The Ontology Blog

Standardizing Ontology a Top Priority for NICHD

2011-10-21T19:36:00.000-07:00

The Eunice Kennedy Shriver National Institute for Child Health and Human Development held a series of "vision workshops" to create its vision for the next decade.

In a slide deck here (warning: PDF), the number one recommendation under the heading of "Transdisciplinary Science" is ...Standardize ontology, nomenclature, and data standards across disciplines.

The Director of NICHD, Dr. Alan Guttmacher, reitierated that recommendation today in a presentation to the Clinical and Translational Science Award Consortium Child Health Oversight Committee (CC-CHOC). The CC-CHOC meeting had a theme of "Quality Data from Pediatric Trials".

Speakers throughout the day emphasized the need for development and use of standards for collection of data in pediatric research.

Workshop and Tutorial Summary

2011-07-28T04:38:00.000-07:00

I attended the Representing Adverse Events Workshop, and presented as part of the Improving Structured EHR Data Tutorial.

The Adverse Events Workshop confronted the issue of what exactly an adverse event is. A diversity of viewpoints frustrated attempts to reach consensus. The need for an adverse events ontology was called into question by some participants (and one non-participant with whom I discussed the issue afterwards). The concern is that various symptoms and diseases will be duplicated. For example, "fever" vs. "fever adverse event" and "rash" vs. "rash adverse event".

The outcome was an agreement to review use cases and to create a Google Group where participants can post links to their ontologies with requests for feedback. One participant took the action item of reviewing various artifacts (ontology and otherwise) that give definitions of 'adverse event' to look for commonalities.

The Improving Structured EHR Data Tutorial was given by Werner Ceusters and myself. As one of the instructors, I do not want to overstate the success of the tutorial, but there were excellent discussions about Referent Tracking and the advantages it has for making EHR data unambiguous. At least one participant approached me to express her appreciation for the potential of Referent Tracking, and her willingness to collaborate on projects in the future.

The hard work of improving our ability to leverage information to accelerate improvements in the quality and efficiency of biomedical research and patient care continues...

On the eve of ICBO 2011

2011-07-25T18:42:00.000-07:00

I am here in Buffalo on the eve of the International Conference on Biomedical Ontology 2011. The conference begins with workshops and tutorials on Tuesday and Wednesday, followed by the 3-day conference program on Thursday, Friday, and Saturday.

The conference web site is here.

I will be attending the Representing Adverse Events Workshop tomorrow, then participating in a more meaningful way in the Improving Structured EHR Data Tutorial on Wednesday morning.

Over the next few days, it is my intent to post summaries of the best and worst of this year's ICBO, as I did at the last ICBO in 2009.

ISO TR 12310 Draft Standard - Problems and Issues

2011-04-29T03:37:00.000-07:00

A draft of the ISO TR 12310 standard came across our desks in the last day or two, and we were surprised at the substantial problems that exist in its fundamental components. The title of the standard is "Health informatics — Principles and guidelines for the measurement of conformance in the implementation of terminological systems".

First, it defines a concept as "A concept is a single mental representation of some real or abstract thing."

This definition is problematic, because never in the history of terminological systems has anyone elucidated a theory of a basic unit of mental representation. What is a single mental representation? Or a unit of thought (as concept has also been defined)?

If I'm thinking of a car, is that a unit of thought? What if I'm thinking about a particular red, C-class Mercedes Benz with a particular Vehicle Identification Number? Or what if I'm just thinking about red, C-class Mercedes owned by stock brokers and that need new brakes and on which a tree fell during a Spring storm, in general? How many unique mental representations are there? One, two, three? How do we count unique ideas and single mental representations?

This question is not trivial, as the answer determines what concept representations we are permitted to have. Historically, the answer has been that anything anyone wants to put in the system is allowable. For a real-world example, consider the following "concept" from SNOMED CT: Family history of myocardial infarct in first degree female relative less than 65 years of age (situation).

