The weekend of November 12, PLoS sponsored Science Hack Day (SF), an annual event bringing together up to 200 scientists (and citizen scientists), designers, and coders for a ”brief but intense period of collaboration, hacking, and building ‘cool stuff’“.
Several teams utitilized the PLoS APIs in order to run some interesting experiments:
- Science and Gender: This app mashes up the PLoS Solr API and other sources to test if one can “predict gender, with a reasonable margin of error, based only on author names found in articles published by PLoS.”
- SciSentiment: This app uses text analysis (facilitated by the PLoS Solr API, the PLoS ALM API, and the Mendeley API) to see if a prediction can be made for future citations. (You can view some of the preliminary results here, here, and here.)
- Subjects: This data visualization tool, created by PLoS dev team members Jen Song and Joe Osowski, uses the PLoS Solr API and the D3.js tool to create beautiful graphics that show relationships between subject areas assigned to PLoS papers. Here are a couple of the resulting visualizations (click to enlarge):
We’d like to thank Joe Osowski, Jen Song, and Alex Kudlick, the PLoS devs who attended, created, and supported some great hacks, as well as our friends William Gunn and Matt Senate, who were heavily involved in the PLoS-centric projects. Also, many thanks to Ariel Waldman and the rest of the Science Hack Day organizers for including us in their event!
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