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Goals, Purpose, and
Sope:
Goal:
To identify opportunities for information science (IS) standards
and standards development to facilitate bioscience and biomedical
research.
Purposes:
To define the current and emerging state of information science
(IS) standards related to bioscience and biomedical research, and
To identify barriers and gaps to, and opportunities and pathways
for, IS standards development and implementation to enhance bioscience
and biomedical research.
Scope:
The last decade has seen an explosive increase in the use of information
science and technology within all areas of biology and medicine.
From molecular biology to genomics to organism modeling, research
has become dependent on databases, software and networks that proliferates
everyday. Information technology standards are a key aspect to ensuring
that this happens. This workshop brings together researchers in
biology and medicine with experts on data, networks, and computation
to discuss how and why such standards are required for bioscience
and biomedical research. The workshop focuses on three specific
areas:
- Biomedical
Data Integration Standards. (e.g., ontology, data format, nomenclature)
The goal of this session is to assess current standards associated
with the integration and use of massive and complex data sets
from diverse, distributed sources and different levels of biological
systems and identify areas where more (or different) is needed.
- Networked
Science. As we enter an era of intensely collaborative science
enabled by intelligent computer networks and the teragrid -- the
world's largest, fastest, distributed infrastructure for open
scientific research. What IS standards are needed to harness this
computer power to advance biology and medical research? How will
such standards foster the virtual laboratories of the future?
- Quantitative
Computational Biology. Advances in computation power, networking,
modeling and applied mathematics have made quantitative computational
biology a reality. The analysis and interpretation of biological
knowledge increasingly results from modeling of complex biological
phenomena. What standards are required to improve today’s
environment for quantitative computational biology?
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