The draft standard then goes on to say: "Concepts are should be unique within a code system." The grammatical problem aside, the standard is now engaged in use-mention confusion. For your mental representations are not part of any code system! The standard is using the word concept for both representations of concepts and concepts (themselves mental representations).

The draft standard then goes on to say: "A concept representation is a mechanism by which the system can express a concept." So it should be concept representations that are unique within a code system, not concepts.

But then the standard says: "Most code systems support multiple representations for each concept, sometimes even multiple representations of a given type."

How do code systems support interoperability, then?

Next, we are told that a "Concept id" is "A concept representation that is unique within the code system and that is used internally by the code system when referencing concepts."

Does that mean we cannot use concept ids outside the code system, either because it's impossible or disallowed? Surely some software applications are using SNOMED CT concept ids external to SNOMED CT itself? Are they out of conformance?

And that covers just pages 1 and 2.

NSF Funds Phenotype Ontology Coordination Network

2010-11-29T04:44:00.000-08:00

The National Science Foundation recently awarded just over $500,000 to the University of South Dakota (USD) for the creation of the Phenotype Ontology Research Coordination Network. According to the grant proposal, the PI at USD is Dr. Paula Mabee and coPIs include Dr. Andrew Dean (North Carolina State University), Dr. Eva Huala (Stanford University), Suzanna Lewis (Lawrence Berkley National Laboratory), and Dr. Anne Maglia (Missouri University of Science and Technology).

The goal of the grant is to ...establish a network of scientists who are developing phenotype ontologies and to use this network to enable and enhance the research of all of those involved.

The specific aims are:

Develop anatomical reference ontologies for three key taxonomic clades;
Align and synchronize anatomical ontologies using homology and various types of similarity relations;
Define, test and document anatomy ontology development best practices and standards;
Reach out to ancillary phenotype groups to share with them common concepts and practices;
Educate the community about the methods for developing ontologies and their importance and utility in research.

The principals of the grant are soliciting participation in the network. To join, you can sign up here.

The Statistical Core Vocabulary: Can Definitions Really be this Bad?

2010-11-27T07:00:00.000-08:00

I just learned of the Statistical Core Vocabulary (abbreviated as SCOVO), the latest version of which one may find here. This vocabulary defines itself as: A vocabulary for representing statistical data on the Web.

It contains 3 classes and 5 properties. For a small artifact that aims to capture the core entities in a domain, one ought to expect that careful attention would be paid to the definitions of the classes and properties, on the part of its creator(s).

Clearly, that is not the case here.

The SCOVO definition of Dataset is: a statistical dataset. This is equivalent to defining subatomic particle as: a positively-charged subatomic particle.

Similarly, the SCOVO definition of Item is: a statistical data item. This definition is even worse, being the equivalent of defining book as: a red hardcover book.

Finally, the SCOVO definition of its third and final class, Dimension, is: a dimension of a statistical data item. This definition is the equivalent of defining length as the length of a rectangular wooden table.

The situation for the properties in SCOVO is no better. Two of the properties even have the same name as two of the classes: dimension and dataset. The dataset relation is intended to link an item to a dataset. The dataset relation is thus the equivalent of having a relation liver to link the liver itself to the organism of which it is part.

By contrast, the Information Artifact Ontology (IAO) has taken pains to define the terms data item and dataset well. Definitions of these terms, and other terms used in their definitions, follow:

Data item: an information content entity that is intended to be a truthful statement about something (modulo, e.g., measurement precision or other systematic errors) and is constructed/acquired by a method which reliably tends to produce (approximately) truthful statements.

Information content entity: an entity that is generically dependent on some artifact and stands in relation of aboutness to some entity.

Note that for the definition of generic dependence, the IAO relies on a formal, upper ontology called Basic Formal Ontology.

Data set: a data item that is an aggregate of other data items of the same type that have something in common. Averages and distributions can be determined for data sets.

In the IAO, data items stand in the "is about" relation to some entity. Thus, data are linked to the world that they are about.

