Reproducible Research in Geoinformatics: Concepts, Challenges and Benefits (Vision Paper)

Kray C, Pebesma E, Konkol M, Nüst D

Research article in edited proceedings (conference) | Peer reviewed

Abstract

Geoinformatics deals with spatial and temporal information and its analysis. Research in this field often follows established practices of first developing computational solutions for specific spatiotemporal problems and then publishing the results and insights in a (static) paper, e.g. as a PDF. Not every detail can be included in such a paper, and particularly, the complete set of computational steps are frequently left out. While this approach conveys key knowledge to other researchers it makes it difficult to effectively re-use and reproduce the reported results. In this vision paper, we propose an alternative approach to carry out and report research in Geoinformatics. It is based on (computational) reproducibility, promises to make re-use and reproduction more effective, and creates new opportunities for further research. We report on experiences with executable research compendia (ERCs) as alternatives to classic publications in Geoinformatics, and we discuss how ERCs combined with a supporting research infrastructure can transform how we do research in Geoinformatics. We point out which challenges this idea entails and what new research opportunities emerge, in particular for the COSIT community.

Details about the publication

PublisherTimpf S, Schlieder C, Kattenbeck M, Ludwig B, Stewart K
Book title14th International Conference on Spatial Information Theory (COSIT 2019)
Publishing companyDagstuhl Publishing
Place of publicationDagstuhl, Germany
Title of seriesLeibniz International Proceedings in Informatics (LIPIcs) (ISSN: 1868-8969)
Volume of series142
StatusPublished
Release year2019
Language in which the publication is writtenEnglish
Conference14th International Conference on Spatial Information Theory (COSIT 2019), Regensburg, Germany, undefined
ISBN978-3-95977-115-3
DOI10.4230/LIPIcs.COSIT.2019.8
Link to the full texthttp://drops.dagstuhl.de/opus/volltexte/2019/11100
Keywordsvision paper; Geoinformatics; reproducibility; computational; spatial and temporal information; spatial data science; GI Science

Authors from the University of Münster

Konkol, Markus
Professur für Geoinformatik (Prof. Kray)
Kray, Christian
Professur für Geoinformatik (Prof. Kray)
Nüst, Daniel
Professur für Geoinformatik (Prof. Pebesma)
Pebesma, Edzer
Professur für Geoinformatik (Prof. Pebesma)