Martin Graham
Vesper: Visualising species archives
Graham, Martin; Kennedy, Jessie
Abstract
Vesper (Visual Exploration of SPEcies-referenced Repositories) is a tool that visualises Darwin Core Archive (DwC-A) datasets, and is aimed at reducing the amount of time and effort expended by biologists to ascertain the quality of data they are generating or using. Currently, DwC-A quality checking is limited to table outputs of data ‘existence’ and compliance with DwC-A format guidelines via the online DwC-A archive validator and reader. While these tools thoroughly examine the presence of data, and the correctness of data structure against the DwC-A schema, they do not give any insight into the underlying quality of the data itself.
Built on top of the D3 JavaScript library, Vesper analyses and displays DwC-A datasets in three fundamental dimensions - taxonomic, geographic and temporal - with a visualisation dedicated to each of these aspects of the data. By viewing a dataset’s composition in these dimensions, a data consumer can judge whether it is suitable for the tasks or analyses they have in mind, while a data provider can identify where a dataset they’ve constructed may fall short in terms of data quality i.e. does it contains data that is obviously incorrect such as the classic longitude inversion that places North American specimens in China. A further visualisation of the taxonomic dimension can reveal the subtaxa distribution of reference taxonomies - while a simple table reveals the presence or not of certain data types for each record to give an overall data ‘existence’ profile for the dataset. Selections of parts of a dataset within one visualisation are linked to the other visualisation displays for that dataset, permitting the discovery of whether data quality issues are restricted to identifiable sub-portions of the dataset.
Vesper can handle client-side data sets of a million entities within a browser by judicious use of data filtering, as many of the data types within individual records are not necessary to judge the geographic, temporal or taxonomic distribution and extent of a dataset. Thus, many of the more verbose fields in the file can simply be passed over during an initial data decompression stage. Furthermore it can provide limited name and structure matching of a dataset against DwC-A packaged reference taxonomies to indicate data quality relative to sources outside the archive. A selection of annotated example scenarios shows how Vesper can reveal data quality issues in DwC-A archives.
Citation
Graham, M., & Kennedy, J. (2014). Vesper: Visualising species archives. Ecological Informatics, 24, 132-147. https://doi.org/10.1016/j.ecoinf.2014.08.004
Journal Article Type | Article |
---|---|
Acceptance Date | Aug 17, 2014 |
Online Publication Date | Aug 30, 2014 |
Publication Date | 2014-11 |
Deposit Date | Sep 2, 2014 |
Publicly Available Date | Sep 2, 2014 |
Print ISSN | 1574-9541 |
Electronic ISSN | 1878-0512 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 24 |
Pages | 132-147 |
DOI | https://doi.org/10.1016/j.ecoinf.2014.08.004 |
Keywords | Information Visualisation, Data Quality, Darwin Core Archive, Open Source, Biodiversity |
Public URL | http://researchrepository.napier.ac.uk/id/eprint/7129 |
Files
Vesper: Visualising species archives
(4.2 Mb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by-nc-nd/4.0/
You might also like
BayesPiles: Visualisation Support for Bayesian Network Structure Learning
(2018)
Journal Article
A Task Taxonomy for Temporal Graph Visualisation
(2015)
Journal Article
Temporal Multivariate Networks.
(2014)
Book Chapter
Visualization beyond the desktop--the Next Big Thing.
(2014)
Journal Article
Helium: visualization of large scale plant pedigrees
(2014)
Journal Article
Downloadable Citations
About Edinburgh Napier Research Repository
Administrator e-mail: repository@napier.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search