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Abstract. OWL ontologies present many interesting visualization challenges. Here we present CropCircles, a technique designed to view the class hierarchies in ontologies as trees. We place special emphasis on topology understanding when designing the tool. We drew inspiration from treemaps, but made substantial changes in the representation and layout. Most notably, the spacefillingness of treemap is relaxed in exchange for visual clarity. We outline the problem scape of visualizing ontology hierarchies, note the requirements that go into the design of the tool, and discuss the interface and implementation. Finally, through a controlled experiment involving tasks common to understanding ontologies, we show the benefits of our design.

Current electronic health record (EHR) systems facilitate the storage, retrieval, persistence, and sharing of patient data. However, the way physicians interact with EHRs has not changed much. More specifically, support for temporal analysis of a large number of EHRs has been lacking. A number of information visualization techniques have been proposed to alleviate this problem. Unfortunately, due to their limited application to a single case study, the results are often difficult to generalize across medical scenarios. We present the usage data of Lifelines2 [22], our information visualization system, and user comments, both collected over eight different medical case studies. We generalize our experience into a visual analytics process model for multiple EHRs. Based on our analysis, we make seven design recommendations to information visualization tools to explore EHR systems.

We have designed a Biobank Portal that lets researchers request Biobank samples and genotypic data, query associated electronic health records, and design and download datasets containing de-identified attributes about consented Biobank subjects. This do-it-yourself functionality puts a wide variety and volume of data at the fingertips of investigators, allowing them to create custom datasets for their clinical and genomic research from complex phenotypic data and quickly obtain corresponding samples and genomic data. The Biobank Portal is built upon the i2b2 infrastructure [1] and uses an open-source web client that is available to faculty members and other investigators behind an institutional firewall. Built-in privacy measures [2] ensure that the data in the Portal are utilized only according to the processes to which the patients have given consent.

Abstract. We survey nearly 1300 OWL ontologies and RDFS schemas. The collection of statistical data allows us to perform analysis and report some trends. Though most of the documents are syntactically OWL Full, very few stay in OWL Full when they are syntactically patched by adding type triples. We also report the frequency of occurrences of OWL language constructs and the shape of class hierarchies in the ontologies. Finally, we note that of the largest ontologies surveyed here, most do not exceed the description logic expressivity of ALC.

Current electronic health record (EHR) systems facilitate the storage, retrieval, persistence, and sharing of patient data. However, the way physicians interact with EHRs has not changed much. More specifically, support for temporal analysis of a large number of EHRs has been lacking. A number of information visualization techniques have been proposed to alleviate this problem. Unfortunately, due to their limited application to a single case study, the results are often difficult to generalize across medical scenarios. We present the usage data of Lifelines2 [22], our information visualization system, and user comments, both collected over eight different medical case studies. We generalize our experience into an information-seeking process model for multiple EHRs. Based on our analysis, we make recommendations to future information visualization designers for EHRs on design requirements and future research directions.

No abstract

Historically, medical images collected in the course of clinical care have been difficult to access for secondary research studies. While there is a tremendous potential value in the large volume of studies contained in clinical image archives, Picture Archiving and Communication Systems (PACS) are designed to optimize clinical operations and workflow. Search capabilities in PACS are basic, limiting their use for population studies, and duplication of archives for research is costly. To address this need, we augment the Informatics for Integrating Biology and the Bedside (i2b2) open source software, providing investigators with the tools necessary to query and integrate medical record and clinical research data. Over 100 healthcare institutions have installed this suite of software tools that allows investigators to search medical record metadata including images for specific types of patients. In this report, we describe a new Medical Imaging Informatics Bench to Bedside (mi2b2) module (www.mi2b2.org), available now as an open source addition to the i2b2 software platform that allows medical imaging examinations collected during routine clinical care to be made available to translational investigators directly from their institution’s clinical PACS for research and educational use in compliance with the Health Insurance Portability and Accountability Act (HIPAA) Omnibus Rule. Access governance within the mi2b2 module is customizable per institution and PACS minimizing impact on clinical systems. Currently in active use at our institutions, this new technology has already been used to facilitate access to thousands of clinical MRI brain studies representing specific patient phenotypes for use in research.