SCOVO does have one thing going for it: it serves as an exemplar of the worst possible way to define terms.

Physician decries lack of definitions in informatics

2010-09-01T05:50:00.000-07:00

Dick Stanley, MD, Chief Medical Information Officer (CMIO) at Cooley-Dickinson Hospital, Northampton, Mass, decries the lack of definitions in informatics. He states: Interestingly, I’m having trouble finding even basic definitions of very common terms...

Dr. Stanley correctly points out that the science of informatics requires good definitions of terms to make progress. He notes that ...we’re supposed to be the people who care about [definitions].

However, the field of biomedical informatics has long been delinquent in this regard. The definitions it does generate are often quite poor. Like many outsiders who are recent to the field of informatics, Dr. Stanley notes that ...the whole informatics industry suffers from a tremendous lack of definitions.

As a member of that "industry" for 15 years, Dr. Stanley, let me say, guilty as charged.

Fortunately, there is light on the horizon. Criticism in this regard from ontologists like Dr. Barry Smith and Dr. Werner Ceusters at the University at Buffalo is beginning to turn the tide. They have been advocating for high-quality definitions in ontologies and information models for years, culminating in the adoption at least 3 principles mandating definitions of high quality by the OBO Foundry.

Of course, many ontologists, typically those with an engineering and/or computer science background, are anxious to have rigorous logical axioms that define ontology terms. We caution that getting textual definitions for human understanding correct is a necessary first step toward the logical axioms they rightly desire for ontologies to support automated reasoning.

But we ought not to put any carts before the horse of textual definitions, be they the conduct of science, the application of science to the clinical realm, or the development of logical axioms to automate cognitive activities of humans.

LOINC Changes Frustrating Semantic Interoperability in Canada

2010-07-30T04:47:00.000-07:00

According to minutes of the 2010-07-29 HL7 Vocabulary Working Group call, the new release of Logical Observation Identifiers, Names, and Codes (LOINC) is creating ambiguity about how to represent things like birth date. Apparently, it is now possible to represent birth date as an "observation", with a value that is a date. This representation conflicts with the "usual" way of representing birth date in the HL7 Clinical Document Architecture (CDA) standard, which represents it as a "demographic attribute of a person".

Really, the fundamental issue here is the failure to recognize that terminologies such as LOINC and SNOMED CT are representations developed in uncoordinated fashion with HL7's CDA, also a representation. Which is to say, that terminologies, information models, and ontologies (obviously) all make ontological commitments.

Conflicting views such as these are common. Indeed the whole TermInfo group of HL7 was created to reconcile conflicting representations (HL7 and SNOMED CT) to ensure (as much as possible) semantic interoperability.

Confusion reigns--and remains--about SNOMED CT licensing

2010-04-09T12:32:00.000-07:00

On a Clinical and Translational Science Award (CTSA) Consortium call about data standards and interoperability, participants raised numerous questions about the allowable uses of SNOMED CT in the applications they are developing to facilitate translational science.

If I develop a web application that uses SNOMED CT codes under the covers, may I allow users in a country without a SNOMED CT license to access it?

If I develop a subset of SNOMED CT codes (sometimes also known as a "value set") to serve as the set of answers to an online survey question, can I publish this subset for others to use (thereby facilitating interoperability among surveys)?

By the end of the call, attendees had more questions than answers.

Wouldn't the open approach taken by the Open Biomedical Ontologies (OBO) Foundry serve the purpose of interoperability better? Shouldn't the United States redirect at least some of its investment in SNOMED CT into truly open standards?

First OBO Foundry Ontologies Announced

2010-03-05T16:53:00.000-08:00

The OBO Foundry Coordinating Editors today announced the first set of ontologies to be included in the OBO Foundry. They are:

CHEBI: Chemical Entities of Biological Interest
GO: Gene Ontology
PATO: Phenotypic Quality Ontology
PRO: Protein Ontology
XAO: Xenopus Anatomy Ontology
ZFA: Zebrafish Anatomy Ontology

Candidates that came close to membership but require more extensive revision first include the Cell Ontology (CL) and the Foundational Model of Anatomy (FMA). In particular, the FMA requires an open source license.

