What is an ontology?

The idea of "Ontology" is an idea borrowed from philosophy, and it is used to — as an abstract noun — represents branches of Philosophy that discuss "existence." But in Information Science, an "ontology" — as a concrete noun — is a way of showing the properties of a subject area and how they are related, by defining a set of terms and relational expressions that represent the entities in that subject area.

In i2b2's domain of Clinical Research Informatics, an ontology is a collection of healthcare-related "concepts," that define a set of terms representing the various categories of clinical and translational science. Categories such as demographics, diagnoses, procedures, laboratory tests, and medications are described as "concepts" in an i2b2 ontology.

Unlike some other ontologies in Information Science, an i2b2 ontology does not define relational expressions among the concepts or terms. Therefore, strictly speaking, an i2b2 ontology the realm of i2b2, an ontology is actually a "taxonomy," which is a hierarchical group of terms or concepts, without any relational expressions among them.

For instance, if . If you recall (from your high-school biology class) Linnaeus's "binomial nomenclature" model of how to name living organisms, then you already know what a taxonomy is. For instance, the common house fly Musca domestica and other flies in the family Muscidae are members of the order Diptera, which are organisms in the class Insecta, phylum Arthropoda, kingdom Animalia. A taxonomy defines the hierarchical "is-a" relationship between two concepts. LikewiseSimilarly, a Camry is a Toyota, which is an automobile, which is a type of motorized, wheeled conveyance.

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An i2b2 instance requires an ontology so that researchers can locate "concepts" of interest and query data.locate patients whose medical records contain these "concepts."

The medical healthcare concepts contained in an the ontology are essentially the building blocks of an i2b2 query:
This is what “drives” . The i2b2 ontology is represented in the upper-left corner of the i2b2 webclient . In order to make facts or observations you wish to load into your i2b2 query-able, you must have corresponding entries in your ontology (that account for the codes used to represent these facts or observations)(user interface). See the screenshot below.

These concepts are rendered as a collection of nested folders and are assumed to generally represent child-parent (or is-a) relationships. Researchers may locate these concepts by using a hierarchical tree, or taxonomy. When you log in to the demo i2b2 site (username "demo", password "demouser" are already filled in), you will see the i2b2 ontology tree on the upper-left side of the user interface. We also refer to that listing as a group of ontologies, where each domain category or top-level taxonomy is called an ontology in its own right. 

In this screenshot, we would say that i2b2 is displaying an ontology tree with 13 top-level ontologies ontology trees or domainscategories, namely: Clinical Trials, Custom Metadata, Demographics, Diagnoses, etc.

For instance:

• diabetes mellitus is an endocrine disorder, which is a type of diagnosis; it will be found in both the "Diagnoses" tree and in the "Diagnoses (ICD10)" tree;
• aspirin is a non-steroidal anti-inflammatory drug, which is a type of medication; it will be found in the "Medications" tree;
• tonsillectomy is a type of surgery, which is a procedure; it will be found in the "Procedures" tree;
• hemoglobin A1c is a blood test, which is a type of laboratory test; it will be found in the "Laboratory Tests" tree; and
• gender or sex race is a patient-demographic descriptor; it will be found in the "Demographics" tree.

Here is another screenshot, where you can see the hierarchy for "Race" in the "Demographics" tree:

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How does it work? How does the i2b2 ontology make the patient data queryable?

A) The ontology is made up of medical concepts. The ontology is visible to researchers through the webclient, and each medical concept in the ontology includes specific code(s) that match medical observation facts (such as diagnoses, medications, procedures, etc). A researcher can select concepts they are interested in to build a query, and medical data that matches those concepts' codes will be counted.

First, a little more terminology. The i2b2 "patient data" are stored in the Clinical Research Chart database, or "CRC database." The ontology of concepts that describe those patient data is known as the "metadata." The metadata or ontology is stored in the Metadata database, or "ONT database."

The i2b2 metadata in the ONT database work B) The i2b2 ontology in the i2b2 metadata database works together with the patient data in the i2b2 CRC database. Each patient "observation" in the CRC database must have a code associated with it, and that code must match a healthcare concept — diagnosis, procedure, medication, lab test, demographic descriptor, etc. — that exists in the metadata database. So the CRC patient data will be queryable in i2b2 only if the patient facts in the CRC database are recorded utilizing standard codes that are referenced in the i2b2 metadata (ontology trees).

For instance, if the patient's electronic health record indicates that the patient had the procedure "tonsillectomy with adenoidectomy," then that fact needs to be recorded in the CRC database  using the standard code for that particular procedure. In the case of using the default i2b2 Procedures metadata tree, that code would be "ICD9:28.3". So the CRC patient data will be queryable in i2b2 only if the patient facts in the CRC database are recorded utilizing standard codes that are referenced in the i2b2 metadata (ontology trees).

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A query in the user interface for "tonsillectomy with adenoidectomy" will be translated by i2b2 into a query in the database for patients who have the code ICD9:28.3 in their CRC data records.

A) The ontology is made up of medical concepts. The ontology is visible to researchers through the webclient, and each medical concept in the ontology includes specific code(s) that match medical observation facts (such as diagnoses, medications, procedures, etc). A researcher can select concepts they are interested in to build a query, and medical data that matches those concepts' codes will be counted.

Where did the i2b2 ontology "concepts" come from?

Typically, the concepts that make up the various categories or "domains" are based on medical terminology standards published by various institutions. Concepts can also be created ad hoc for a specific i2b2 instance by the i2b2 administrator at that site. (For more information on custom metadata, please see Ontologies 201.)

The . Some commonly used standards to represent representing basic structured clinical patient data collected in EHRs include:

Do all i2b2 instances always have the same ontology?

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