ISO/DIS 16843-2

Health informatics — Categorial structures for representation of acupuncture — Part 2: Needling

Scope

The purpose of ISO/TS 16843-2:2015 is to specify categorial structures within the subject field of acupuncture by defining a set of domain constraints for use within terminological resources.
This Technical Specification describes a concept system detailing domain constraints of sanctioned characteristics, each composed of a semantic link and an applicable characterizing category.
The potential benefits of ISO/TS 16843-2:2015 include:
a) support for developers of new terminology systems concerning acupuncture needling;
b) support for developers of new detailed content areas of existing terminology systems concerning acupuncture needling procedures to ensure accuracy, repeatability and comparability;
c) facilitating the representation of acupuncture needling procedures using a standard core model in a manner suitable for computer processing;
d) providing a conceptual framework for the generation of compositional concept representation of acupuncture needling;
e) facilitating the mapping and improved semantic correspondence between different terminologies by proposing a core specification for acupuncture needling;
f) providing a core model to describe the structure of acupuncture, and facilitate improved semantic correspondence with information models;
g) providing a tool for acupuncture text mining, database construction, ancient documents processing and wide area of acupuncture information collection and processing;
h) providing a new method for researchers to conduct relevant research, and ideas for the development of acupuncture disciplines.
Target groups include:
- stakeholders such as companies that offer systems that incorporate Electronic Categorial Structures, by helping building knowledge databases or automatic processing of medical literature, and
- doctors, who can be better assisted with knowledge and documentation of needling procedures.
This Technical Specification can also be used in clinical decision support and to help in data mining for researchers.