The Editors recommend that these ontologies ...serve as preferred targets for community convergence.

We agree.

Hymenoptera Ontology Receives NSF Funding

2010-02-16T15:51:00.001-08:00

Somehow, we always seem to find out that ontology projects receive funding well after the fact.

Nevertheless, here is another one. The Hymenoptera Ontology has received funding from the National Science Foundation. The funding started on April 1, 2009.

You can read more at the NSF site linked above, but here is a brief summary:

This project will bring Hymenoptera researchers together to build a consensus structured vocabulary (the Hymenoptera Anatomy Ontology) that 1) enables discovery of research results from publications, 2) empowers taxonomists to efficiently describe/ diagnose species and 3) provide improved access to information for policy makers, farmers, land managers and the general public.

OWL 2.0 is now a W3C Recommendation

2010-01-20T19:13:00.001-08:00

In followup to a December, 2008 post, OWL 2.0 became a W3C Recommendation on October 27, 2009.

A W3C Recommendation is the final stage of the ratification process of a standard by the World Wide Web Consortium (W3C) working group. Thus, except for errata correction, OWL 2.0 is a final standard.

The OWL 2.0 specification is here.

Ontologies to facilitate revolution in scientific publishing

2010-01-11T14:54:00.000-08:00

In an article in Science entitled Strategic Reading, Ontologies, and the Future of Scientific Publishing, authors Allen Renear and Carole Palmer argue that ontologies will facilitate a revolution in scientific publishing whereby scientists will interact increasingly with the literature on a particular topic as whole and less frequently with entire, individual articles.

They state:

The revolution in scientific publishing that has been promised since the 1980s is about to take place. Scientists have always read strategically, working with many articles simultaneously to search, filter, scan, link, annotate, and analyze fragments of content. An observed recent increase in strategic reading in the online environment will soon be further intensified by two current trends: (i) the widespread use of digital indexing, retrieval, and navigation resources and (ii) the emergence within many scientific disciplines of interoperable ontologies. Accelerated and enhanced by reading tools that take advantage of ontologies, reading practices will become even more rapid and indirect, transforming the ways in which scientists engage the literature and shaping the evolution of scientific publishing.

A key enable of the revolution is the development of scientific ontologies, which serve as computational scientific theories. The authors note that:

Originally motivated by the need for data integration, scientific ontologies are now being explored for STM publishing to support information retrieval and text mining, with applications for hypothesis generation and knowledge discovery well underway.

They also highlight the need for collaborative development of ontologies to ensure interoperability, noting that Although many biological ontologies were originally developed independently, the need for interoperability has driven collaboration, a good example being the Open Biomedical Ontologies (OBO), which currently has 54 participating projects (18), including Microarray Gene Expression Data (MGED), BioPAX, for biological pathways data, and Foundational Model of Anatomy (FMA).

Another ontology project receives funding

2009-12-12T11:18:00.000-08:00

The National Center for Research Resources has awarded (warning: PDF) $998,509 over two years to Northwestern University and the University of Maryland to develop the Disease Ontology. This funding is part of the American Recovery and Reinvestment Act. The principal investigators are Warren Kibbe, PhD of Northwestern University and Lynn Schriml, PhD, from the University of Maryland.

For more information on the Disease Ontology, see:

Disease Ontology wiki
Disease Ontology SourceForge site

The advisors to the project include key members and creators of the Open Biomedical Ontologies Foundry.

ICBO Update

2009-07-25T13:35:00.000-07:00

This week has been a busy one, with lots of events. I finished out the tutorials with a second day of events, powers, and dispositions, referent tracking, a WebProtege tutorial, and a discussion of outstanding issues with respect to Basic Formal Ontology, the Information Artifact Ontology, and the Infectious Disease Ontology.

