Semantic-Science

The idea of semantic science is to allow scientific data and scientific theories to be published in machine-understandable forms and for the data and the theories to interact in semantically meaningful ways. The idea is for computers to be able to understand scientific theoris and data.

This work is complementary to the Semantic Grid that is providing semantic infrastructure to scientists.

This site is very preliminary and still under construction. If there are other links that should be added (and there are lots of them) please send email to David.

Overview Papers

Here is a draft paper that tries to outline the view of machine-understandable science:

David Poole, Clinton Smyth, Rita Sharma "Semantic Science: Ontologies, Data and Probabilistic Theories" in Paulo C.G. da Costa, Claudia d'Amato, Nicola Fanizzi, Kathryn B. Laskey, Ken Laskey, Thomas Lukasiewicz, Matthias Nickles, and Mike Pool (Eds.), Uncertainty Reasoning for the Semantic Web I Springer LNAI/LNCS, 2008.

There are other visions of the interaction between science and the semantic web that are complementary to the view advocated here:

James Hendler, Science and the Semantic Web, 2003. See Science and the Semantic Web
De Roure, D., Jennings, N. R. and Shadbolt, N. R. (2005) The Semantic Grid: Past, Present and Future. Procedings of the IEEE 93(3) pp. 669-681.

People

Tim Berners-Lee - visionary for the semantic web
James Hendler - one of the semantic web leaders
Deborah L. McGuinness - works on ontologies and the semantic integration of scientific data
David Poole - works on logic and probabilities (and their interactions with ontologies)
Barry Smith - a pioneer on science ontologies
Clinton Smyth - a geologist who developed one of the first semantic science systems

Companies and Organizations

Buffalo Ontology Site - portal for ontology research
Semantic Web is the basis for much of the development of ontologies and semantic interoperability (not just for science). See also Tim Berners-Lee's design issues.
Georeference Online builds semantic science systems for the earth sciences (doing both parts, the data called "instances" and the scientific theories are called "models")

Scientific Ontologies

Here are some of the well-developed scientific ontologies:

Semantic Web for Earth and Environmental Terminology (SWEET) provides an upper-level ontology for Earth sciences. See also Universal Interchange Technology for Earth science data and services (UNITE).
Open Biomedical Ontologies (OBO) Foundry provides many ontologies for biomedical domains.

Also relevant are upper-level ontologies including:

Scientific Data Repositories

Here are some of the scientific data repositories:

The Community Data Portal publishes data on atmospheric sciences
Virtual Solar-Terrestrial Observatory (VSTO) uses semantic science to publish data on fields of solar, solar-terrestrial and space physics
OneGeology - Making Geological Map Data for the Earth Accessible

Published Scientific Theories

Currently there are no publicly-available scientific theories that adhere to a formal ontology and can make predictions based on data repositories. (As far as we know -- let us know if we are wrong).