From Dirty Data to Tidy Facts: Clustering Practices in Plant Phenomics and Business Cycle Analysis
dc.contributor.author | Boumans, MJ | |
dc.contributor.author | Leonelli, S | |
dc.date.accessioned | 2020-01-07T10:49:26Z | |
dc.date.issued | 2020-06-30 | |
dc.description.abstract | This chapter considers and compares the ways in which two types of data, economic observations and phenotypic data in plant science, are prepared for use as evidence for claims about phenomena such as business cycles and gene-environment interactions. We focus on what we call “cleaning by clustering” procedures, and investigate the principles underpinning this kind of cleaning. These cases illustrate the epistemic significance of preparing data for use as evidence in both the social and natural sciences. At the same time, the comparison points to differences and similarities between data cleaning practices, which are grounded in the characteristics of the objects of interests as well as the conceptual commitments, community standards and research tools used by economics and plant science towards producing and validating claims. | en_GB |
dc.description.sponsorship | European Commission | en_GB |
dc.description.sponsorship | Alan Turing Institute | en_GB |
dc.description.sponsorship | Australian Research Council | en_GB |
dc.identifier.citation | In: Data Journeys in the Sciences, edited by Sabina Leonelli and Niccolò Tempini, pp. 79-101 | en_GB |
dc.identifier.doi | 10.1007/978-3-030-37177-7_5 | |
dc.identifier.uri | http://hdl.handle.net/10871/40283 | |
dc.language.iso | en | en_GB |
dc.publisher | Springer | en_GB |
dc.rights | © The Author(s) 2020. 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. | |
dc.subject | business cycle analysis | en_GB |
dc.subject | clustering | en_GB |
dc.subject | data cleaning | en_GB |
dc.subject | Mary Douglas | en_GB |
dc.subject | gestalt | en_GB |
dc.subject | plant phenomics | en_GB |
dc.title | From Dirty Data to Tidy Facts: Clustering Practices in Plant Phenomics and Business Cycle Analysis | en_GB |
dc.type | Book chapter | en_GB |
dc.date.available | 2020-01-07T10:49:26Z | |
dc.identifier.isbn | 978-3-030-37176-0 | |
dc.description | This is the final version. Available on open access from Springer via the DOI in this record | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
exeter.funder | ::European Commission | en_GB |
exeter.funder | ::Alan Turing Institute | en_GB |
exeter.funder | ::Australian Research Council | en_GB |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2019-08-01 | |
rioxxterms.type | Book chapter | en_GB |
refterms.dateFCD | 2020-01-07T10:46:17Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2020-09-10T13:29:49Z |
Files in this item
This item appears in the following Collection(s)
Except where otherwise noted, this item's licence is described as © The Author(s) 2020.
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.