The conference proper began yesterday. Highlights included a presentation by Stefan Schulz entitled "SNOMED CT's Ontological Commitment". It turns out that SNOMED CT is very unclear about its ontological commitment, which will hamper interoperability. Do so-called 'concepts' in SNOMED CT refer to entries in medical records, situations, or entities in reality?? One can find aspects of all three in SNOMED CT, and they're not clearly delineated and often mixed in the same hierarchy.

Another highlight yesterday was Werner Ceusters' presentation about the eyeGene research database. Again, the information model confuses entities in reality (the L1 Level of Reality), beliefs and hypotheses about L1 entities (the L2 Level of Reality), and information about L1 and L2 entities (the L3 Level of Reality). He recommends that the eyeGene database reform to make careful distinctions among them. And he believes it to be feasible.

A third highlight yesterday was Albert Goldfain's paper on the ontology of resistance, with special attention to methicillin-resistant Staphylococcus aureus (MRSa). He gave a detailed, precise, and high-fidelity representation of resistance.

Today's highlights included a presentation by Harold Solbrig, who gave an account of how he is trying to eliminate use of the word 'concept' in Biomedical Informatics and health care information technology. He nicely demonstrated how the word 'concept' leads otherwise reasonable people to cause all sorts of pathology in their representations (e.g., information models, data models, terminologies, etc). Although he has yet to convince people or the International Standards Organization (ISO) to eliminate the word altogether, by getting them to use 'ConceptDescription' in place of 'Concept', he has been able to limit the carnage.

Chris Mungall led off the day with an excellent paper "Cross-Product Extensions of the Gene Ontology". Because of combinatorial explosion, it is unwise to pre-coordinate every term that one might use from an ontology. However, by exploring the combinatorial space and isolating it from the core ontology, Mungall et al. were able to improve the quality of the core ontology as well as facilitate annotations with post-coordinated terms.

Melanie Courtot gave an excellent presentation (and got the biggest laugh of the day) on "MIREOT: The Minimum Information to Reference an External Ontology Term". Rather than duplicating terms from other ontologies, one wants to use terms from them when defining terms in one's own ontology. However, importing the entire ontology is impractical as they often are quite large. The MIREOT then, is the source ontology URI plus the source term URI plus the source term direct superclass URI. More software support is needed for this approach, but overall it is absolutely the right direction to go.

Later this evening, there is a poster session, dinner, and the plenary keynote. Tomorrow, more paper sessions and concluding remarks.

From the International Conference on Biomedical Ontology

2009-07-20T15:34:00.000-07:00

I am attending the first International Conference on Biomedical Ontology (ICBO) at the University at Buffalo. Today was the first of four days of tutorials before the ICBO officially opens on Friday.

I am taking the "Ontology of Events, Dispositions, and Powers" tutorial, co-taught by Randall Dipert and Neil Williams. Dipert led off in the morning session with a discussion of events. Williams followed in the afternoon with dispositions.

It turns out that defining 'event' without the aid of the modal notions of necessity and possibility is difficult.

And that a proper analysis of dispositions that goes beyond subjunctive conditionals (which alone are insufficient to define dispositions) is nearly impossible without resorting to circularity.

Overall, two excellent sessions.

Funding received for development of chemistry ontology (ChEBI)

2009-07-05T05:22:00.000-07:00

The Biotechnology and Biological Sciences Research Council (BBSRC) of the United Kingdom has awarded a 3 year grant to develop the Chemical Entities of Biological Interest (ChEBI) ontology, and to reform its structure to use Basic Formal Ontology as its upper-level ontology, according to the blog of one of the researchers on the grant.

Christoph Steinbeck, at the European Bioinformatics Institute, on May 19th, wrote:

We received our official award letter from BBSRC Tools and Resources Fund today for the ChEBI ontology development grant. Needless to say, we are thrilled. We are now going to work together with Michael Ashburner’s group at the University of Cambridge to align ChEBI with other OBO Foundry ontologies by adoption of the Basic Formal Ontology and the Relationship Types Ontology.

