Question-Based Spatial Computing—A Case Study

Vahedi, Behzad; Kuhn, Walther; Ballatore, Andrea

doi:10.1007/978-3-319-33783-8_3

Cited by 21 publications

(43 citation statements)

References 10 publications

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“…The improvement of the workflow development process has been researched from various perspectives; including the translation of spatial questions into operations [28], semantic descriptions of spatial data in order to define which operations can be sensibly applied to the data [7,11], ontologies of domain knowledge that support the automated translation of a user task into operations [6], extended descriptions of geoprocessing operations [12,13,29], and verification of workflows before execution [14,30]. These approaches are discussed in the following section; extended operation descriptions are discussed in more detail in Section 2.2.…”

Section: Improved Workflow Developmentmentioning

confidence: 99%

Coupling Knowledge with GIS Operations: The Benefits of Extended Operation Descriptions

Hofer

Papadakis

Mäs

2017

IJGI

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Abstract:The automated development of spatial analysis workflows is one of the envisioned benefits of Web services that provide geoprocessing functionality. Automated workflow development requires the means to translate a user objective into a series of geographic information system (GIS) operations and to evaluate the match between data and operations. Even though full automation is yet out of reach, users benefit from formalized knowledge about operations that is available during workflow development. This article presents user support during workflow development based on a recent approach to extended operation descriptions. User support thereby focuses on the discovery of operations across GIS tools and the validation of chains of spatial analysis operations. The required knowledge about operations is stored in a knowledge base, which builds on an approach called geooperators and extends the geooperator approach with a data-type ontology for describing the interfaces of geooperators and for expressing constraints of geooperator inputs. The advantages of the knowledge base are demonstrated for the construction of a multi-criteria decision making workflow. This workflow contains a set of pre-processing tasks for the input datasets and eventually the calculation of a cost distance raster. A critical discussion of the complexity of the knowledge base and a comparison with existing approaches complement this contribution.

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Section: Improved Workflow Developmentmentioning

confidence: 99%

Coupling Knowledge with GIS Operations: The Benefits of Extended Operation Descriptions

Hofer

Papadakis

Mäs

2017

IJGI

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“…As Kuhn ( : 2267 notes, it is essential to rethink the fundamentals of spatial information while promoting clarity that cuts across technical boundaries and broadens spatial literacy for nonexperts. Contributing to the work by Kuhn and Ballatore (2015: 219) and Vahedi et al (2016) to design an intuitive GIS language for question-driven spatial studies, we focus on bridging the gaps between data discovery and spatial analysis tools by broadening the spectrum of exploitable spatial data sources. Compared to the vast amount of implicit spatial data (hidden location attributes often in the form of metadata, auxiliary place names, and geotagged attributes (Heinzle and Sester 2003: 335)), there remains a relatively limited quantity of online explicit spatial data (georeferenced geometry-based features (Brisaboa et al 2011: 358)).…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal enabled Content-based Image Retrieval

Belgiu¹,

Sudmanns²,

Tiede³

et al. 2016

GIScience

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Wireless Sensor Networks (WSNs) are widely used for monitoring and observation of dynamic phenomena. A sensor in WSNs covers only a limited region, depending on its sensing and communicating ranges, as well as the environment configuration. For efficient deployment of sensors in a WSN the coverage estimation is a critical issue. Probabilistic methods are among the most accurate models proposed for sensor coverage estimation. However, most of these methods are based on raster representation of the environment for coverage estimation which limits their quality. In this paper, we propose a probabilistic method for estimation of the coverage of a sensor network based on 3D vector representation of the environment.

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“…As Kuhn (2012Kuhn ( : 2267 notes, it is essential to rethink the fundamentals of spatial information while promoting clarity that cuts across technical boundaries and broadens spatial literacy for nonexperts. Contributing to the work by Kuhn and Ballatore (2015: 219) and Vahedi et al (2016) to design an intuitive GIS language for question-driven spatial studies, we focus on bridging the gaps between data discovery and spatial analysis tools by broadening the spectrum of exploitable spatial data sources.…”

Section: Introductionmentioning

confidence: 99%

“…When available, explicit data are typically served from a limited number of administrative portals or require intensive energy and time from a user searching, exporting, encoding and cleaning before being usable (Munson 2013: 65). These preprocessing requirements limit the feasibility of question-driven spatial analysis (Vahedi et al 2016) and force domain scientists to base their studies on data availability.…”

Section: Introductionmentioning

confidence: 99%

Deriving Locational Reference through Implicit Information Retrieval

Hervey¹,

Kühn²

2016

GIScience

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The often fragmented process of online spatial data retrieval remains a barrier to domain scientists interested in spatial analysis. Although there is a wealth of hidden spatial information online, scientists without prior experience querying web APIs (Application Programming Interface) or scraping web documents cannot extract this potentially valuable implicit information across a growing number of sources. In an attempt to broaden the spectrum of exploitable spatial data sources, this paper proposes an extensible, locational reference deriving model that shifts extraction and encoding logic from the user to a preprocessing mediation layer. To implement this, we develop a user interface that: collects data through web APIs and scrapers, determines locational reference as geometries, and re-encodes the data as explicit spatial information, usable with spatial analysis tools, such as those in R or ArcGIS.

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Question-Based Spatial Computing—A Case Study

Cited by 21 publications

References 10 publications

Coupling Knowledge with GIS Operations: The Benefits of Extended Operation Descriptions

Coupling Knowledge with GIS Operations: The Benefits of Extended Operation Descriptions

Spatiotemporal enabled Content-based Image Retrieval

Deriving Locational Reference through Implicit Information Retrieval

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