DYI Ontology Development Mark A. Musen Professor of Medicine and Computer Science Stanford University

Supreme genus: SUBSTANCE Subordinate genera: BODYSPIRIT Differentiae: material immaterial Differentiae: animate inanimate Differentiae: sensitive insensitive Subordinate genera: LIVING MINERAL Proximate genera: ANIMALPLANT Species: HUMANBEAST Differentiae: rational irrational Individuals: Socrates Plato Aristotle … Porphyry’s depiction of Aristotle’s Categories

Creating Ontologies in Machine-Processable Form Provides a mechanism for developers to codify salient distinctions about the world or some application area Provides a structure for knowledge bases that can enable –Information retrieval –Information integration –Automated translation –Decision support

The New Philosophers Categorizing “what exists” in machine- understandable form Providing a structure that enables –Developers to locate and update relevant descriptions –Computers to infer relationships and properties Creating new abstractions to facilitate the creation of this structure

There is a misconception … That people building ontologies are all well versed in metaphysics, computer science, knowledge representation, and the content domain That ontologies in the real world are “clean” and well defined That most people who are creating ontologies understand all the ramifications of what they are doing!

Lots of ontology builders are not very good philosophers Nearly always, ontologies are created to address pressing professional needs The people who have the most insight into professional knowledge may have little appreciation for metaphysics, principles of knowledge representation, or computational logic There simply aren’t enough good philosophers to go around

The pressing need to standardize the names of human genes

But the human genome is only part of the problem … Biologists maintain huge databases of gene sequences and gene expression for a wide range of “model organisms” (e.g., mouse, rat, yeast, fruit fly, round worm, slime mold) Database entries are annotated with the entries such as the name of a gene, the function of the gene, and so on How do you ensure uniformity in the nature of these annotations?

Gene Ontology Consortium Founded in 1998 as a collaboration among scientists responsible for developing different databases of genomic data for model organisms (fruit fly, yeast, mouse) Now, essentially all developers of all model- organism databases participate Goal: To produce a dynamic, controlled vocabulary that can be applied to all organism databases even as knowledge of gene and protein roles in cells is accumulating and changing

GO = Three Ontologies Molecular Function –elemental activity or task –example: DNA binding Cellular Component –location or complex –example: cell nucleus Biological Process –goal or objective within cell –example: secretion

GO has been wildly successful!! Dozens of biologists around the world contribute to GO on a regular basis The ontology is updated every 30 minutes! It’s now impossible to work in most areas of computational biology without making use of GO terms

But GO has real problems … Ontologies are represented in an idiosyncratic format that is not compatible with standard knowledge-representation systems The format is based on directed acyclic graphs of concepts, without the general ability to specify machine interpretable properties of concepts or definitions of concepts Because of the informal knowledge-representation system, lots of errors have crept into GO –Terms that are duplicated in different places –Terms with no superclasses –Uncertain relationships between terms

Tension in the GO Community Biologists around the world with pressing needs to integrate research databases work together to add terms to GO nearly continuously –Using an impoverished, nonstandard knowledge- representation system –Using no standards to assure uniform modeling conventions from one part of GO to another Computer scientists bemoan all this ad-hoc-ery and condemn GO as a hack that will become increasingly unusable and unmaintainable

The Capulets and Montagues A plague on both your houses? Professor Carole Goble University of Manchester, UK Warning: This talk contains sweeping generalisations A wonderful keynote talk from the recent meeting on Standards and Ontologies for Functional Genomics

Prologue Two households, both alike in dignity, In fair genomics, where we lay our scene, (One, comforted by its logic’s rigour, Claims ontology for the realm of pure, The other, with blessed scientist’s vigour, Acts hastily on models that endure), From ancient grudge break to new mutiny, When “being” drives a fly-man to blaspheme. From forth the fatal loins of these two foes Researchers to unlock the book of life; Whole misadventured piteous overthrows Can with their work bury their clans’ strife. The fruitful passage of their GO-mark'd love, And the continuance of their studies sage, Which, united, yield ontologies undreamed-of, Is now the hours' traffic of our stage; The which if you with patient ears attend, What here shall miss, our toil shall strive to mend. Based on an idea by Shakespeare  Carole Goble

The Montagues Computer Science, Knowledge engineering, AI Logic and Languages Theory Top down, well-behaved neatness Generic and lots of toys Methodologies & patterns Tools and standards Technology push Academic pursuit One, comforted by its logic’s rigour, Claims ontology for the realm of pure  Carole Goble

The Capulets Life Scientists Practice Bottom up, real-world Specific and many of them Methodologies, community practice Tools and standards Application pull Practical pursuit – build ‘n’ use it The other, with blessed scientist’s vigour, Acts hastily on models that endure  Carole Goble

The Philosophers Philosophers Theory Truth Generic – the one true ontology? Methodologies, patterns & foundational ontologies Not really into tools No push or pull Academic pursuit One, comforted by its logic’s rigour, Claims ontology for the realm of pure  Carole Goble

The Princes of Genomics Rebellious subjects, enemies to peace, Profaners of this neighbour-stained steel,-- Will they not hear? What, ho! you men, you beasts, That quench the fire of your pernicious rage With purple fountains issuing from your veins, On pain of torture, from those bloody hands Throw your mistemper'd weapons to the ground, And hear the sentence of your moved prince. Three civil brawls, bred of an airy word, By thee, old Capulet, and Montague, Have thrice disturb'd the quiet of our streets, And made genomics's ancient citizens Cast by their grave beseeming ornaments, To wield old partisans, in hands as old, Canker'd with peace, to part your canker'd hate:  Carole Goble

A tragedy? As in Romeo and Juliet, the threats are political and sociological

Creating ontologies has become a widespread cottage industry Professional Societies –MGED: Microarray Gene Expression Data Society –HUPO: Human Protein Organization Government –NCI Thesaurus –NIST: Process Specification Language Open Biological Ontologies –GO –Three dozen (and growing) other ontologies –Mostly in DAG-Edit, some in Protégé format

Moving from cottage industry to the industrial age Government and professional societies must set expectations regarding the need for appropriate standards Government and professional societies must invest in educational programs to teach Montagues to identify with Capulets, and vice versa Demonstration projects must communicate to the potential developers of future ontologies the strengths and weaknesses of the guidelines, tools, and languages that facilitated the development work

A thousand flowers are blooming from every corner of the landscape Ontologies are being developed by interested groups from every sector of academia, industry, and government Many of these ontologies have been proven to be extraordinarily useful to wide communities Many of these same ontologies have been shown to be structurally flawed and of uncertain semantics We finally are at the stage where we have tools and representation languages that can lift us out of the grass roots to create durable and maintainable ontologies with rich semantic content