Beyond Data Capture: Using REDCap™ to Facilitate Web-Based Therapeutic Intervention Research

Background Limited guidelines to assist nurse researchers who use web-based interventions are available. Nurses must develop the supporting technology enabling participants to complete study activities and collected data while maintaining data security and participant confidentiality. Objectives To describe how the authors used advanced Research Electronic Data Capture (REDCapTM) functionality to support the data management infrastructure of an interactive, web-based therapeutic intervention. Methods The data management infrastructure for the WISER intervention pilot study consisted of two components: a website for presentation of the intervention and participant account management and a REDCap project for data capture and storage. REDCap application programming interface (API) connected these two components using HTML links and data exchanges. Results We completed an initial pilot study of WISER with 14 participants using the REDCap-based infrastructure. Minimal technical difficulties were encountered. Discussion REDCap is cost-effective, readily available, and through its advanced functionality is able to facilitate confidential, secure interactions with participants, robust data management, and seamless participant progression in web-based intervention research

Results of 2013 Survey of Parallel Computing Needs Focusing on NSF-funded Researchers

The field of supercomputing is experiencing a rapid change in system structure, programming models, and software environments in response to advances in application requirements and in underlying enabling technologies. Traditional parallel programming approaches have relied on static resource allocation and task scheduling through programming interfaces such as MPI and OpenMP. These methods are reaching their efficiency and scalability limits on the new emerging classes of systems, spurring the creation of innovative dynamic strategies and software tools, including advanced runtime system software and programming interfaces that use them. To accelerate adoption of these next-generation methods, Indiana University is investigating the creation of a single supported Reconfigurable Execution Framework Testbed (REFT) to be used by parallel application algorithm developers as well as researchers in advanced tools for parallel computing. These investigations are funded by the National Science Foundation Award Number 1205518 to Indiana University with Thomas Sterling as Principal Investigator, and Maciej Brodowicz, Matthew R. Link, Andrew Lumsdaine, and Craig Stewart as Co-Principal Investigators. As a starting point in this research we proposed to assess needs in parallel computing in general and needs for software tools and testbeds in particular within the NSF-funded research community. As one set of data toward understanding these needs, we conducted a survey of researchers funded by the National Science Foundation. Because of the strong possibility of distinct needs of researchers funded by what is now the Division of Advanced Cyberinfrastructure, researchers funded by the other divisions of the Computer and Information Sciences and Engineering Directorate, and researchers funded by the remainder of the NSF, we surveyed these populations separately. The report states the methods and summarize survey results. The data sets and copies of SPSS descriptive statistics describing the data are available online at http://hdl.handle.net/2022/19924.National Science Foundation Award Number 120551

2003 Report on Indiana University Accomplishments supported by Shared University Research Grants from IBM, Inc.

Indiana University and IBM, Inc. have a very strong history of collaborative research, aided significantly by Shared University Research (SUR) grants from IBM to Indiana University. The purpose of this document is to review progress against recent SUR grants to Indiana University. These grants focus on the joint interests of IBM, Inc. and Indiana University in the areas of deep computing, grid computing, and especially computing for the life sciences. SUR funding and significant funding from other sources, including a $1.8M grant from the NSF and a portion of a$105M grant to Indiana University to create the Indiana Genomics Initiative, have enabled Indiana University to achieve a suite of accomplishments that exceed the ambitious goals set out in these recent SUR grants

Indiana University's Advanced Cyberinfrastructure

This is an archived document. The most current version may be found at http://pti.iu.edu/ciThe purpose of this document is to introduce researchers to Indiana University’s cyberinfrastructure – to clarify what these facilities make possible, to discuss how to use them and the professional staff available to work with you. The resources described here are complex and varied, among the most advanced in the world. The intended audience is anyone unfamiliar with IU’s cyberinfrastructure

Implementation of a Distributed Architecture for Managing Collection and Dissemination of Data for Fetal Alcohol Spectrum Disorder

We implemented a distributed system for management of data for an international collaboration studying Fetal Alcohol Spectrum Disorders (FASD). Subject privacy was protected, researchers without dependable Internet access were accommodated, and researchers’ data were shared globally. Data dictionaries codified the nature of the data being integrated, data compliance was assured through multiple consistency checks, and recovery systems provided a secure, robust, persistent repository. The system enabled new types of science to be done, using distributed technologies that are expedient for current needs while taking useful steps towards integrating the system in a future grid-based cyberinfrastructure. The distributed architecture, verification steps, and data dictionaries suggest general strategies for researchers involved in collaborative studies, particularly where data must be de-identified before being shared. The system met both the collaboration’s needs and the NIH Roadmap’s goal of wide access to databases that are robust and adaptable to researchers’ needs

