Hypertext Rapid Application Framework (HTRAF): An innovative application-development layer enables rapid delivery of web applications for autism research and autism funding decisions

<p>Despite tremendous progress in web-development technologies, building custom data-driven web applications remains out of reach for most research programs. Application development costs too much, takes too long, and requires too many technical skills. A technology platform that significantly speeds and simplifies development would bridge the gap between limited budgets and capabilities and researchers’ need for powerful web tools for interacting with data.</p

RexMart: Empowering Analysts to Configure Research Data Marts to Improve End-User Data Exploration

<p>We set out to build a powerful configuration layer for semi-technical analysts and end users on top of relational database technology. This configuration layer empowers data analysts to define data feeds and transformations, data mart schemas, as well as query builder display properties. A data exploration tool that can readily be configured by both analysts and end-users is more likely to meet users’ needs at a lower cost than fully custom software while providing greater data quality and auditability than spreadsheets.</p

HTRAF and HTSQL: New Open-Source Tools Enabling the Rapid Development of Data-Driven Web Dashboards for Clinical and Research Staff

<p>We developed and used two open-source tools, the HyperText Rapid Application Framework (HTRAF) and HyperText Structured Query Language (HTSQL), to rapidly create four custom dashboards for an observational study.</p> <p> </p> <p>We gathered initial requirements, created mock-ups and solicited two rounds of feedback from four users: Clinician, Research Assistant, Clinic Coordinator, and Intake Coordinator.</p> <p> </p> <p>Prototypes were developed in one day, fully functional dashboards in five days. Developers were able to modify dashboards within hours.  Qualitative feedback from users revealed that they liked the dashboards and found them easy to use.</p

RexAcquire: A Configurable, Open-Source Data Acquisition Platform for Integrated Autism Data Management Environments

<p>The collaborative, multidisciplinary, and often longitudinal nature of autism research requires a data acquisition platform that is secure, scalable, extensible, and reusable across multiple studies and domains. We evaluated existing systems and found that none fit the needs of complex interdisciplinary or translational projects. No existing platform offered the combination of features that included interactive, user-driven configuration; open-source licensing; and thoughtful support for integrated data management across studies, data types, and sites. To address this deficit we packaged and open-sourced the Research Exchange and Acquisition Platform (RexAcquire), a secure Electronic Data Capture (EDC) system with integrated data management features.</p> <p> </p> <p> </p

RexMart: An Open Source Tool for Exploring and Sharing Research Data without Compromising Data Integrity

<p>Behavioral and biomedical researchers value data integrity, data exploration, and data sharing, but traditional research databases have unacceptable trade-offs among these important data management functions. This case study examines the design, development, and evaluation of RexMart, an open-source application designed to optimize data integrity, exploration, and sharing with easily accessible querying tools including the powerful query language HTSQL.</p

An Open Source, Integrated Data Management System for Medical Registries: A Case Study using RexDB (Informatics to Support Clinical Trials)

<p>Disease- and procedure-specific registries are powerful tools for the improvement of long-term patient care. Unfortunately, registries are typically too expensive for smaller practices and organizations to develop and maintain. This case study examines an affordable and scalable alternative, RexDB®, an open-source solution that can integrate institutional (EHR) and primary research data.</p

The Reusable Online Assessment Data Service (ROADS): A Lightweight, Extensible, Open-Source Tool for Configuring and Administering Secure Clinical Data Assessments on the Web

<p>The Reusable Online Assessment Data Service (ROADS) is a lightweight and secure tool for publishing complex clinical assessments on the web and for collecting data from several different sources, including self-administered questionnaires from study participants and paper form data collected with dual data entry verification. ROADS makes it simple for researchers to design, maintain, and administer assessments with complex structures and that use a wide variety of question types.</p

Open-sourcing RexDB®: How to package a successful open-source project as a data management platform used extensively in autism research.

<p>The need for effective centralized management of biomedical and behavioral research data has expanded dramatically in the past decade. Interdisciplinary, longitudinal, and multi-center research benefits from secure, flexible data management platforms. Current solutions are either insufficiently flexible or too expensive. Our team has developed an integrated data management platform used at over a dozen leading autism research centers over the last 6 years. In late 2011, we began to package this platform, originally developed as a mix of proprietary and open-source components, as an open-source project with the goal of making it freely available to all autism research centers and programs.</p

Building a data warehouse describing the autism research community in a new way: Extract, Load and Transform (ELT).

<p>Understanding the scope of research activities in a scientific community requires leveraging data from multiple public and private sources. However, data from different sources, such as PubMed and NIH RePORTER, may be difficult to link because data are organized differently, are of inconsistent or poor quality or lack appropriate identifiers. The standard solution to these challenges is to use an Extract, Transform and Load process (ETL), which pulls the data out of the original data source, changes its structure and content, then stores it in the target database. However, ETL processes tend to be brittle, expensive, and difficult to run. We needed a data-integration solution that would remain flexible and inexpensive, and would support an expanding list of ad hoc data sources to support decisions about scientific funding.</p

Use of an extensible, agile web development platform supports decision-making about grants and programs in autism research

<p>We produced a platform for rapidly configuring decision support dashboards that can be delivered in days or hours.</p> <p>The platform was created using an agile methodology over 10 weekly iterations. We developed a data warehouse for storing data about scientific research, added a web-native data-access layer (HTSQL) and a rapid web-application framework (HTRAF). The prototype was developed in two weeks and included a total of 21 different screens covering 5 use cases for usability reviews.</p> <p>The final tool contained 191,000 total records from multiple internal and external grants and publications sources. Specifically, the application included 136,000 NIH records and 39,800 PubMed Publications, 7,800 scientists across 1,300 institutions and 2,400 internal records.</p