Integrations

Browser Add-ons

Google Chrome Google Chrome Extension

Bloodhound Attributor Google Chrome Extension modifies Global Biodiversity Information Facility (GBIF) occurrence pages to include links to ORCID accounts.

Firefox Firefox Add-on

Bloodhound Attributor Firefox Add-on modifies Global Biodiversity Information Facility (GBIF) occurrence pages to include links to ORCID accounts.

Web Services

Bloodhound data are exposed as CSV downloads or JSON-LD documents on publicly shared profile pages. Individual occurrence records are exposed as JSON-LD documents.

Occurrence Record
https://bloodhound-tracker.net/occurrence/477976412.json

Where /occurrence/477976412 is that provided by the Global Biodiversity Information Facility (GBIF), https://gbif.org/occurrence/477976412

Raw Data

List of Public Profiles
bloodhound-public-profiles.csv

Where the above csv includes a header, "Family, Given, wikidata, ORCID, URL"

All Claims from Public Profiles
Daily build, bloodhound-public-claims.csv.gz (7.59 MB)

Where the above gzipped csv includes a header, "Subject, Predicate, Object" and rows are expressed as, "https://gbif.org/occurrence/1801358422, http://rs.tdwg.org/dwc/iri/identifiedBy, https://orcid.org/0000-0001-9008-0611"

Unverified, Unauthenticated Agents
bloodhound-agents.gz (474 MB)

The above gzipped csv includes a header, "agents, gbifIDs_recordedBy, gbifIDs_identifiedBy", was constructed from https://doi.org/10.15468/dl.rohj3n using a Scala / Apache Spark script where the gbifIDs_recordedBy and gbifIDs_identifiedBy columns each contain an array of GBIF IDs. The "agents" column is as presented on GBIF and will require additional parsing.

Feeds

New Public Profiles
https://bloodhound-tracker.net/user.rss

RSS feed of new, public profiles.

Latest Comments on Profiles
https://bloodhound-tracker.disqus.com/latest.rss

RSS feed of all new comments (aka "Field notes") on profiles, provided by Disqus.

Code

The MIT-licensed code is available on GitHub. Technologies at play include Apache Spark to group occurrence records by raw entries in recordedBy and identifiedBy and to import into MySQL, Neo4j to store the scores between similarly structured people names, Elasticsearch to aid in the searching of people names once parsed and cleaned, Redis to coordinate the processing queues, and Sinatra/ruby for the application layer.