Procedural metadata for geographic information using an algebra of core concept transformations
DOI:
https://doi.org/10.5311/JOSIS.2023.27.268Keywords:
core concepts, geographic information, workflows, transformations, type inference, semantic webAbstract
Transformations are essential for dealing with geographic information. They are involved not only in the conversion between geodata formats and reference systems, but also in turning geodata into useful information according to some purpose. However, since a transformation can be implemented in various formats and tools, its function and purpose usually remains hidden underneath the technicalities of a workflow. To automate geographic information procedures, we therefore need to model the transformations implemented by workflows on a conceptual level, as a form of procedural knowledge. Although core concepts of spatial information provide a useful level of description in this respect, we currently lack a model for the space of possible transformations between such concepts. In this article, we present the algebra of core concept transformations (CCT). It consists of a type hierarchy which models core concepts as relation types, and a set of basic transformations described in terms of function signatures that use such types. We enrich GIS workflows with abstract machine-readable metadata, by compiling algebraic tool descriptions and inferring goal concepts across a workflow. In this article, we show how such procedural metadata can be used to retrieve workflows based on task descriptions derived from geo-analytical questions. Transformations can be queried independently from their implementations or data formats.
![268](http://josis.net/public/journals/1/submission_268_276_coverImage_en_US.png)
Downloads
Published
Issue
Section
License
Copyright (c) 2023 Niels Steenbergen, Eric Top, Enkhbold Nyamsuren, Simon Scheider
![Creative Commons License](http://i.creativecommons.org/l/by/3.0/88x31.png)
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
Articles in JOSIS are licensed under a Creative Commons Attribution 3.0 License.