An object identifier is anything associated with the object that persists throughout the life of the object
and that is unique to the object (ie, does not belong to any other object). Everyone is familiar with
biometric identifiers, such as fingerprints, iris patterns, and genome sequences. In the case of data objects,
the identifier usually refers to a randomly chosen long sequence of numbers and letters that is
permanently assigned to the object and that is never assigned to any other data object (see Glossary
item, Data object).
An identifier system is a set of data-related protocols that satisfy the following conditions: (1) Completeness
(ie, every unique object has an identifier); (2) Uniqueness (ie, each identifier is a unique sequence);
(3) Exclusivity (ie, each identifier is assigned to only one unique object and to no other object,
ever); (4) Authenticity (ie, objects that receive identification can be verified as the objects that they are
intended to be); (5) Aggregation (ie, all information associated with an identifier can be collected); and
(6) Permanence (ie, an identifier is never deleted).
- Jules Berman (copyrighted material)
key words: identifier, identification, uniqueness, data object, jules j berman
Showing posts with label data object. Show all posts
Showing posts with label data object. Show all posts
Tuesday, January 19, 2016
Thursday, March 8, 2007
Specifications versus Standards
In a prior blog I suggested 16 ways that SDOs (Standards Development Organizations) can protect their standards from embedded patents. Suggestion 12 was "Make specifications, not standards."
This suggestion, I'm sure, is cryptic to most people. A major theme of this blog site is that specifications are different from standards and have a number of features that make them more suitable than standards for describing and exchanging many types of biomedical information.
Though informaticians often use the terms "specification" and "standard" interchangeably, a specification is just a formal way (usually employing RDF) of describing any data object. A data standard is a set of requirements, created by an SDO, that comprise a pre-determined content and format for a set of data related to a very specific kind of data object.
Features of a "specified" object:
1. Anyone can understand the composition and construction of the object
2. If the object is unique, anyone can distinguish the object from all other objects.
3. If the object falls into a known class of objects, anyone can determine, from the specification, the class of the object.
A specification serves most of the purposes of a standard, and much more (data description, data exchange, data merging, data interoperability, semantic logic). Data specifications spare us most of the heavy baggage that comes with a standard (limited flexibility to include changing data objects, locked-in data descriptors, licensing and other intellectual property issues, competing standards for the same domain resulting in limited interoperability, bureaucratic overhead, etc.).
Readers of this blog might want to read an introduction to RDF data specifications written by myself and Dr. G. William Moore. I believe that standards are important, but that specifications are even more important. There are instances in the field of biomedical informatics where specifications could serve better than standards. This was a developed theme in my book, Biomedical Informatics.I hope to provide many examples of specifications (how they are created and used) in future blogs here.
-Jules Berman
Science is not a collection of facts. Science is what facts teach us; what we can learn about our universe, and ourselves, by deductive thinking. From observations of the night sky, made without the aid of telescopes, we can deduce that the universe is expanding, that the universe is not infinitely old, and why black holes exist. Without resorting to experimentation or mathematical analysis, we can deduce that gravity is a curvature in space-time, that the particles that compose light have no mass, that there is a theoretical limit to the number of different elements in the universe, and that the earth is billions of years old. Likewise, simple observations on animals tell us much about the migration of continents, the evolutionary relationships among classes of animals, why the nuclei of cells contain our genetic material, why certain animals are long-lived, why the gestation period of humans is 9 months, and why some diseases are rare and other diseases are common. In “Armchair Science”, the reader is confronted with 129 scientific mysteries, in cosmology, particle physics, chemistry, biology, and medicine. Beginning with simple observations, step-by-step analyses guide the reader toward solutions that are sometimes startling, and always entertaining. “Armchair Science” is written for general readers who are curious about science, and who want to sharpen their deductive skills.
This suggestion, I'm sure, is cryptic to most people. A major theme of this blog site is that specifications are different from standards and have a number of features that make them more suitable than standards for describing and exchanging many types of biomedical information.
Though informaticians often use the terms "specification" and "standard" interchangeably, a specification is just a formal way (usually employing RDF) of describing any data object. A data standard is a set of requirements, created by an SDO, that comprise a pre-determined content and format for a set of data related to a very specific kind of data object.
Features of a "specified" object:
1. Anyone can understand the composition and construction of the object
2. If the object is unique, anyone can distinguish the object from all other objects.
3. If the object falls into a known class of objects, anyone can determine, from the specification, the class of the object.
A specification serves most of the purposes of a standard, and much more (data description, data exchange, data merging, data interoperability, semantic logic). Data specifications spare us most of the heavy baggage that comes with a standard (limited flexibility to include changing data objects, locked-in data descriptors, licensing and other intellectual property issues, competing standards for the same domain resulting in limited interoperability, bureaucratic overhead, etc.).
Readers of this blog might want to read an introduction to RDF data specifications written by myself and Dr. G. William Moore. I believe that standards are important, but that specifications are even more important. There are instances in the field of biomedical informatics where specifications could serve better than standards. This was a developed theme in my book, Biomedical Informatics.I hope to provide many examples of specifications (how they are created and used) in future blogs here.
-Jules Berman
Science is not a collection of facts. Science is what facts teach us; what we can learn about our universe, and ourselves, by deductive thinking. From observations of the night sky, made without the aid of telescopes, we can deduce that the universe is expanding, that the universe is not infinitely old, and why black holes exist. Without resorting to experimentation or mathematical analysis, we can deduce that gravity is a curvature in space-time, that the particles that compose light have no mass, that there is a theoretical limit to the number of different elements in the universe, and that the earth is billions of years old. Likewise, simple observations on animals tell us much about the migration of continents, the evolutionary relationships among classes of animals, why the nuclei of cells contain our genetic material, why certain animals are long-lived, why the gestation period of humans is 9 months, and why some diseases are rare and other diseases are common. In “Armchair Science”, the reader is confronted with 129 scientific mysteries, in cosmology, particle physics, chemistry, biology, and medicine. Beginning with simple observations, step-by-step analyses guide the reader toward solutions that are sometimes startling, and always entertaining. “Armchair Science” is written for general readers who are curious about science, and who want to sharpen their deductive skills.
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