Fast and Accurate Metadata Authoring Using Ontology-Based Recommendations.

In biomedicine, high-quality metadata are crucial for finding experimental datasets, for understanding how experiments were performed, and for reproducing those experiments. Despite the recent focus on metadata, the quality of metadata available in public repositories continues to be extremely poor. A key difficulty is that the typical metadata acquisition process is time-consuming and error prone, with weak or nonexistent support for linking metadata to ontologies.

ImmPort, toward repurposing of open access immunological assay data for translational and clinical research.

Immunology researchers are beginning to explore the possibilities of reproducibility, reuse and secondary analyses of immunology data. Open-access datasets are being applied in the validation of the methods used in the original studies, leveraging studies for meta-analysis, or generating new hypotheses. To promote these goals, the ImmPort data repository was created for the broader research community to explore the wide spectrum of clinical and basic research data and associated findings.

RImmPort: an R/Bioconductor package that enables ready-for-analysis immunology research data.

Summary: : Open access to raw clinical and molecular data related to immunological studies has created a tremendous opportunity for data-driven science. We have developed RImmPort that prepares NIAID-funded research study datasets in ImmPort (immport.org) for analysis in R.

TrialWiz: an ontology-driven tool for authoring clinical trial protocols.

There has long been great interest in the clinical research community for automated support of clinical trials management. At the core of such efforts is formal specification of protocol knowledge. Building a clinical-trial knowledge base is a complex task involving software engineers and domain experts.

Knowledge-data integration for temporal reasoning in a clinical trial system.

Managing time-stamped data is essential to clinical research activities and often requires the use of considerable domain knowledge. Adequately representing and integrating temporal data and domain knowledge is difficult with the database technologies used in most clinical research systems. There is often a disconnect between the database representation of research data and corresponding domain knowledge of clinical research concepts.

An ontology-based architecture for integration of clinical trials management applications.

Management of complex clinical trials involves coordinated-use of a myriad of software applications by trial personnel. The applications typically use distinct knowledge representations and generate enormous amount of information during the course of a trial. It becomes vital that the applications exchange trial semantics in order for efficient management of the trials and subsequent analysis of clinical trial data.

Knowledge-level querying of temporal patterns in clinical research systems.

Managing time-stamped data is essential to clinical research activities and often requires the use of considerable domain knowledge. Adequately representing this domain knowledge is difficult in relational database systems. As a result, there is a need for principled methods to overcome the disconnect between the database representation of time-oriented research data and corresponding knowledge of domain-relevant concepts.

Translating research into practice: organizational issues in implementing automated decision support for hypertension in three medical centers.

Information technology can support the implementation of clinical research findings in practice settings. Technology can address the quality gap in health care by providing automated decision support to clinicians that integrates guideline knowledge with electronic patient data to present real-time, patient-specific recommendations. However, technical success in implementing decision support systems may not translate directly into system use by clinicians.

A knowledge-acquisition wizard to encode guidelines.

An important step in building guideline-based clinical care systems is encoding guidelines. Protégé-2000, developed in our laboratory, is a general-purpose knowledge-acquisition tool that facilitates domain experts and developers to record, browse and maintain domain knowledge in knowledge bases. In this poster we illustrate a knowledge-acquisition wizard that we built around Protégé-2000.