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Wednesday, October 24, 2012

Webinar on Text Mining

The Center for Research Libraries is hosting a webinar on text-mining in a few weeks.  It will explore trends in text mining and how publishers and libraries are responding to the challenges that come with it.  Topics to be addressed (from the announcement):
  • the types of resources being “mined”, including e-journal databases and digitized newspapers and archives
  • recent text-mining projects
  • the challenges and issues these present for database publishers
  • what role, if any, libraries can play to support these activities
  • what new services are envisioned and what is in the pipeline
The webinar will take place online Tuesday, Nov. 13th 11a - 12:30p Pacific Time.  You can register here (may need to sign up for free account first):

Friday, October 5, 2012

Special Report About Missing Data in Clinical Trials

New England Journal of Medicine just released a special report titled "The Prevention and Treatment of Missing Data in Clinical Trials".  The research indicated that trial design, flexible treatment regimens, better follow-up and use of more scientific methods to adjust for missing data could improve results for clinical trials.

To read a review of the article: 

Here's the citation for the original study: N Engl J Med 2012; 367:1355-1360; October 4, 2012 DOI: 10.1056/NEJMsr1203730
UW subscribes to NEJM and you can access the study from a campus computer or through the Libraries proxy server.

(Thanks, Cynthia)

Thursday, October 4, 2012

New Tool to Help Manage Data: DataUp

Microsoft announced the release of a new open-source tool to help researchers "document, manage and archive" tabular data.  Best part is that it can be used as a web app or as an add-in for Microsoft Excel.

Per the release, whether you go for the Excel extension or the online app, DataUp can help you with four main tasks:
  1. Perform a best-practices check to ensure good data organization
  2. Guide users through creation of metadata for their Excel file
  3. Help users obtain a unique identifier for their dataset
  4. Connect users to a major repository, where their data can be deposited and shared with others
Read more about the tool and check it out for yourself here: