The ACGT Master Ontology and its applications – Towards an ontology-driven cancer research and management system
Objective: This paper introduces the objectives, methods and results of ontology development in the EU co-funded project Advancing Clinico-genomic Trials on Cancer – Open Grid Services for Improving Medical Knowledge Discovery (ACGT). While the available data in the life sciences has recently grown...
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Veröffentlicht in: | Journal of biomedical informatics 2011-02, Vol.44 (1), p.8-25 |
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creator | Brochhausen, Mathias Spear, Andrew D. Cocos, Cristian Weiler, Gabriele Martín, Luis Anguita, Alberto Stenzhorn, Holger Daskalaki, Evangelia Schera, Fatima Schwarz, Ulf Sfakianakis, Stelios Kiefer, Stephan Dörr, Martin Graf, Norbert Tsiknakis, Manolis |
description | Objective: This paper introduces the objectives, methods and results of ontology development in the EU co-funded project Advancing Clinico-genomic Trials on Cancer – Open Grid Services for Improving Medical Knowledge Discovery (ACGT). While the available data in the life sciences has recently grown both in amount and quality, the full exploitation of it is being hindered by the use of different underlying technologies, coding systems, category schemes and reporting methods on the part of different research groups. The goal of the ACGT project is to contribute to the resolution of these problems by developing an ontology-driven, semantic grid services infrastructure that will enable efficient execution of discovery-driven scientific workflows in the context of multi-centric, post-genomic clinical trials. The focus of the present paper is the ACGT Master Ontology (MO).
Methods: ACGT project researchers undertook a systematic review of existing domain and upper-level ontologies, as well as of existing ontology design software, implementation methods, and end-user interfaces. This included the careful study of best practices, design principles and evaluation methods for ontology design, maintenance, implementation, and versioning, as well as for use on the part of domain experts and clinicians.
Results: To date, the results of the ACGT project include (i) the development of a master ontology (the ACGT-MO) based on clearly defined principles of ontology development and evaluation; (ii) the development of a technical infrastructure (the ACGT Platform) that implements the ACGT-MO utilizing independent tools, components and resources that have been developed based on open architectural standards, and which includes an application updating and evolving the ontology efficiently in response to end-user needs; and (iii) the development of an Ontology-based Trial Management Application (ObTiMA) that integrates the ACGT-MO into the design process of clinical trials in order to guarantee automatic semantic integration without the need to perform a separate mapping process. |
doi_str_mv | 10.1016/j.jbi.2010.04.008 |
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Methods: ACGT project researchers undertook a systematic review of existing domain and upper-level ontologies, as well as of existing ontology design software, implementation methods, and end-user interfaces. This included the careful study of best practices, design principles and evaluation methods for ontology design, maintenance, implementation, and versioning, as well as for use on the part of domain experts and clinicians.
Results: To date, the results of the ACGT project include (i) the development of a master ontology (the ACGT-MO) based on clearly defined principles of ontology development and evaluation; (ii) the development of a technical infrastructure (the ACGT Platform) that implements the ACGT-MO utilizing independent tools, components and resources that have been developed based on open architectural standards, and which includes an application updating and evolving the ontology efficiently in response to end-user needs; and (iii) the development of an Ontology-based Trial Management Application (ObTiMA) that integrates the ACGT-MO into the design process of clinical trials in order to guarantee automatic semantic integration without the need to perform a separate mapping process.</description><identifier>ISSN: 1532-0464</identifier><identifier>EISSN: 1532-0480</identifier><identifier>DOI: 10.1016/j.jbi.2010.04.008</identifier><identifier>PMID: 20438862</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Animals ; Cancer research ; Clinical trial administration ; Computational Biology ; Database Management Systems ; Databases, Factual ; Humans ; Medical Informatics ; Medical Oncology ; Neoplasms ; Ontological engineering ; Ontology ; Translational medicine ; Vocabulary, Controlled</subject><ispartof>Journal of biomedical informatics, 2011-02, Vol.44 (1), p.8-25</ispartof><rights>2010 Elsevier Inc.</rights><rights>Copyright © 2010 Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c482t-30978210160295cb085108a4862635a40e50ea1a4b9db46ad2f6b24091ebeafd3</citedby><cites>FETCH-LOGICAL-c482t-30978210160295cb085108a4862635a40e50ea1a4b9db46ad2f6b24091ebeafd3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jbi.2010.04.008$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,315,781,785,886,3551,27929,27930,46000</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20438862$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Brochhausen, Mathias</creatorcontrib><creatorcontrib>Spear, Andrew D.</creatorcontrib><creatorcontrib>Cocos, Cristian</creatorcontrib><creatorcontrib>Weiler, Gabriele</creatorcontrib><creatorcontrib>Martín, Luis</creatorcontrib><creatorcontrib>Anguita, Alberto</creatorcontrib><creatorcontrib>Stenzhorn, Holger</creatorcontrib><creatorcontrib>Daskalaki, Evangelia</creatorcontrib><creatorcontrib>Schera, Fatima</creatorcontrib><creatorcontrib>Schwarz, Ulf</creatorcontrib><creatorcontrib>Sfakianakis, Stelios</creatorcontrib><creatorcontrib>Kiefer, Stephan</creatorcontrib><creatorcontrib>Dörr, Martin</creatorcontrib><creatorcontrib>Graf, Norbert</creatorcontrib><creatorcontrib>Tsiknakis, Manolis</creatorcontrib><title>The ACGT Master Ontology and its applications – Towards an ontology-driven cancer research and management system</title><title>Journal of biomedical informatics</title><addtitle>J Biomed Inform</addtitle><description>Objective: This paper introduces the objectives, methods and results of ontology development in the EU co-funded project Advancing Clinico-genomic Trials on Cancer – Open Grid Services for Improving Medical Knowledge Discovery (ACGT). While the available data in the life sciences has recently grown both in amount and quality, the full exploitation of it is being hindered by the use of different underlying technologies, coding systems, category schemes and reporting methods on the part of different research groups. The goal of the ACGT project is to contribute to the resolution of these problems by developing an ontology-driven, semantic grid services infrastructure that will enable efficient execution of discovery-driven scientific workflows in the context of multi-centric, post-genomic clinical trials. The focus of the present paper is the ACGT Master Ontology (MO).
