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Identifying Data Sharing in Biomedical Literature

Heather Piwowar¹ & Wendy W. Chapman¹

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1. University of Pittsburgh

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Document Type:

Manuscript

Date:

Received 25 March 2008 16:22 UTC; Posted 25 March 2008

Subjects:

Bioinformatics

Tags:

• natural language processing
• data sharing
• bioinformatics
• microarrays
• databases

Abstract:

Many policies and projects now encourage investigators to share their raw research data with other scientists. Unfortunately, it is difficult to measure the effectiveness of these initiatives because data can be shared in such a variety of mechanisms and locations. We propose a novel approach to finding shared datasets: using NLP techniques to identify declarations of dataset sharing within the full text of primary research articles. Using regular expression patterns and machine learning algorithms on open access biomedical literature, our system was able to identify 61% of articles with shared datasets with 80% precision. A simpler version of our classifier achieved higher recall (86%), though lower precision (49%). We believe our results demonstrate the feasibility of this approach and hope to inspire further study of dataset retrieval techniques and policy evaluation.

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License:

This document is licensed to the public under the Creative Commons Attribution 3.0 License

How to cite this document:

Piwowar, Heather and Chapman, Wendy. Identifying Data Sharing in Biomedical Literature. Available from Nature Precedings <http://hdl.handle.net/10101/npre.2008.1721.1> (2008)

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Other versions of this document in Nature Precedings

Version number	Document title	Date
v2	Posted 04 August 2008

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