Scheider, S. and Ballatore, Andrea and Lemmens, R. (2018) Finding and sharing GIS methods based on the questions they answer. International Journal of Digital Earth 12 (5), pp. 594-613. ISSN 1753-8947.
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Abstract
Geographic information has become central for data scientists of many disciplines to put their analyses into a spatio-temporal perspective. However, just as the volume and variety of data sources on the Web grow, it becomes increasingly harder for analysts to be familiar with all the available geospatial tools, including toolboxes in Geographic Information Systems (GIS), R packages, and Python modules. Even though the semantics of the questions answered by these tools can be broadly shared, tools and data sources are still divided by syntax and platform-specific technicalities. It would, therefore, be hugely beneficial for information science if analysts could simply ask questions in generic and familiar terms to obtain the tools and data necessary to answer them. In this article, we systematically investigate the analytic questions that lie behind a range of common GIS tools, and we propose a semantic framework to match analytic questions and tools that are capable of answering them. To support the matching process, we define a tractable subset of SPARQL, the query language of the Semantic Web, and we propose and test an algorithm for computing query containment. We illustrate the identification of tools to answer user questions on a set of common user requests.
Metadata
| Item Type: | Article |
|---|---|
| Additional Information: | This is an Accepted Manuscript of an article published by Taylor & Francis, available online at the link above. |
| Keyword(s) / Subject(s): | Question answering, GIS methods, SPARQL, Semantic workflows, Query containment |
| 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: | 26 Apr 2018 09:33 |
| Last Modified: | 02 Aug 2023 17:41 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/22231 |
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