The overall goal of this effort is to bring together key aspects of intelligent systems, namely data mining / knowledge extraction and semantic knowledge representation, and to prove the benefit of this approach by applying it to a science problem that is representative of NASA Science Mission Directorate research interests. The Scientific Knowledge Integration Framework (SKIF) vision is to integrate distributed resources including a toolkit of data mining and knowledge extraction web services designed specifically for NASA data; a series of linked ontologies describing both the data mining, manipulation and analysis services as well as the science problem domain; and a web-based user interface which will allow users to discover and explore available data and services, compose workflows of data access, data mining and related services appropriate for their tasks, and invoke them to perform the desired analysis.
Original project objectives required to meet this goal include:
- Provide formal, unambiguous and machine-operable descriptions of science domains and relevant data sets captured in ontologies using Web Ontology Language recommended standards.
- Leverage previous NASA-funded research to package selected algorithms from the Algorithm Development and Mining (ADaM) data mining toolkit as web services.
- Provide ontological descriptions of these services using the OWL-S service ontology language.
- Prototype a science user environment that will allow a researcher to explore the services available for addressing specific data analysis needs and orchestrate selected services into a workflow.