Difference between revisions of "SOCR HTML5 InteractivePubsMappingProject"
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| − | The goal of this project is to design a new dynamic visualization tool that provides an interactive mechanism for traversing, exploring, mapping, parsing and viewing SOCR Publications. The meta-data about SOCR publications will be automatically retrieved from [http://www.ncbi.nlm.nih.gov/pmc/?term=socr PMC] | + | The goal of this project is to design a new dynamic visualization tool that provides an interactive mechanism for traversing, exploring, mapping, parsing and viewing SOCR Publications. The meta-data about SOCR publications will be automatically retrieved from [http://www.ncbi.nlm.nih.gov/pmc/?term=socr PMC], or [http://scholar.google.com/scholar?hl=en&as_sdt=0,5&q=%22statistics+online+computational+resource%22 Scholar], and the HTML interface will be platform- and browser-independent, implemented using [http://en.wikipedia.org/wiki/HTML5 HTML5]/[http://en.wikipedia.org/wiki/JavaScript JavaScript]/[http://jquery.com/ JQuery] technologies. |
===Project Description=== | ===Project Description=== | ||
Revision as of 17:19, 18 October 2012
Contents
SOCR Project - SOCR Interactive Publications Mapping Project
Project goals
The goal of this project is to design a new dynamic visualization tool that provides an interactive mechanism for traversing, exploring, mapping, parsing and viewing SOCR Publications. The meta-data about SOCR publications will be automatically retrieved from PMC, or Scholar, and the HTML interface will be platform- and browser-independent, implemented using HTML5/JavaScript/JQuery technologies.
Project Description
- Review the listings of the SOCR Pubs1, Pubs2, PMC and Scholar publications.
- Design a method to automatically retrieve the SOCR Publications, parse the authors, titles, years, journals and URLs. Note that only PMC provides an API for machine consumption of publications meta-data. Start with the PMC API first].
- Review the D3 framework and its many examples.
- See this Publications mapping example. Note that this demonstration uses a Django app back-end, which makes it impractical for our use. This webapp needs to run on the client machine.
- Demonstrate you can pull publications meta-data (from PMC) using "SOCR" or "statistics online computational resource" phrases.
- then demonstrate you can parse the publication citation meta-data (e.g., author(s), year, journal, URL, etc.)
- Design a clever mapping UI that allows the user to interactively search, filter, group, sort, view pubs by year, (co)author, journal, topic, etc.
- Make sure this infrastructure can be easily extended for any other project.
See also
- A publications mapping example and it's sparse documentation.
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