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REUSABLE SOFTWARE PATTERNS FOR DATA COLLECTION SYSTEMS SUPPORTING LARGE-SCALE HUMAN SUBJECTS RESEARCH WITH SUBSTANTIAL REPORTING REQUIREMENTS

Jeffrey Brymer-Bashore

First published: 2015https://doi.org/10.5593/SGEMSOCIAL2015/B12/S3.110View metrics

Abstract

Managing data collection for any research project can be a time consuming task. It can quickly become overwhelming if you’re collecting data on thousands of human subjects and have additional requirements of reporting results at multiple levels of analysis and producing thousands of standardized reports for many research stakeholders. As a result, more time is spent managing data than using data; taking precious time away from research. My team at the International Data Evaluation Center has developed reusable software patterns to overcome these challenges, patterns that can be applied to different areas of research. We have been using them for 14+ years to manage data for Reading Recovery at The Ohio State University and have adapted them for other projects in the U.S. and abroad. To manage data collection for large-scale projects, we have used implementation of the following systems: registry Management System, Web-based Data Collection System, and High-Volume Reporting System. If implemented effectively, these systems allow many projects to be managed by a small team rather than an army of graduate assistants. This approach requires a large investment upfront, but pays huge dividends once implemented and allows researchers to focus on their passion: research.

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Title
REUSABLE SOFTWARE PATTERNS FOR DATA COLLECTION SYSTEMS SUPPORTING LARGE-SCALE HUMAN SUBJECTS RESEARCH WITH SUBSTANTIAL REPORTING REQUIREMENTS
Authors
Jeffrey Brymer-Bashore
Proceedings
Proceedings of 2nd International Multidisciplinary Scientific Conference on Social Sciences and Arts SGEM2015
Publisher
STEF92 Technology
Year
2015
Pages
849-862
SWS Citekey
Brymer-Bashore20153849862
ISSN
2367-5659
ISBN
978-619-7105-45-2
Language
en
Publication type
Proceedings Paper
Keywords
human-subjectsdata collectionstandardized reportingdata management
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