Paper details

Title: A method to produce metadata describing and assessing the quality of spatial landmark datasets in mountain area

Authors: Marie-Dominique Van Damme, Ana-Maria Olteanu-Raimond

Abstract: Obtained from CrossRef

Abstract. The increase of recreational activities in the mountains and a growing amount of websites proposing geographic data, offer new opportunities for societal needs such as mountain rescue, biodiversity monitoring, outdoor activities. However, the main issue with the websites data is the lack of metadata that minimizes its reuse outside the community that produced the data. The goal of this paper is to study and generate quality and descriptive metadata using ISO standards. To this end, we propose a method based on a common vocabulary such as an ontology and a data matching process. The first one allows to associate to each type of feature from an available geographic dataset an ontology class that will facilitate data matching, reproducibility of results and minimize semantic heterogeneity. The second one allows to define matching links between features representing the same entity in the real world and compute quality indicators based on the validated links. Finally, at the end of this process, we are able to generate descriptive and quality metadata. By following ISO standards and using the QualityML dictionary for measures, the metadata is serialized to XML and can finally be published as open source. Our approach was applied to five different landmark datasets in the French Alps region. New insights were acquired regarding positional accuracy and semantic granularity.

Codecheck details

Certificate identifier: 2022-014

Codechecker name: Philipp A. Friese

Time of codecheck: 2022-07-09 12:00:00

Repository: https://osf.io/6S2GP

Codecheck report: https://doi.org/10.17605/osf.io/6s2gp

Summary:

The software of the paper under reproduction is publicly available on GitHub. The data sets are publicly available in a zenodo project. Out of the four Figures and four Tables, two Figures and two Tables are eligible for reproduction. Both eligible Figures have been successfully reproduced. Both eligible Tables have been partially reproduced. The reproduction of Table 3 and 4 was partial as the provided software scripts comprise reproduction of one out of the four data columns. The remaining columns are expected to be reproducible after adjusting the scripts with references to the remaining data sets. The authors showed concern and dedication to improve reproducibility of their work. Reproduction was partially successful.

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© Stephen Eglen & Daniel Nüst

Published under CC BY-SA 4.0

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