We develop a semantics-driven, automated approach for dynamically performing rigorous scientific studies.
Data science is advancing inductive conduct of science driven by the greater volumes, complexity and heterogeneity of data being made available over the Internet. Data science combines of aspects of data management, library science, computer science, and physical science using supporting cyberinfrastructure and information technology. As such it is changing the way all of these disciplines do both their individual and collaborative work.
Data science is helping scienists face new global problems of a magnitude, complexity and interdisciplinary nature whose progress is presently limited by lack of available tools and a fully trained and agile workforce.
What has been lacking, until recently, is a successful method to develop, implement and sustain informatics solutions to modern application problems, such as environmental and climate assessments, that provide interoperability among very diverse and heterogeneous data and information sources, as
Reasoning and querying over data streams rely on the ability to deliver a sequence of stream snapshots to the processing algorithms.
These snapshots are typically provided using windows as views into streams and associated window management strategies.
Across many fields involving complex computing, software systems are being augmented with workflow logging functionality.
We have used semantic technologies to design, implement, and deploy an interdisciplinary virtual observatory. The Virtual Solar-Terrestrial Observatory is a production data framework providing access to observational datasets.
As personal assistant software matures and assumes more autonomous control of user activities, it becomes more critical that this software can tell the user why it is doing what it is doing, and instill trust in the user that its task knowledge reflects standard practice and is being appropriatel
Information Fusion has been a focus of research within the field of computer science for a number of years.