European "SemanticHEALTH Report" calls for SNOMED CT reform

2009-02-06T11:41:00.000-08:00

In a report (warning: pdf) for the European Commission's ICT for Health organization, the SemanticHEALTH project recommends:

Demonstration of a semantically sound and well quality assured reformulation of one or more suitable subsets of SNOMED CT, in order to provide evidence for long term decisions on the role of SNOMED CT in Europe.

The report criticizes SNOMED CT, saying:

For the time being we must therefore state that SNOMED CT is only fit for purpose as a controlled vocabulary and system of managed identifiers, but it can not yet safely be used as a source of semantics...

Per the International Health Terminology Standards Development Organization (IHTSDO), which owns and maintains SNOMED CT:

The focus is on enabling the implementation of semantically accurate health records that are interoperable.

If the report's criticism is true (and we believe it is), then SNOMED CT is not fit for its primary purpose.

Duke and SUNY at Buffalo get grant to build ontology

2009-01-26T18:22:00.000-08:00

The National Institute for Allergy and Infectious Diseases (NIAID) has awarded Duke University a $1.25 million grant to develop the Infectious Disease Ontology (IDO). SUNY at Buffalo receives a $250,000 subcontract under the award.

The goal of the grant is to create an ontology of the bacterium Staphylococcus aureus, and its related genes, proteins, capsule, pathophysiology, and diseases. If researchers from multiple institutions all encode their data using IDO, then they can combine their data sets more easily to generate new scientific knowledge.

The grant represents something of a novelty for the National Institutes of Health (one of which is NIAID), because it issues few grants or requests for proposals with a focus of ontology development. Congratulations to the researchers involved, and we wish them success, as their success could determine whether the NIH funds similar work.

OWL 2.0 inches closer to completion

2008-12-11T07:44:00.000-08:00

The OWL Working Group (OWG) of W3C, the standards-setting body for the Internet, published 11 documents on OWL 2.0 for comment on December 2. Six of the documents are last call working draft documents, and the remaining five are first public working draft documents.

The OWG is soliciting comments from the public. They are due by January 23, 2009.

OWL 2.0 is the next version of the Web Ontology Language (OWL) standard. Per the Charter Document for the OWG, OWL 2.0 makes the following changes to the previous version of OWL:

The extensions, referred to as OWL 1.1, fall into the following categories:

Extensions to the logic underlying OWL, adding new constructs that extend the expressivity of OWL (e.g., qualified cardinality restrictions and property chain inclusion axioms).
Extensions to the datatype support provided by OWL, e.g., with XML Schema Datatype semantics and datatype facets.
Additional syntactic facilities that do not extend the expressive power of OWL but that make some common modelling paradigms easier to express (e.g., disjoint unions).

The Working Group will also define a set of language fragments—profiles, or subsets of the language—that have been identified as having interesting or useful properties (e.g., being easier to implement). Fragments may include some of the extensions that the Working Group adopts. One of the first tasks of the Working Group will be to determine how subsets are to be defined.

The next step in the process for the last call working draft documents is to become a Candidate Recommendation. Before becoming final, Candidate Recommendations go on to become Proposed Recommendations and then finally W3C Recommendations.

The Purpose of this Blog

2008-12-10T10:53:00.000-08:00

The purpose of this blog is bring the latest developments in the world of ontology into one place for information, discussion, and dissemination.

To get an idea of what this blog is (or will be) about, here are some links, in no particular order:

Wikipedia definition of ontology
Wikipedia definition of applied ontology (we'll spend most of our time on applied ontology)
The homepage of Dr. Barry Smith at the University at Buffalo
The Open Biomedical Ontologies (OBO) Foundry
The Gene Ontology
The Foundational Model of Anatomy (FMA) Ontology
The Protege open-source ontology development tool
The W3C Web Ontology Language (OWL) standard
The Ontolog Forum
The Formal Ontology in Information Systems (FOIS) conference series
The National Center for Biomedical Ontology (NCBO)
The NCBO Dissemination Wiki