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      Knowledge Management Framework for Emerging Infectious Diseases Preparedness and Response: Design and Development of Public Health Document Ontology

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          Abstract

          Background

          There are increasing concerns about our preparedness and timely coordinated response across the globe to cope with emerging infectious diseases (EIDs). This poses practical challenges that require exploiting novel knowledge management approaches effectively.

          Objective

          This work aims to develop an ontology-driven knowledge management framework that addresses the existing challenges in sharing and reusing public health knowledge.

          Methods

          We propose a systems engineering-inspired ontology-driven knowledge management approach. It decomposes public health knowledge into concepts and relations and organizes the elements of knowledge based on the teleological functions. Both knowledge and semantic rules are stored in an ontology and retrieved to answer queries regarding EID preparedness and response.

          Results

          A hybrid concept extraction was implemented in this work. The quality of the ontology was evaluated using the formal evaluation method Ontology Quality Evaluation Framework.

          Conclusions

          Our approach is a potentially effective methodology for managing public health knowledge. Accuracy and comprehensiveness of the ontology can be improved as more knowledge is stored. In the future, a survey will be conducted to collect queries from public health practitioners. The reasoning capacity of the ontology will be evaluated using the queries and hypothetical outbreaks. We suggest the importance of developing a knowledge sharing standard like the Gene Ontology for the public health domain.

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          Most cited references64

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Spatial epidemiology: an emerging (or re-emerging) discipline.

            Spatial epidemiology is the study of spatial variation in disease risk or incidence. Several ecological processes can result in strong spatial patterns of such risk or incidence: for example, pathogen dispersal might be highly localized, vectors or reservoirs for pathogens might be spatially restricted, or susceptible hosts might be clumped. Here, we briefly describe approaches to spatial epidemiology that are spatially implicit, such as metapopulation models of disease transmission, and then focus on research in spatial epidemiology that is spatially explicit, such as the creation of risk maps for particular geographical areas. Although the spatial dynamics of infectious diseases are the subject of intensive study, the impacts of landscape structure on epidemiological processes have so far been neglected. The few studies that demonstrate how landscape composition (types of elements) and configuration (spatial positions of those elements) influence disease risk or incidence suggest that a true integration of landscape ecology with epidemiology will be fruitful.
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              • Article: not found

              Crossing the Quality Chasm: A New Health System for the 21st Century

              B. Bloom (2002)
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                Author and article information

                Contributors
                Journal
                JMIR Res Protoc
                JMIR Res Protoc
                ResProt
                JMIR Research Protocols
                JMIR Publications (Toronto, Canada )
                1929-0748
                October 2017
                11 October 2017
                : 6
                : 10
                : e196
                Affiliations
                [1] 1 Fu Foundation School of Engineering and Applied Science Department of Chemical Engineering Columbia University New York, NY United States
                [2] 2 Mailman School of Public Health Department of Epidemiology Columbia University New York, NY United States
                [3] 3 Center for the Management of Systemic Risk Columbia University New York, NY United States
                Author notes
                Corresponding Author: Venkat Venkatasubramanian venkat@ 123456columbia.edu
                Author information
                http://orcid.org/0000-0002-6192-0789
                http://orcid.org/0000-0001-6318-9523
                http://orcid.org/0000-0002-5434-5683
                http://orcid.org/0000-0002-4923-0582
                Article
                v6i10e196
                10.2196/resprot.7904
                5656775
                29021130
                06b3c87e-e38d-412b-a4e7-c6f3f495ed61
                ©Zhizun Zhang, Mila C Gonzalez, Stephen S Morse, Venkat Venkatasubramanian. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 11.10.2017.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included.

                History
                : 5 May 2017
                : 30 May 2017
                : 19 July 2017
                : 11 September 2017
                Categories
                Original Paper
                Original Paper

                eids,public health,systems engineering,knowledge representation,teleological function,knowledge management,ontology,semantic reasoning

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