Web-based interactive mapping from data dictionaries to ontologies, with an application to cancer registry
Abstract Background The Kentucky Cancer Registry (KCR) is a central cancer registry for the state of Kentucky that receives data about incident cancer cases from all healthcare facilities in the state within 6 months of diagnosis. Similar to all other U.S. and Canadian cancer registries, KCR uses a...
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| Format: | Article |
| Language: | English |
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BMC
2020-12-01
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| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12911-020-01288-7 |
| _version_ | 1818610005152104448 |
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| author | Shiqiang Tao Ningzhou Zeng Isaac Hands Joseph Hurt-Mueller Eric B. Durbin Licong Cui Guo-Qiang Zhang |
| author_facet | Shiqiang Tao Ningzhou Zeng Isaac Hands Joseph Hurt-Mueller Eric B. Durbin Licong Cui Guo-Qiang Zhang |
| author_sort | Shiqiang Tao |
| collection | DOAJ |
| description | Abstract Background The Kentucky Cancer Registry (KCR) is a central cancer registry for the state of Kentucky that receives data about incident cancer cases from all healthcare facilities in the state within 6 months of diagnosis. Similar to all other U.S. and Canadian cancer registries, KCR uses a data dictionary provided by the North American Association of Central Cancer Registries (NAACCR) for standardized data entry. The NAACCR data dictionary is not an ontological system. Mapping between the NAACCR data dictionary and the National Cancer Institute (NCI) Thesaurus (NCIt) will facilitate the enrichment, dissemination and utilization of cancer registry data. We introduce a web-based system, called Interactive Mapping Interface (IMI), for creating mappings from data dictionaries to ontologies, in particular from NAACCR to NCIt. Method IMI has been designed as a general approach with three components: (1) ontology library; (2) mapping interface; and (3) recommendation engine. The ontology library provides a list of ontologies as targets for building mappings. The mapping interface consists of six modules: project management, mapping dashboard, access control, logs and comments, hierarchical visualization, and result review and export. The built-in recommendation engine automatically identifies a list of candidate concepts to facilitate the mapping process. Results We report the architecture design and interface features of IMI. To validate our approach, we implemented an IMI prototype and pilot-tested features using the IMI interface to map a sample set of NAACCR data elements to NCIt concepts. 47 out of 301 NAACCR data elements have been mapped to NCIt concepts. Five branches of hierarchical tree have been identified from these mapped concepts for visual inspection. Conclusions IMI provides an interactive, web-based interface for building mappings from data dictionaries to ontologies. Although our pilot-testing scope is limited, our results demonstrate feasibility using IMI for semantic enrichment of cancer registry data by mapping NAACCR data elements to NCIt concepts. |
| first_indexed | 2024-12-16T15:07:33Z |
| format | Article |
| id | doaj.art-52209f4aa78f4ecba6928a209b21101e |
| institution | Directory Open Access Journal |
| issn | 1472-6947 |
| language | English |
| last_indexed | 2024-12-16T15:07:33Z |
| publishDate | 2020-12-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Informatics and Decision Making |
| spelling | doaj.art-52209f4aa78f4ecba6928a209b21101e2022-12-21T22:27:03ZengBMCBMC Medical Informatics and Decision Making1472-69472020-12-0120S101910.1186/s12911-020-01288-7Web-based interactive mapping from data dictionaries to ontologies, with an application to cancer registryShiqiang Tao0Ningzhou Zeng1Isaac Hands2Joseph Hurt-Mueller3Eric B. Durbin4Licong Cui5Guo-Qiang Zhang6The University of Texas Health Science Center at HoustonDepartment of Computer Science, University of KentuckyKentucky Cancer RegistryKentucky Cancer RegistryKentucky Cancer RegistryThe University of Texas Health Science Center at HoustonThe University of Texas Health Science Center at HoustonAbstract Background The Kentucky Cancer Registry (KCR) is a central cancer registry for the state of Kentucky that receives data about incident cancer cases from all healthcare facilities in the state within 6 months of diagnosis. Similar to all other U.S. and Canadian cancer registries, KCR uses a data dictionary provided by the North American Association of Central Cancer Registries (NAACCR) for standardized data entry. The NAACCR data dictionary is not an ontological system. Mapping between the NAACCR data dictionary and the National Cancer Institute (NCI) Thesaurus (NCIt) will facilitate the enrichment, dissemination and utilization of cancer registry data. We introduce a web-based system, called Interactive Mapping Interface (IMI), for creating mappings from data dictionaries to ontologies, in particular from NAACCR to NCIt. Method IMI has been designed as a general approach with three components: (1) ontology library; (2) mapping interface; and (3) recommendation engine. The ontology library provides a list of ontologies as targets for building mappings. The mapping interface consists of six modules: project management, mapping dashboard, access control, logs and comments, hierarchical visualization, and result review and export. The built-in recommendation engine automatically identifies a list of candidate concepts to facilitate the mapping process. Results We report the architecture design and interface features of IMI. To validate our approach, we implemented an IMI prototype and pilot-tested features using the IMI interface to map a sample set of NAACCR data elements to NCIt concepts. 47 out of 301 NAACCR data elements have been mapped to NCIt concepts. Five branches of hierarchical tree have been identified from these mapped concepts for visual inspection. Conclusions IMI provides an interactive, web-based interface for building mappings from data dictionaries to ontologies. Although our pilot-testing scope is limited, our results demonstrate feasibility using IMI for semantic enrichment of cancer registry data by mapping NAACCR data elements to NCIt concepts.https://doi.org/10.1186/s12911-020-01288-7Data dictionaryOntologyConcept mapping |
| spellingShingle | Shiqiang Tao Ningzhou Zeng Isaac Hands Joseph Hurt-Mueller Eric B. Durbin Licong Cui Guo-Qiang Zhang Web-based interactive mapping from data dictionaries to ontologies, with an application to cancer registry BMC Medical Informatics and Decision Making Data dictionary Ontology Concept mapping |
| title | Web-based interactive mapping from data dictionaries to ontologies, with an application to cancer registry |
| title_full | Web-based interactive mapping from data dictionaries to ontologies, with an application to cancer registry |
| title_fullStr | Web-based interactive mapping from data dictionaries to ontologies, with an application to cancer registry |
| title_full_unstemmed | Web-based interactive mapping from data dictionaries to ontologies, with an application to cancer registry |
| title_short | Web-based interactive mapping from data dictionaries to ontologies, with an application to cancer registry |
| title_sort | web based interactive mapping from data dictionaries to ontologies with an application to cancer registry |
| topic | Data dictionary Ontology Concept mapping |
| url | https://doi.org/10.1186/s12911-020-01288-7 |
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