Methods: ACGT project researchers undertook a systematic review of existing domain and upper-level ontologies, as well as of existing ontology design software, implementation methods, and end-user interfaces. This included the careful study of best practices, design principles and evaluation methods for ontology design, maintenance, implementation, and versioning, as well as for use on the part of domain experts and clinicians.
Results: To date, the results of the ACGT project include (i) the development of a master ontology (the ACGT-MO) based on clearly defined principles of ontology development and evaluation; (ii) the development of a technical infrastructure (the ACGT Platform) that implements the ACGT-MO utilizing independent tools, components and resources that have been developed based on open architectural standards, and which includes an application updating and evolving the ontology efficiently in response to end-user needs; and (iii) the development of an Ontology-based Trial Management Application (ObTiMA) that integrates the ACGT-MO into the design process of clinical trials in order to guarantee automatic semantic integration without the need to perform a separate mapping process.</description><subject>Animals</subject><subject>Cancer research</subject><subject>Clinical trial administration</subject><subject>Computational Biology</subject><subject>Database Management Systems</subject><subject>Databases, Factual</subject><subject>Humans</subject><subject>Medical Informatics</subject><subject>Medical Oncology</subject><subject>Neoplasms</subject><subject>Ontological engineering</subject><subject>Ontology</subject><subject>Translational medicine</subject><subject>Vocabulary, Controlled</subject><issn>1532-0464</issn><issn>1532-0480</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkcFuEzEQhlcIREvhAbgg3zhtGHttxyskpCqiBamol3C2Zr2TxNHuOtibVLnxDrwhT1KHhAgucLKt-eebf_wXxWsOEw5cv1tP1o2fCMhvkBMA86S45KoSJUgDT893LS-KFymtAThXSj8vLgTIyhgtLos4XxG7nt3O2RdMI0V2P4yhC8s9w6FlfkwMN5vOOxx9GBL7-f0Hm4cHjG0uDCycxGUb_Y4G5nBwmREpEUa3-sXoccAl9TSMLO3ziP5l8WyBXaJXp_Oq-HrzcT77VN7d336eXd-VThoxlhXUUyMOe4KolWvAKA4GZbatK4USSAEhR9nUbSM1tmKhGyGh5tQQLtrqqvhw5G62TU-tyw4idnYTfY9xbwN6-3dl8Cu7DDurpkqpGjLg7QkQw7ctpdH2PjnqOhwobJM1ujagtRD_Vyqp9NSoaVbyo9LFkFKkxdkPB3tY1q5tDtUeQrUgbQ4197z5c5Fzx-8Us-D9UUD5O3eeok3OU46i9ZHcaNvg_4F_BGB5tF4</recordid><startdate>20110201</startdate><enddate>20110201</enddate><creator>Brochhausen, Mathias</creator><creator>Spear, Andrew D.</creator><creator>Cocos, Cristian</creator><creator>Weiler, Gabriele</creator><creator>Martín, Luis</creator><creator>Anguita, Alberto</creator><creator>Stenzhorn, Holger</creator><creator>Daskalaki, Evangelia</creator><creator>Schera, Fatima</creator><creator>Schwarz, Ulf</creator><creator>Sfakianakis, Stelios</creator><creator>Kiefer, Stephan</creator><creator>Dörr, Martin</creator><creator>Graf, Norbert</creator><creator>Tsiknakis, Manolis</creator><general>Elsevier Inc</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>5PM</scope></search><sort><creationdate>20110201</creationdate><title>The ACGT Master Ontology and its applications – Towards an ontology-driven cancer research and management system</title><author>Brochhausen, Mathias ; Spear, Andrew D. ; Cocos, Cristian ; Weiler, Gabriele ; Martín, Luis ; Anguita, Alberto ; Stenzhorn, Holger ; Daskalaki, Evangelia ; Schera, Fatima ; Schwarz, Ulf ; Sfakianakis, Stelios ; Kiefer, Stephan ; Dörr, Martin ; Graf, Norbert ; Tsiknakis, Manolis</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c482t-30978210160295cb085108a4862635a40e50ea1a4b9db46ad2f6b24091ebeafd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Animals</topic><topic>Cancer research</topic><topic>Clinical trial administration</topic><topic>Computational Biology</topic><topic>Database Management Systems</topic><topic>Databases, Factual</topic><topic>Humans</topic><topic>Medical Informatics</topic><topic>Medical Oncology</topic><topic>Neoplasms</topic><topic>Ontological engineering</topic><topic>Ontology</topic><topic>Translational medicine</topic><topic>Vocabulary, Controlled</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Brochhausen, Mathias</creatorcontrib><creatorcontrib>Spear, Andrew D.