2 Search Results for "Konkol, Markus"


Document
Reproducible Research and GIScience: An Evaluation Using GIScience Conference Papers

Authors: Frank O. Ostermann, Daniel Nüst, Carlos Granell, Barbara Hofer, and Markus Konkol

Published in: LIPIcs, Volume 208, 11th International Conference on Geographic Information Science (GIScience 2021) - Part II


Abstract
GIScience conference authors and researchers face the same computational reproducibility challenges as authors and researchers from other disciplines who use computers to analyse data. Here, to assess the reproducibility of GIScience research, we apply a rubric for assessing the reproducibility of 75 conference papers published at the GIScience conference series in the years 2012-2018. Since the rubric and process were previously applied to the publications of the AGILE conference series, this paper itself is an attempt to replicate that analysis, however going beyond the previous work by evaluating and discussing proposed measures to improve reproducibility in the specific context of the GIScience conference series. The results of the GIScience paper assessment are in line with previous findings: although descriptions of workflows and the inclusion of the data and software suffice to explain the presented work, in most published papers they do not allow a third party to reproduce the results and findings with a reasonable effort. We summarise and adapt previous recommendations for improving this situation and propose the GIScience community to start a broad discussion on the reusability, quality, and openness of its research. Further, we critically reflect on the process of assessing paper reproducibility, and provide suggestions for improving future assessments. The code and data for this article are published at https://doi.org/10.5281/zenodo.4032875.

Cite as

Frank O. Ostermann, Daniel Nüst, Carlos Granell, Barbara Hofer, and Markus Konkol. Reproducible Research and GIScience: An Evaluation Using GIScience Conference Papers. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part II. Leibniz International Proceedings in Informatics (LIPIcs), Volume 208, pp. 2:1-2:16, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2021)


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@InProceedings{ostermann_et_al:LIPIcs.GIScience.2021.II.2,
  author =	{Ostermann, Frank O. and N\"{u}st, Daniel and Granell, Carlos and Hofer, Barbara and Konkol, Markus},
  title =	{{Reproducible Research and GIScience: An Evaluation Using GIScience Conference Papers}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part II},
  pages =	{2:1--2:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-208-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{208},
  editor =	{Janowicz, Krzysztof and Verstegen, Judith A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.II.2},
  URN =		{urn:nbn:de:0030-drops-147615},
  doi =		{10.4230/LIPIcs.GIScience.2021.II.2},
  annote =	{Keywords: reproducible research, open science, reproducibility, GIScience}
}
Document
Vision Paper
Reproducible Research in Geoinformatics: Concepts, Challenges and Benefits (Vision Paper)

Authors: Christian Kray, Edzer Pebesma, Markus Konkol, and Daniel Nüst

Published in: LIPIcs, Volume 142, 14th International Conference on Spatial Information Theory (COSIT 2019)


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.

Cite as

Christian Kray, Edzer Pebesma, Markus Konkol, and Daniel Nüst. Reproducible Research in Geoinformatics: Concepts, Challenges and Benefits (Vision Paper). In 14th International Conference on Spatial Information Theory (COSIT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 142, pp. 8:1-8:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


Copy BibTex To Clipboard

@InProceedings{kray_et_al:LIPIcs.COSIT.2019.8,
  author =	{Kray, Christian and Pebesma, Edzer and Konkol, Markus and N\"{u}st, Daniel},
  title =	{{Reproducible Research in Geoinformatics: Concepts, Challenges and Benefits}},
  booktitle =	{14th International Conference on Spatial Information Theory (COSIT 2019)},
  pages =	{8:1--8:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-115-3},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{142},
  editor =	{Timpf, Sabine and Schlieder, Christoph and Kattenbeck, Markus and Ludwig, Bernd and Stewart, Kathleen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2019.8},
  URN =		{urn:nbn:de:0030-drops-111008},
  doi =		{10.4230/LIPIcs.COSIT.2019.8},
  annote =	{Keywords: vision paper, Geoinformatics, reproducibility, computational, spatial and temporal information, spatial data science, GI Science}
}
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