GBIF dataset metrics

Get insights in GBIF-mediated datasets with charts and metrics.

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GBIF Dataset Metrics

GBIF Dataset Metrics is a Google Chrome extension that provides aggregated occurrence metrics for GBIF-mediated datasets. It includes stacked bar charts, interactive taxonomy partitions, sample images, and downloads charts to help users quickly assess the fitness for use of a dataset.

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Extension stats

By: Datafable

Users: 83

Rating: 5.00

(6)

Version: 0.2.1 (Last updated: 2015-08-31)

Creation date: 2015-08-31

Risk impact: Low risk impact

Risk likelihood:

Low risk likelihood

Manifest version: 2

Permissions:

http://*.gbif.org/
http://datafable.cartodb.com/

Size: 190.46K

Ranking

# 75,292 ▲ 522

Other rankings

#30794 in Workflow & Planning ▲ 32 #215 in chart keyword 11 ▲ 3

Other platforms

Not available on Android

Not available on Firefox

Not available on Edge

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Extension summary

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The Global Biodiversity Information Facility (GBIF) facilitates access to over 13,233 species occurrence datasets, collectively holding more than 570 million records. GBIF dataset pages are important access points to GBIF-mediated data (e.g. via DOIs) and currently show dataset metadata, a map of georeferenced occurrences, some basic statistics, and a paged table of download events. If a user wants to know more about the occurrences a dataset contains, he/she has to filter/page through a table of occurrences or download the data. Neither are convenient ways to get quick insights or assess the fitness for use.

For the 2015 GBIF Ebbe Nielsen challenge, we have developed this Google Chrome extension as proof of concept for enhancing GBIF dataset pages with aggregated occurrence metrics. These metrics are visualized as stacked bar charts - showing the occurrence distribution for basis of record, coordinates, multimedia, and taxa matched with the GBIF backbone - as well as an interactive taxonomy partition, a sample of images (if available), and a downloads chart. Metrics that score particularly well are highlighted as achievements. Collectively these features not only inform the user what a dataset contains and if it is fit for use, but also help data publishers discover what aspects could be improved.

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