Scientific Data Management Group
Advances in observational, experimental and computational technologies have led to an exponential increase in the volumes, variety and complexity of scientific data, and whilst data deluge might not be happening everywhere in an absolute sense, it does in a relative one for most research groups. This exceptional growth in data volumes and complexity has presented researchers with significant challenges, foremost how to manage, analyze and correlate the results of their research effectively.
The PNNL Scientific Data Management Group offers innovative solutions to enable effective research in these data intensive environments, by engaging in leading edge research and development in data quality management, metadata, provenance, data analysis and integration, semantic technologies and knowledge management. The group focuses on integrated solution design, tightly embedded into the scientific research processes, working closely with computational and experimental researchers in climate science, earth science, chemistry, systems biology, high energy physics and energy, as well as the law enforcement and intelligence community.
Next to research and development the group operates highly distributed, data management system services such as the Data Management Facility of the Atmospheric Radiation Measurement Climate Research facility for the past 25 years. The PNNL Scientific Data Management Group currently has 24 members on staff.
We are delighted to announce that Professor Paulo Pinheiro da Silva is joining the PNNL Scientific Data Management group on January 1st 2012. Paulo is an outstanding researcher in the areas of provenance and semantic and will lead the group's provenance work.
Group lead Kerstin Kleese van Dam with Laboratory Fellow, Professor Valerio Pascucci.
We are pleased to announce that Professor Valerio Pascucci has joined the PNNL Scientific Data Management Group in a joint appointment with the University of Utah's Scientific Computing and Imaging Institute. Valerio will be strengthening the groups data analysis and visualization efforts.
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