</creatorcontrib><creatorcontrib>Cocos, Cristian</creatorcontrib><creatorcontrib>Weiler, Gabriele</creatorcontrib><creatorcontrib>Martín, Luis</creatorcontrib><creatorcontrib>Anguita, Alberto</creatorcontrib><creatorcontrib>Stenzhorn, Holger</creatorcontrib><creatorcontrib>Daskalaki, Evangelia</creatorcontrib><creatorcontrib>Schera, Fatima</creatorcontrib><creatorcontrib>Schwarz, Ulf</creatorcontrib><creatorcontrib>Sfakianakis, Stelios</creatorcontrib><creatorcontrib>Kiefer, Stephan</creatorcontrib><creatorcontrib>Dörr, Martin</creatorcontrib><creatorcontrib>Graf, Norbert</creatorcontrib><creatorcontrib>Tsiknakis, Manolis</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of biomedical informatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Brochhausen, Mathias</au><au>Spear, Andrew D.</au><au>Cocos, Cristian</au><au>Weiler, Gabriele</au><au>Martín, Luis</au><au>Anguita, Alberto</au><au>Stenzhorn, Holger</au><au>Daskalaki, Evangelia</au><au>Schera, Fatima</au><au>Schwarz, Ulf</au><au>Sfakianakis, Stelios</au><au>Kiefer, Stephan</au><au>Dörr, Martin</au><au>Graf, Norbert</au><au>Tsiknakis, Manolis</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The ACGT Master Ontology and its applications – Towards an ontology-driven cancer research and management system</atitle><jtitle>Journal of biomedical informatics</jtitle><addtitle>J Biomed Inform</addtitle><date>2011-02-01</date><risdate>2011</risdate><volume>44</volume><issue>1</issue><spage>8</spage><epage>25</epage><pages>8-25</pages><issn>1532-0464</issn><eissn>1532-0480</eissn><abstract>Objective: This paper introduces the objectives, methods and results of ontology development in the EU co-funded project Advancing Clinico-genomic Trials on Cancer – Open Grid Services for Improving Medical Knowledge Discovery (ACGT). While the available data in the life sciences has recently grown both in amount and quality, the full exploitation of it is being hindered by the use of different underlying technologies, coding systems, category schemes and reporting methods on the part of different research groups. The goal of the ACGT project is to contribute to the resolution of these problems by developing an ontology-driven, semantic grid services infrastructure that will enable efficient execution of discovery-driven scientific workflows in the context of multi-centric, post-genomic clinical trials. The focus of the present paper is the ACGT Master Ontology (MO).
Methods: ACGT project researchers undertook a systematic review of existing domain and upper-level ontologies, as well as of existing ontology design software, implementation methods, and end-user interfaces. This included the careful study of best practices, design principles and evaluation methods for ontology design, maintenance, implementation, and versioning, as well as for use on the part of domain experts and clinicians.
Results: To date, the results of the ACGT project include (i) the development of a master ontology (the ACGT-MO) based on clearly defined principles of ontology development and evaluation; (ii) the development of a technical infrastructure (the ACGT Platform) that implements the ACGT-MO utilizing independent tools, components and resources that have been developed based on open architectural standards, and which includes an application updating and evolving the ontology efficiently in response to end-user needs; and (iii) the development of an Ontology-based Trial Management Application (ObTiMA) that integrates the ACGT-MO into the design process of clinical trials in order to guarantee automatic semantic integration without the need to perform a separate mapping process.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>20438862</pmid><doi>10.1016/j.jbi.2010.04.008</doi><tpages>18</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Animals Cancer research Clinical trial administration Computational Biology Database Management Systems Databases, Factual Humans Medical Informatics Medical Oncology Neoplasms Ontological engineering Ontology Translational medicine Vocabulary, Controlled |
title | The ACGT Master Ontology and its applications – Towards an ontology-driven cancer research and management system |
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