ArticleZooKeys2018
An audit of some processing effects in aggregated occurrence records.
Article in ZooKeys, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- FAIRness at all costs? Practical limitations in applying the FAIR principles to plant genetic resources data.Frontiers in plant science · 2026Article
- Pytaxon: A Python software for resolving and correcting taxonomic names in biodiversity data.Biodiversity data journal · 2025Article
- A new R package to parse plant species occurrence records into unique collection events efficiently reduces data redundancy.Scientific reports · 2024Article
- Unified and pluralistic ideals for data sharing and reuse in biodiversity.Database : the journal of biological databases and curation · 2023Article
- Open Data Practices among Users of Primary Biodiversity Data.Bioscience · 2021Article
- The Atlas of Living Australia: History, current state and future directions.Biodiversity data journal · 2021Article
- Decentralized but Globally Coordinated Biodiversity Data.Frontiers in big data · 2020Article
- Connecting data and expertise: a new alliance for biodiversity knowledge.Biodiversity data journal · 2019Article
- An updated checklist of the Tenebrionidae sec. Bousquet et al. 2018 of the Algodones Dunes of California, with comments on checklist data practices.Biodiversity data journal · 2018Article
- Data Leakage and Loss in Biodiversity Informatics.Biodiversity data journal · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A total of ca 800,000 occurrence records from the Australian Museum (AM), Museums Victoria (MV) and the New Zealand Arthropod Collection (NZAC) were audited for changes in selected Darwin Core fields after processing by the Atlas of Living Australia (ALA; for AM and MV records) and the Global Biodiversity Information Facility (GBIF; for AM, MV and NZAC records). Formal taxon names in the genus- and species-groups were changed in 13-21% of AM and MV records, depending on dataset and aggregator. There was little agreement between the two aggregators on processed names, with names changed in two to three times as many records by one aggregator alone compared to records with names changed by both aggregators. The type status of specimen records did not change with name changes, resulting in confusion as to the name with which a type was associated. Data losses of up to 100% were found after processing in some fields, apparently due to programming errors. The taxonomic usefulness of occurrence records could be improved if aggregators included both original and the processed taxonomic data items for each record. It is recommended that end-users check original and processed records for data loss and name replacements after processing by aggregators.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.