Harry Hochheiser

The Open Microscopy Environment (OME) Data Model and XML file: open tools for informatics and quantitative analysis in biological imaging

The Open Microscopy Environment (OME) defines a data model and a software implementation to serve as an informatics framework for imaging in biological microscopy experiments, including representation of acquisition parameters, annotations and image analysis results. OME is designed to support high-content cell-based screening as well as traditional image analysis applications. The OME Data Model, expressed in Extensible Markup Language (XML) and realized in a traditional database, is both extensible and self-describing, allowing it to meet emerging imaging and analysis needs.

The FaceBase Consortium: a comprehensive program to facilitate craniofacial research.

The FaceBase Consortium consists of ten interlinked research and technology projects whose goal is to generate craniofacial research data and technology for use by the research community through a central data management and integrated bioinformatics hub. Funded by the National Institute of Dental and Craniofacial Research (NIDCR) and currently focused on studying the development of the middle region of the face, the Consortium will produce comprehensive datasets of global gene expression patterns, regulatory elements and sequencing; will generate anatomical and molecular atlases; will provide human normative facial data and other phenotypes; conduct follow up studies of a completed genome-wide association study; generate independent data on the genetics of craniofacial development, build repositories of animal models and of human samples and data for community access and analysis; and will develop software tools and animal models for analyzing and functionally testing and integrating these data. The FaceBase website (http://www.facebase.org) will serve as a web home for these efforts, providing interactive tools for exploring these datasets, together with discussion forums and other services to support and foster collaboration within the craniofacial research community.

Interactive Exploration of Time Series Data

Widespread interest in discovering features and trends in time- series has generated a need for tools that support interactive exploration. This paper introduces timeboxes: a powerful direct-manipulation metaphor for the specification of queries over time series datasets. Our TimeSearcher implementation of timeboxes supports interactive formulation and modification of queries, thus speeding the process of exploring time series data sets and guiding data mining.

Using interactive visualizations of WWW log data to characterize access patterns and inform site design

HTTP server log files provide Web site operators with substantial detail regarding the visitors to their sites. Interest in interpreting this data has spawned an active market for software packages that summarize and analyze this data, providing histograms, pie graphs, and other charts summarizing usage patterns. While useful, these summaries obscure useful information and restrict users to passive interpretation of static displays. Interactive visualizations can be used to provide users with greater abilities to interpret and explore web log data. By combining two-dimensional displays of thousands of individual access requests, color and size coding for additional attributes, and facilities for zooming and filtering, these visualizations provide capabilities for examining data that exceed those of traditional web log analysis tools. We introduce a series of interactive visualizations that can be used to explore server data across various dimensions. Sample visualizations of server data from two web sites are presented. Coordinated, snap-together visualizations (STVs) of log data are introduced as a means of gaining additional expressive power. Possible uses of these visualizations are discussed, and difficulties of data collection, presentation, and interpretation are explored.

Universal usability as a stimulus to advanced interface design

The desire to make computing available to broader populations has historically been a motivation for research and innovation that led to new breakthroughs in usability. Menus, graphical user interfaces and the World Wide Web are examples of innovative technological solutions that have arisen out of the challenge of bringing larger and more diverse groups of users into the world of computing. Universal usability is the latest such challenge: In order to build systems that are universally usable, designers must account for technology variety, user diversity and gaps in user knowledge. These issues are particularly challenging and important in the context of increasing the usability of the World Wide Web. To raise awareness, web designers are urged to provide universal usability statements that offer users information about the usability of their sites. These statements can inform users and thereby reduce frustration and confusion. Further steps toward universal usability might be achieved through research aimed at developing tools that would encourage or promote usability. The paper closes with five proposals for future research.

