovisualization use case, and show how it enables the abstract specification and automated composition of a complex cartographic workflow.

AB - The construction of computational pipelines, for example automated cartographic workflows for the construction of thematic maps, typically requires detailed knowledge about the available tools for the individual steps and the technicalities of their composition. It is a time-consuming process and comes with the risk of missing meaningful workflows because many possible pipelines are never taken into account. Automated workflow composition techniques can facilitate comprehensive workflow discovery based on semantic constraints: The users express their intention about the workflows by means of high-level constraints, and receive possible workflows that meet their request. The successful application of such methods essentially depends on the availability and quality of semantic domain models that describe the tools and data types in the domain. In this paper, we present an exemplary domain model for a geovisualization use case, and show how it enables the abstract specification and automated composition of a complex cartographic workflow.

KW - scientific workflows

KW - automated workflow composition

KW - workflow discovery

KW - workflow synthesis

KW - semantic domain modeling

KW - geoscience

KW - geovisualization

U2 - 10.1007/978-3-030-24302-9_34

DO - 10.1007/978-3-030-24302-9_34

M3 - Conference contribution

SN - 9783030243012

T3 - Lecture Notes in Computer Science

SP - 473

EP - 488

BT - Computational Science and Its Applications -- ICCSA 2019

A2 - Misra, Sanjay

A2 - Gervasi, Osvaldo

A2 - Murgante, Beniamino

A2 - Stankova, Elena

A2 - Korkhov, Vladimir

A2 - Torre, Carmelo

A2 - Rocha, Ana Maria A.C.

A2 - Taniar, David

A2 - Apduhan, Bernady O.

A2 - Tarantino, Eufemia

PB - Springer

CY - Cham

Y2 - 1 July 2019 through 4 July 2019

ER -

Kasalica V, Lamprecht AL. Workflow Discovery Through Semantic Constraints: A Geovisualization Case Study. In Misra S, Gervasi O, Murgante B, Stankova E, Korkhov V, Torre C, Rocha AMAC, Taniar D, Apduhan BO, Tarantino E, editors, Computational Science and Its Applications -- ICCSA 2019: 19th International Conference, Saint Petersburg, Russia, July 1-4, 2019, Proceedings. Cham: Springer. 2019. p. 473-488. (Lecture Notes in Computer Science). doi: 10.1007/978-3-030-24302-9_34