Implementation of a Shared Data Repository and Common Data Dictionary for Fetal Alcohol Spectrum Disorders Research

Many previous attempts by fetal alcohol spectrum disorders researchers to compare data across multiple prospective and retrospective human studies have failed due to both structural differences in the collected data as well as difficulty in coming to agreement on the precise meaning of the terminology used to describe the collected data. Although some groups of researchers have an established track record of successfully integrating data, attempts to integrate data more broadly amongst different groups of researchers have generally faltered. Lack of tools to help researchers share and integrate data has also hampered data analysis. This situation has delayed improving diagnosis, intervention, and treatment before and after birth. We worked with various researchers and research programs in the Collaborative Initiative on Fetal Alcohol Spectrum Disorders (CI-FASD) to develop a set of common data dictionaries to describe the data to be collected, including definitions of terms and specification of allowable values. The resulting data dictionaries were the basis for creating a central data repository (CI-FASD Central Repository) and software tools to input and query data. Data entry restrictions ensure that only data which conform to the data dictionaries reach the CI-FASD Central Repository. The result is an effective system for centralized and unified management of the data collected and analyzed by the initiative, including a secure, long-term data repository. CI-FASD researchers are able to integrate and analyze data of different types, collected using multiple methods, and collected from multiple populations, and data are retained for future reuse in a secure, robust repository

PHPCap and Software patterns for the College Toolbox Project

Presented to the REDCap Consortium weekly meeting on Nov 13, 2015.Indiana University has been selected by Glenn Close and her non-profit organization, U Bring Change 2 Mind, to be the national site to create a 'toolbox' of activities and events, designed by students for students to end the stigma that people with mental illness often face, and to make college campuses safer and more welcoming places. 7,000 freshman at IU Bloomington were invited to participate: Initial survey, Swag pickup, Events, and Follow-up surveys. We developed multiple applications that use multiple REDCap projects to meet the College Toolbox Project needs, and used a newly created, publicly available software library, PHPCap to make development faster and easier

The centralized life science data service at Indiana University

Presented at IBM solutions seminar, 2-3 March 2004, Bethesda, MD.This research was supported in part by the Indiana Genomics Initiative. The Indiana Genomics Initiative of Indiana University is supported in part by Lilly Endowment Inc. This work was supported in part by Shared University Research grants from IBM, Inc. to Indiana University, and in particular by IU’s relationship with IBM as an IBM Life Sciences Institute of Innovation. This material is based upon work supported by the National Science Foundation under Grant No. 0116050 and Grant No. CDA-9601632. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF). Informatics E-mail server supported in part by the 21st Century Research & Technology Fund Online Biological Retrieval Data system supported in part by National Institutes of Health R01 NS3716

Open source tools for computational biology

Tutorial presented at IEEE/ACM SC04 Conference, 6-12 Nov 2005, Pittsburgh, PA

REDCap: Easy creation of data management systems, plus a lot more

Presented at the IU Statewide IT Conference, 24-Sep-2012REDCap (Research Electronic Data Capture) provides easy-to-use methods for non-programmers to quickly create a web-based data management system. Project owners use GUI- and spreadsheet-driven functionality that allows one to create a complete project in minutes. Projects have access to a wealth of functionality: Branching logic, calculated fields, and data validity checks during data entry; a survey component for data entry done by non data managers; data import, reporting and export tools; simple online analysis views; and a complete audit log. REDCap can also do much more: Help with scheduling patient visits; support multi-institution projects through data access groups; enhance data quality through double data entry and data checking; protect electronic protected health information (ePHI) by protecting identifiers throughout the system; interoperate with other systems through an Application Programmer Interface (API), and just about anything else through a plugin architecture and custom code. REDCap was developed by and is actively maintained by Vanderbilt University (http://www.project-redcap.org). It is in use by more than three hundred institutions worldwide, including the Indiana Clinical and Translational Sciences Institute (Indiana CTSI), which makes REDCap available to all partner institutions. Within the Indiana CTSI, REDCap has more than 520 active users working in more than 290 active projects, primarily on the IUPUI campus. REDCap is available for little or no cost to all Indiana University faculty and staff and is an excellent tool for leveraging shared resources for increased efficiency.This material is based upon work supported by the NIH under the Clinical & Translational Science Awards (http://www.ncats.nih.gov/research/cts/ctsa/ctsa.html)