Ten quick tips for editing Wikidata

Shafee, Thomas; Mietchen, Daniel; Lubiana, Tiago; Jemielniak, Dariusz; Waagmeester, Andra

doi:10.1371/journal.pcbi.1011235

Cited by 6 publications

(3 citation statements)

References 28 publications

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“…Also, as the project was a branch of T.L.’s Ph.D. work, done with J.V.F.C., an undergraduate student at the time, we chose the simpler Wikidata to have a straightforward, technically lighter framework. Wikidata makes it extremely easy to mint new identifiers for a scientific concept, by just clicking a few buttons on a web interface, without authorization systems or gatekeeping (Shafee et al, 2023).…”

Section: Discussionmentioning

confidence: 99%

Bringing PanglaoDB to 5-star Linked Open Data using Wikidata

Lubiana,

Cavalcante

2024

Preprint

Self Cite

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PanglaoDB is a database of cell-type markers widely used for single-cell RNA sequencing data analysis. However, cell types and genes in the database are encoded by free text, lacking proper identifiers. Wikidata, is a freely editable knowledge graph database useful for integrating biomedical knowledge. We thus reasoned that porting PanglaoDB's markers to the platform could improve their reusability and overall technical quality (FAIRness). We mapped 188 cell types from PanglaoDB to species-neutral terms on Wikidata and created 376 species-specific terms for cell types in Homo sapiens and Mus musculus. These terms were enriched with marker information via the has marker (P8872) property, totaling over 15.000 cell type X marker associations (w.wiki/9iw6). We explored this new subset of the graph via SPARQL queries, illustrating the discovery potential of structured, integrated knowledge. For example, we found a previously unexplored link between rosehip neurons, clozapine, and schizophrenia via the HRH1 marker. Besides the graph-based insights, we took time to describe the details of the reconciliation process, hoping to stimulate more resources for a move to a 5-star linked open data format.

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Section: Discussionmentioning

confidence: 99%

Bringing PanglaoDB to 5-star Linked Open Data using Wikidata

Lubiana,

Cavalcante

2024

Preprint

Self Cite

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“…Wikidata was the central hub for this project. Wikidata is an open, collaborative and multilingual knowledge base providing structured data that can be read and edited by humans and machines ( Vrandečić and Krötzsch 2014 , Shafee et al 2023 ). As a hub for other identifiers, it plays a central role in semantic linking and enriching of data (e.g.…”

Section: Sampling Methodsmentioning

confidence: 99%

Creating a multi-linked dynamic dataset: a case study of plant genera named for women

von Mering,

Gardiner,

Knapp

et al. 2023

BDJ

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A discussion on social media led to the formation of a multidisciplinary group working on this project to highlight women’s contributions to science. The role of marginalised groups in science has been a topic of much discussion, but data on these contributions are largely lacking. Our motivation for the development of this dataset was not only to highlight names of plant genera that honour women, but to enrich this information with data that would allow the names, roles and lives of these women to be shared more widely with others, both researchers and data sources like Wikidata. Amplification of the contributions of women to botany through multiple means will enable the community to better recognise and celebrate the role of this particular marginalised group in the history and development of science. The innovative approach of our study resulted in a dataset that is dynamic, expansive and widely shared. We have published a static dataset with this paper and have also created a dynamic dataset by linking flowering plant genera and the women in whose honour those genera were named in Wikidata. This concurrent addition of the data to Wikidata, a linked open data repository, enabled it to be enriched, queried and proactively shared during the whole process of dataset creation and into the future. This innovative workflow allowed wide, open participation throughout the research process. The methodology and workflows applied can be used to create future datasets celebrating and amplifying the contributions of marginalised groups in science.

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“…Record the access date in the reference with the property "retrieved" (P813), which will help future editors troubleshoot if the GBIF record changes again. See Shafee et al (2023) for guidance on editing Wikidata.…”

Section: ) Gbif Taxonid Has Been Deprecated or Mergedmentioning

confidence: 99%

Paying it forward: Crowdsourcing of taxonomic harmonization and linking of biodiversity identifiers

Seah

2023

Preprint

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Linking records for the same taxa between different databases is an essential step when working with biodiversity data. However, name-matching alone is error-prone, because of issues such as homonyms (unrelated taxa with the same name) and synonyms (same taxon under different names). Therefore, most projects will require some degree of curation to ensure that taxon identifiers are correctly linked. Unfortunately, formal guidance on such curation is uncommon, and these steps are often ad hoc and poorly documented, which hinders transparency and reproducibility, yet the task requires specialist knowledge and cannot be easily automated without careful validation. Here we present a case study on linking identifiers between the GBIF and NCBI taxonomies for a species checklist dataset. This represents a common usage scenario: finding publicly available sequencing data (available from NCBI) for species chosen by their occurrence or geographical distribution (from GBIF). Wikidata, a publicly editable knowledge base of structured data, can serve as an additional information source for identifier linking. We suggest a software toolkit for taxon name matching and data cleaning, describe common issues encountered during curation, and propose concrete steps to address them. For example, about 2.8% of the taxa in our dataset had wrong identifiers linked on Wikidata because of errors in name matching caused by homonyms. By correcting such errors during data cleaning, either directly (through editing Wikidata) or indirectly (by reporting errors in GBIF or NCBI), we crowdsource the curation and contribute to improvement of community resources, thereby improving the quality of downstream analyses.

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Ten quick tips for editing Wikidata

Cited by 6 publications

References 28 publications

Bringing PanglaoDB to 5-star Linked Open Data using Wikidata

Bringing PanglaoDB to 5-star Linked Open Data using Wikidata

Creating a multi-linked dynamic dataset: a case study of plant genera named for women

Paying it forward: Crowdsourcing of taxonomic harmonization and linking of biodiversity identifiers

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