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Challenges of ultra large scale integration of biomedical computing systems
The NCRI Informatics Initiative is overseeing the implementation of an informatics
framework for the UK cancer research community. The framework advocates an integrated
multidisciplinary method of working between scientific and medical communities. Key to this
process is community adoption of high quality acquisition, storage, sharing and integration of
diverse data elements to improve knowledge of the causes, prevention and treatment of
cancer. The integration of the complex data and meta-data used by these multiple
communities is a significant challenge and there are technical, resource-based and
sociological issues to be addressed. In this paper we review progress aimed at establishing
the framework and outline key challenges in ultra large scale integration of biomedical
computing systems
Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines
A cross-disciplinary examination of the user behaviours involved in seeking
and evaluating data is surprisingly absent from the research data discussion.
This review explores the data retrieval literature to identify commonalities in
how users search for and evaluate observational research data. Two analytical
frameworks rooted in information retrieval and science technology studies are
used to identify key similarities in practices as a first step toward
developing a model describing data retrieval
The Neuroscience Information Framework: A Data and Knowledge Environment for Neuroscience
With support from the Institutes and Centers forming the NIH Blueprint for Neuroscience Research, we have designed and implemented a new initiative for integrating access to and use of Web-based neuroscience resources: the Neuroscience Information Framework. The Framework arises from the expressed need of the neuroscience community for neuroinformatic tools and resources to aid scientific inquiry, builds upon prior development of neuroinformatics by the Human Brain Project and others, and directly derives from the Society for Neuroscience’s Neuroscience Database Gateway. Partnered with the Society, its Neuroinformatics Committee, and volunteer consultant-collaborators, our multi-site consortium has developed: (1) a comprehensive, dynamic, inventory of Web-accessible neuroscience resources, (2) an extended and integrated terminology describing resources and contents, and (3) a framework accepting and aiding concept-based queries. Evolving instantiations of the Framework may be viewed at http://nif.nih.gov, http://neurogateway.org, and other sites as they come on line
National Center for Biomedical Ontology: Advancing biomedicine through structured organization of scientific knowledge
The National Center for Biomedical Ontology is a consortium that comprises leading informaticians, biologists, clinicians, and ontologists, funded by the National Institutes of Health (NIH) Roadmap, to develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in machine-processable form. The goals of the Center are (1) to help unify the divergent and isolated efforts in ontology development by promoting high quality open-source, standards-based tools to create, manage, and use ontologies, (2) to create new software tools so that scientists can use ontologies to annotate and analyze biomedical data, (3) to provide a national resource for the ongoing evaluation, integration, and evolution of biomedical ontologies and associated
tools and theories in the context of driving biomedical projects (DBPs), and (4) to disseminate the tools and resources of the Center and to identify, evaluate, and communicate best practices of ontology development to the biomedical community. Through the research activities within the Center, collaborations with the DBPs, and interactions with the biomedical community, our goal is to help scientists to work more effectively in the e-science paradigm, enhancing experiment design, experiment execution, data analysis, information synthesis, hypothesis generation and testing, and understand human disease
Issues in the Design of a Pilot Concept-Based Query Interface for the Neuroinformatics Information Framework
This paper describes a pilot query interface that has been constructed to help us explore a "concept-based" approach for searching the
Neuroscience Information Framework (NIF). The query interface is
concept-based in the sense that the search terms submitted through the
interface are selected from a standardized vocabulary of terms
(concepts) that are structured in the form of an ontology. The NIF
contains three primary resources: the NIF Resource Registry, the NIF
Document Archive, and the NIF Database Mediator. These NIF resources
are very different in their nature and therefore pose challenges when
designing a single interface from which searches can be automatically
launched against all three resources simultaneously. The paper first
discusses briefly several background issues involving the use of
standardized biomedical vocabularies in biomedical information
retrieval, and then presents a detailed example that illustrates how
the pilot concept-based query interface operates. The paper concludes
by discussing certain lessons learned in the development of the current
version of the interface
Best Practices for Health Informatician Involvement in Interprofessional Health Care Teams
Academic and nonacademic health informatics (HI) professionals (informaticians) serve on interprofessional health care teams with other professionals, such as physicians, nurses, pharmacists, dentists, and nutritionists. Presently, we argue for investing greater attention to the role health informaticians play on interprofessional teams and the best practices to support this role
The New Knowledge Environment: Quality Initiatives in Health Sciences Libraries
published or submitted for publicatio
Participatory Approach to Program Evaluation: Learning from Students and Faculty to Improve Training in Biomedical Informatics
Participatory evaluation tools have shown to be effective for program development in various settings, including in higher education. Taking student perspectives into consideration is key for graduate program development, particularly in interdisciplinary programs.The current study utilizes Group Level Assessment (GLA),a participatory program evaluation tool, to evaluate the Biomedical Informatics (BMI) PhD Program at the University of Cincinnati (UC) and Cincinnati Children’s Hospital Medical Center (CCHMC). The study was conducted two years after the program was established, an appropriate timing to gauge the opinions of current doctoral students as the program grows and develops. The findings show the strengths and identify areas of improvement of the doctoral program, providing an evidence base for administrators and faculty to work collaboratively with students to capitalize on assets and address potential issues
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