1. The Bio-Health Informatics Group Andy Brass – andrewmbrass@gmail.com Robert Stevens – robert.stevens@manchester.ac.uk

2. What is Bio-health Informatics? Biology, medicine and health care produce lots of data They produce very complex data They produce volatile data And it’s a bit of a mess too Bio-health informatics is all about managing and analysing those data Data management and description (ontologies, linked data, integration) Data science – innovative methods for making the data work…

3. Bio-health around the school Andy Brass (BHIG) Robert Stevens (BHIG) Sophia Ananiadou ™ Goran Nenadic ™ Jock McNaught ™ Pedro Mendes (MLO) Ross King (MLO) Carole goble (IMG) Norman Paton (IMG) Bijan Parsia (IMG) …and more… There’s a lot of it going on It poses problems for lots of areas of cS..and lots of connections outside the school into FLS and medicine

4. We’re diverse Health records for mummies Natural language generation from ontologies Ontology comprehension Tolerance to sleeping sickness in east African cattle Ontology Design Patterns Ziphian analyses of annotations in health records Managing, integrating and analysing kidney and urinary pathway data Understanding how people author ontologies

5. What is an ontology? The number “7” isn’t much good to us… “7 cm” tells us it’s a length, but not what it’s a length of… “7 cm tail which is part of a mouse” tells us a whole lot more Descriptions of the semantics of a domain in the form of an ontology We write these ontologies in the Web Ontology Language (OWL) Building, using, evaluating these ontologies is of research interest

6. Describing a buttercup in OWL Class: RanunculusRepens Annotations: [in flower] label "Ranunculus Repens", comment "Common buttercup"^^string SubClassOf: [in flower] * Flower, Flower and (hasFlowerSymmetry some RadialSymmetry) and (hasPart some (Androecium and (hasAndroecialFusion some Apostemonous) and (hasPart some (Stamen and (hasPart some Filament) and (hasPart some (Anther and (hasAntherAttachment some AdnateAntherAttachment) and (hasDehiscenceType some LongitudinalDehiscence))))))) and (hasPart some (Gynoecium and (hasGynoecialFusion some Apocarpous) and (hasPart some (Pistil and (hasPart some Carpel) and (hasPart some Style) and (hasPart some (Stigma and (hasStickiness some Stickiness) and (hasStigmaShape some HookedStigmaShape))) and (hasPart only (Carpel or Stigma or Style)))) and (hasSexualPartArrangement some SpiralArrangement))) and (hasPart exactly 1 (Perianth and (hasPart some (Calyx and (hasPart exactly 5 (Sepal and (hasColour some Green) and (hasRegion some (BaseRegion and (hasForm some Truncate))) and (hasRegion some (MarginRegion and (hasSepalPetalFeature some Entire) and (hasSepalPetalFeature some Membranous))) and (hasRegion some (SurfaceRegion and (hasSepalPetalFeature some Pubescent) and (hasSurfaceSelector some LowerSurfaceSelector))) and (hasRegion some (SurfaceRegion and (hasSepalPetalFeature some Smooth) and (hasSurfaceSelector some UpperSurfaceSelector))) and (hasRegion some (TipRegion and (hasForm some Truncate))) and (hasSepalPetalFeature some PalmatelyNetted) and (hasSepalPetalShape some Ovate) and (hasSepalousity some Aposepalos))))) and (hasPart some (Corolla and (hasPart exactly 5 (Petal and (hasColour some Yello) and (hasPetalousity some Apopetalos) and (hasRegion some (BaseRegion and (hasForm some Acute))) and (hasRegion some (MarginRegion and (hasSepalPetalFeature some Entire))) and (hasRegion some (TipRegion and (hasForm some Acute))) and (hasSepalPetalFeature some PalmatelyNetted) and (hasSepalPetalShape some Obovate) and (hasPart exactly 1 Nectary))))) and (hasPerianthArrangement some AlternatingPerianthArrangement) and (hasPart only (Calyx or Corolla) )))

7. Evaluating an emotion ontology Can members of the audience at the International Conference on Biomedical Ontology articulate their emotional response to a talk using the emotion ontology? For each talk, audience members record their emotions and ease of articulation using tags We analyse the data for: –Whether the tags were adequate –Strength of emotional response –Effects of talk, time of day –Tags that are missing anxiety anger contempt disgust surprise grief interest fear pleasure jealousy compassion hate disappointment irritation moral disgust

8. Making kidney and urinary pathway data useful

9. What if…? An ontology is a complex system of axioms An automated reasoner draws inferences from the axioms in the ontology “What if…” I add this axiom? Investigating the authoring tasks, for an ontology How do we help authors to explore the effects of the axioms we add?

10. Possible ontology topics this year Automatic annotation of pmouse phenotypes Metrics for ontology evaluation Exploring and exploiting document and rhetoric structure for scientific Text-mining Cost models for ontology development styles