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.
Highlights
Volume, velocity, variety, and value of data [1] are challenges for today’s spatial data and service infrastructures and for the generation of knowledge across themes and domains [2,3]
Data and geoprocessing web services are promoted as approaches to automating the development of spatial analysis workflows in order to derive information from data [4,5,6]
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]
Summary
Velocity, variety, and value of data [1] are challenges for today’s spatial data and service infrastructures and for the generation of knowledge across themes and domains [2,3]. Standard tools should be used for representing the knowledge, and the ways to generate the formalization should be documented to support contributions from the community [15,16] Under consideration of these claims, we analysed the requirements of pieces of information about geoprocessing operations during the workflow development process and conceptualized a knowledge base [17]. The demonstrator tool is implemented in Java and can translate user input into SPARQL queries (SPARQL Protocol And RDF Query Language, [18]), which retrieve information from the ontology These two developments are presented in this paper; they allow us to test the benefits of the proposed operation descriptions as well as the chosen representation of the knowledge in standard tools using OWL and SPARQL.
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