Semantic typing of linked geoprocessing workflows
Scheider, S. and Ballatore, Andrea (2017) Semantic typing of linked geoprocessing workflows. International Journal of Digital Earth 11 (1), pp. 113-138. ISSN 1753-8955.
|
Text
2017-Scheider-Ballatore-Linked_Geoprocessing_Workflows.pdf - Author's Accepted Manuscript Download (5MB) | Preview |
|
|
Text
20772.pdf - Published Version of Record Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (5MB) | Preview |
Abstract
In Geographic Information Systems (GIS), geoprocessing workflows allow analysts to organize their methods on spatial data in complex chains. We propose a method for expressing workflows as linked data, and for semi-automatically enriching them with semantics on the level of their operations and datasets. Linked workflows can be easily published on the Web and queried for types of inputs, results, or tools. Thus, GIS analysts can reuse their workflows in a modular way, selecting, adapting, and recommending resources based on compatible semantic types. Our typing approach starts from minimal annotations of workflow operations with classes of GIS tools, and then propagates data types and implicit semantic structures through the workflow using an OWL typing scheme and SPARQL rules by backtracking over GIS operations. The method is implemented in Python and is evaluated on two real-world geoprocessing workflows, generated with Esri’s ArcGIS. To illustrate the potential applications of our typing method, we formulate and execute competency questions over these workflows.
Metadata
| Item Type: | Article |
|---|---|
| Additional Information: | This is the peer reviewed version of the article, which has been published in final form at the link above. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. |
| Keyword(s) / Subject(s): | Geoprocessing, spatial analysis, workflows, semantic typing, linked data |
| School: | Birkbeck Faculties and Schools > Faculty of Humanities and Social Sciences > School of Social Sciences |
| Research Centres and Institutes: | Data Analytics, Birkbeck Institute for |
| Depositing User: | Andrea Ballatore |
| Date Deposited: | 13 Mar 2017 14:51 |
| Last Modified: | 02 Aug 2023 17:31 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/18301 |
Statistics
Additional statistics are available via IRStats2.
Archive Staff Only (login required)
 |
Edit/View Item |