Performance Benefits of Simultaneous over Sequential Menus as Task Complexity Increases

To date, experimental comparisons of menu layouts have concentrated on variants of hierarchical structures of sequentially presented menus. Simultaneous menus-layouts that present multiple active menus on a screen at the same time-are an alternative arrangement that may be useful in many Web design situations. This article describes an experiment involving a between-subject comparison of simultaneous menus and their traditional sequential counterparts. A total of 20 experienced Web users used either simultaneous or sequential menus in a standard Web browser to answer questions based on U.S. Census data. Our results suggest that appropriate use of simultaneous menus can lead to improved task performance speeds without harming subjective satisfaction measures. For novice users performing simple tasks, the simplicity of sequential menus appears to be helpful, but experienced users performing complex tasks may benefit from simultaneous menus. Design improvements can amplify the benefits of simultaneous menu layouts.

HCI and Societal Issues: A Framework for Engagement

Human-computer interaction (HCI) is much broader than the study of interface design and input devices. It includes considerations of the social, political, ethical, and societal implications of computer systems. Concerns such as privacy, accessibility, universal design, and voting usability have led to active HCI research. Our examination of HCI responses to these and other issues informs a model of social engagement based on societal influences that motivate various responses from the HCI community. This model provides suggestions for engagement with issues that are likely to grow in importance over the next several years. By focusing on these issues, HCI researchers may make still greater contributions toward addressing societal concerns.

The Monarch Initiative: an integrative data and analytic platform connecting phenotypes to genotypes across species.

The correlation of phenotypic outcomes with genetic variation and environmental factors is a core pursuit in biology and biomedicine. Numerous challenges impede our progress: patient phenotypes may not match known diseases, candidate variants may be in genes that have not been characterized, model organisms may not recapitulate human or veterinary diseases, filling evolutionary gaps is difficult, and many resources must be queried to find potentially significant genotype–phenotype associations. Non-human organisms have proven instrumental in revealing biological mechanisms. Advanced informatics tools can identify phenotypically relevant disease models in research and diagnostic contexts. Large-scale integration of model organism and clinical research data can provide a breadth of knowledge not available from individual sources and can provide contextualization of data back to these sources. The Monarch Initiative (monarchinitiative.org) is a collaborative, open science effort that aims to semantically integrate genotype–phenotype data from many species and sources in order to support precision medicine, disease modeling, and mechanistic exploration. Our integrated knowledge graph, analytic tools, and web services enable diverse users to explore relationships between phenotypes and genotypes across species.

Use of model organism and disease databases to support matchmaking for human disease gene discovery.

The Matchmaker Exchange application programming interface (API) allows searching a patients genotypic or phenotypic profiles across clinical sites, for the purposes of cohort discovery and variant disease causal validation. This API can be used not only to search for matching patients, but also to match against public disease and model organism data. This public disease data enable matching known diseases and variant–phenotype associations using phenotype semantic similarity algorithms developed by the Monarch Initiative. The model data can provide additional evidence to aid diagnosis, suggest relevant models for disease mechanism and treatment exploration, and identify collaborators across the translational divide. The Monarch Initiative provides an implementation of this API for searching multiple integrated sources of data that contextualize the knowledge about any given patient or patient family into the greater biomedical knowledge landscape. While this corpus of data can aid diagnosis, it is also the beginning of research to improve understanding of rare human diseases.

Evaluating the barriers to point-of-care documentation for nursing staff.

Point-of-care documentation has been identified as a patient safety measure for improving accuracy and timeliness of data. To evaluate the barriers that nurses and nurse aide/clinical technicians encounter for electronic point-of-care documentation, we conducted surveys on a telemetry unit at a southwestern Pennsylvania community hospital. Our first survey revealed that the location of the in-room computers, perceived lack of in-room computer reliability, Health Insurance Portability and Accountability Act/privacy concerns, and perceptions of the patients’ response to charting on computers in patient rooms were all barriers to point-of-care documentation. Our second survey revealed that workflow priority issues were also a barrier to point-of-care documentation, as staff members did not rate documentation as a high priority in terms of delivering timely medical care. Changes in both nursing practices and hospital infrastructure may be needed if these barriers to point-of-care documentation are to be overcome.