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Sci Score a tool to support rigor and transparency guidelines

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R43OD024432-01
Agency Tracking Number: R43OD024432
Amount: $221,865.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: OD
Solicitation Number: PA14-154
Timeline
Solicitation Year: 2014
Award Year: 2017
Award Start Date (Proposal Award Date): 2017-08-03
Award End Date (Contract End Date): 2018-08-02
Small Business Information
4175 CAMINO ISLAY
San Diego, CA 92122-1810
United States
DUNS: 080111340
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 ANITA BANDROWSKI
 (650) 483-0697
 abandrowski@ucsd.edu
Business Contact
 ANITA BANDROWSKI
Phone: (650) 483-0697
Email: anita@scicrunch.com
Research Institution
N/A
Abstract

Project Summary
While standards in reporting of scientific methods are absolutely critical to producing reproducible science
meeting such standards is difficult Checklists and instructions are tough to follow often resulting in low and inconsistent compliance Scientific journals and societies as well as the National Institutes of Health are now actively proposing general guidelines to address reproducibility issues particularly in the reporting of methods
e g http www cell com star methods but the trickier part will be to train the biomedical community to use these standards to effectively improve how scientific methods are communicated
To support new standards in methods reporting specifically the RRID standard for Rigor and Transparency of
Key Biological Resources we propose to build Sci Score a text mining based tool suite to help authors meet the
standard Sci Score will provide an automated check on compliance with the RRID standard already
implemented by over journals including Cell Journal of Neuroscience and eLife The innovation behind Sci
score is the provision of a score which can be obtained by individual investigators which reflects a numerical
validation of the quality of their methods reporting We posit that the score will serve as a tool that investigators
and journals can use to compete with themselves and each other or in the very least allow them to see how
close they are to the average in meeting quality requirements
Recently our group has developed a text mining algorithm that has now been successfully been used to detect
software tools and databases from the SciCrunch Registry in published papers Digital tools are one of four
resource types that the RRID standard identifies We propose to extend this approach to the other types of
entities antibodies cell lines and model organisms Resource identification along with other quality metrics twill
be used to train an algorithm to score the overall quality of the methods document If successful the tool could
be used by editors reviewers and investigators to improve the number of RRIDs therefore the quality of
descriptors of key biological resources in published papers
This SBIR project will build a set of algorithms similar to the resource finding pipeline and develop it into an
industrial robust and reconfigurable software system Our Phase I specific aims include to creating gold sets
of data for each resource type and training a set of algorithms for each resource type designing and evaluating
the scoring system designing and evaluating a report generating system based on the previous aims In
Phase II we will develop a scalable backend infrastructure to serve the needs of scientific publishers and
research community Standards for scientific methods reporting are absolutely critical to producing reproducible science but meeting
such standards is difficult Checklists and instructions are tough to follow often resulting in low and inconsistent
compliance To support new standards in methods reporting specifically the RRID standard for Rigor and Transparency we propose to build Sci Score text mining based tool suite to help authors meet the standard Sci Score will provide an automated check on compliance with the RRID standard implemented by over journals including Cell Journal of Neuroscience and eLife Sci Score will provide a score rating the quality of
methods reporting in submitted articles which provides feedback to authors reviewers and editors on how to improvecompliance with RRIDs and other standards

* Information listed above is at the time of submission. *

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