Evidence map›Paper›PMID 36758001›Full record

ArticlePloS one2023

A generalized classification and coding system of Human Disease Animal Model Resource data with a case study to show improving database retrieval efficiency.

Huiping Li, Wenjuan Zhang

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Huiping LiGuangdong Laboratory Animals Monitoring Institute, Guangdong Key Laboratory of Laboratory Animals, Guangzhou, Guangdong, China.ORCID 0000-0003-2268-5293
Wenjuan ZhangSchool of Information Science and Technology, School of Cyber Security, Guangdong University of Foreign Studies, Guangzhou Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCurrently there is no unified data classification and coding standard for the existing human disease animal model resource data worldwide. Different data classification and coding systems produce different retrieval methods. Some of these methods are inefficient and difficult to use. This research investigated the rules for the classification and coding of such data based on the Replication Methodology of Animal Models for Human Disease, the Classification and Coding Rules for Health Information Data Set (WS/T 306-2009), the Science and Technology Resource Identification (GB/T 32843-2016), the Scientific Data Management Measures (000014349/2018-00052), and The Generic Description Specification for Natural Science and Technology Resources. This research aimed to develop a classification and coding system for data obtained from human disease animal model resource based on the Internet environment to provide a standardized and unified foundation for the collection, saving, retrieval, and sharing of data from this resource.

resultsA complete data classification and coding table compiled in the form of letters and numbers was produced, with a classification infrastructure that expanded layer by layer according to the three dimensions (namely, system diseases, animal species, and modeling methods) and essential attributes. When necessary, it adopted the hierarchy of major, intermediate, and minor categories for certain layer and also one-to-one matched the code and classification result.

conclusionThrough this study, a sharing and joint construction mechanism for data from this resource can be developed by all research institutes in this field. As a case study, this research also offered technical support for constructing the database for the National Human Disease Animal Model Resource Center. The technological innovation of this paper is to derive a research oriented retrieval method, which provides technical support for the research on the current COVID-19 epidemic and on possible future epidemics.

Indexed as

COVID-19Data ManagementAnimalsDatabases, FactualHumansModels, Animal

Identifiers

PMID36758001
PMCPMC9910694

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.