Open Science, Replicability, and Transparency in Modelling
Date
2021
Authors
Prike, T.
Editors
Bijak, J.
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Book chapter
Citation
Towards Bayesian Model-Based Demography Agency, Complexity and Uncertainty in Migration Studies, 2021 / Bijak, J. (ed./s), vol.17, Ch.10, pp.175-183
Statement of Responsibility
Toby Prike
Conference Name
Abstract
Recent years have seen large changes to research practices within psychology and a variety of other empirical fields in response to the discovery (or rediscovery) of the pervasiveness and potential impact of questionable research practices, coupled with well-publicised failures to replicate published findings. In response to this, and as part of a broader open science movement, a variety of changes to research practice have started to be implemented, such as publicly sharing data, analysis code, and study materials, as well as the preregistration of research questions, study designs, and analysis plans. This chapter outlines the relevance and applicability of these issues to computational modelling, highlighting the importance of good research practices for modelling endeavours, as well as the potential of provenance modelling standards, such as PROV, to help discover and minimise the extent to which modelling is impacted by unreliable research findings from other disciplines.
School/Discipline
Dissertation Note
Provenance
Description
Data source: Supplementary data, https://doi.org/10.1016/j.ejmp.2022.02.001
Access Status
Rights
© The Author(s) 2022. Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.