These are my notes for the talk at the UK Ontology Network Meeting on 14 April, 2016 by Albert Burger, Kenneth McLeod, Chris Armit, Bill Hill, Richard Baldock.
EMAP is used to connect information to visual atlases (Biomedical Atlases) which provide virtual cross-sections of embryos, gene expression etc. Then should be a good link between the visual and the ontology (Anatomy Ontology). EMAP is not as formal as the FMA. BSPO is the Biological Spatial Ontology was created to define spacial direction for describing an organism. WHS (Waxholm Space) is a project dealing with atlas-based data integration. Other atlases include EMA and ABA Brain Atlas.
Integrating across atlases can be tricky. The Straightened Mouse is a project which examines the cartesian vs. natural coordinates. So, people take the 3D model and straighten it, then add axes. From there you can create an EMA 3D model with axes. This means you can now have an up-down direction that actually makes sense. Therefore, even though a curled up point may be below another point, biologically they can store the information that it is actually above it on the organism.
Once you have this information, you can apply these spatial relations in all other sorts of ways (you can say “lateral to the heart” and have it clearly mean something on the model).
So, they are taking information out of the text and pull it out into the information in the atlas. Equally, you can ask the atlas if any papers talk about a particular region.
Ontological challenges include standardization of the ontological-to-geometric space mapping. They also need to discover the most effective spatial descriptions. They wish to see if they can learn from human-to-human communication (versus a computer intermediary). What are the best KR languages to use (e.g. OWL, Prolog)? What are the best spatial reasoning solutions (e.g. RCC)?
Please note that this post is merely my notes on the presentation. I may have made mistakes: these notes are not guaranteed to be correct. Unless explicitly stated, they represent neither my opinions nor the opinions of my employers. Any errors you can assume to be mine and not the speaker’s. I’m happy to correct any errors you may spot – just let me know!