115 research outputs found
In every grain of sand there is a world : an exhibition by Angie Seah
No full textExhibition catalogue : 08 October - 17 October 2014, Victoria College of the Arts, Melbourne, Australia.
Essay: Kyla McFarlane.
"This Asialinks Arts Residency Project is a collaboration between Asialink, the Art Incubator and Victorian College of the Arts and is supported by Arts Victoria.
monagrland/taxo-harmo: Curation of vascular plant species list for reference database
No full text<p>Methods case study on harmonization and linking of taxon names and biodiversity identifiers between public databases using name matching with Gndiff and Wikidata.</p>
<p>Initial release for Zenodo archiving.</p>
Paying it forward: Crowdsourcing the harmonisation and linking of taxon names and biodiversity identifiers
No full textLinking 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 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. This represents a common scenario: finding published sequence data (from NCBI) for species chosen by 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 community resources, thereby improving the quality of downstream analyses
kbseah/mitonotate: Mitonotate v1.0
No full text<p>Initial release for Zenodo archiving purposes.</p>
DOES MARKET CONCENTRATION OF INDUSTRIAL REITS IN A LOCALITY AFFECT MARKET RENTS?
No full textBachelor'sBACHELOR OF SCIENCE (REAL ESTATE
Swart-lab/loxodes-nucleosomes-workflow: Initial release for Zenodo archiving
No full textNo description provided
Swart-lab/bleties-test-tthe: Initial release for Zenodo archiving
No full textBenchmarking BleTIES with Tetrahymena long read dat
kbseah/mass2adduct: mass2adduct v1.0.0.0
No full text<p>Initial release of mass2adduct.</p>
Swart-lab/loxodes-srna-workflow: Initial release for Zenodo archiving
No full textsmall RNA library processing and analysi
Paying it forward: Crowdsourcing of taxonomic harmonization and linking of biodiversity identifiers [Preprint]
No full textLinking 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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